Piff models the point-spread function (PSF) across multiple detectors in the full field of view (FOV). Models can be built in chip coordinates or in sky coordinates if needed to account for the effects of astrometric distortion. The software can fit in either real or Fourier space, and can identify and excise outlier stars that are poor exemplars of the PSF according to some metric.

pieflag compares bandpass-calibrated data to a clean reference channel and identifies and flags essentially all bad data. pieflag compares visibility amplitudes in each frequency channel to a 'reference' channel that is rfi-free (or manually ensured to be rfi-free). pieflag performs this comparison independently for each correlation on each baseline, but will flag all correlations if threshold conditions are met. To operate effectively, pieflag must be supplied with bandpass-calibrated data. pieflag has two core modes of operation (static and dynamic flagging) with an additional extend mode; the type of data largely determines which mode to choose. Instructions for pre-processing data and selecting the mode of operation are provided in the help file. Once pre-processing and selecting the mode of operation are done, pieflag should work well 'out of the box' with its default parameters.

PICsar simulates the magnetosphere of an aligned axisymmetric pulsar and can be used to simulate other arbitrary electromagnetics problems in axisymmetry. Written in Fortran, this special relativistic, electromagnetic, charge conservative particle in cell code features stretchable body-fitted coordinates that follow the surface of a sphere, simplifying the application of boundary conditions in the case of the aligned pulsar; a radiation absorbing outer boundary, which allows a steady state to be set up dynamically and maintained indefinitely from transient initial conditions; and algorithms for injection of charged particles into the simulation domain. PICsar is parallelized using MPI and has been used on research problems with ~1000 CPUs.

Pico is an algorithm that quickly computes the CMB scalar, tensor and lensed power spectra, the matter transfer function and the WMAP 5 year likelihood. It is intended to accelerate parameter estimation codes; Pico can compute the CMB power spectrum and matter transfer function, as well as any computationally expensive likelihoods, in a few milliseconds. It is extremely fast and accurate over a large volume of parameter space and its accuracy can be improved by using a larger training set. More generally, Pico allows using massively parallel computing resources, including distributed computing projects such as Cosmology@Home, to speed up the slow steps in inherently sequential calculations.

Piccard is a Bayesian-inference pipeline for Pulsar Timing Array (PTA) data and interacts with Tempo2 (ascl:1210.015) through libstempo (ascl:2002.017). The code is used mainly for single-pulsar analysis and gravitational-wave detection purposes of full Pulsar Timing Array datasets. Modeling of the data can include correlated signals per frequency or modeled spectrum, with uniform, dipolar, quadrupolar, or anisotropic correlations; multiple error bars and EFACs per pulsar; and white and red noise. Timing models can be numerically included, either by using the design matrix (linear timing model), or by calling libstempo for the full non-linear timing model. Many types of samplers are included. For common-mode mitigation, the signals can be reconstructed mitigating arbitrary signals simultaneously.

picca fits continua of forests, computes correlation functions (1D and 3D) and power-spectra (1D), computes covariance matrices, and fits models for the correlation functions. This set of tools is used for the analysis of the Lyman-alpha forest sample from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) and the Dark Energy Spectroscopic Instrument (DESI).

PICASO (Planetary Intensity Code for Atmospheric Scattering Observations), written in Python, computes the reflected light of exoplanets at any phase geometry using direct and diffuse scattering phase functions and Raman scattering spectral features.

PIAO is an efficient memory-controlled Python code that uses the standard spherical overdensity (SO) algorithm to identify halos. PIAO employs two additional parameters besides the overdensity Δc. The first is the mesh-box size, which splits the whole simulation box into smaller ones then analyzes them one-by-one, thereby overcoming a possible memory limitation problem that can occur when dealing with high-resolution, large-volume simulations. The second is the smoothed particle hydrodynamics (SPH) neighbors number, which is used for the SPH density calculation.

ISOPHOT is one of the instruments on board the Infrared Space Observatory (ISO). ISOPHOT Interactive Analysis (PIA) is a scientific and calibration interactive data analysis tool for ISOPHOT data reduction. Written in IDL under Xwindows, PIA offers a full context sensitive graphical interface for retrieving, accessing and analyzing ISOPHOT data. It is available in two nearly identical versions; a general observers version omits the calibration sequences.

Plages Identification identifies solar plages from Ca II K photographic observations irrespective of noise level, brightness, and other image properties. The code provides an efficient, reliable method for identifying solar plages. The output of the algorithm is an image highlighting the plages and the calculated plage index. Plages Identification is also deployed as a webapp, allowing users to experiment with different hyperparameters and visualize their impact on the output image in real time.

PHOX is a novel, virtual X-ray observatory designed to obtain synthetic observations from hydro-numerical simulations. The code is a photon simulator and can be apply to simulate galaxy clusters. In fact, X-ray observations of clusters of galaxies continue to provide us with an increasingly detailed picture of their structure and of the underlying physical phenomena governing the gaseous component, which dominates their baryonic content. Therefore, it is fundamental to find the most direct and faithful way to compare such observational data with hydrodynamical simulations of cluster-like objects, which can currently include various complex physical processes. Here, we present and analyse synthetic Suzaku observations of two cluster-size haloes obtained by processing with PHOX the hydrodynamical simulation of the large-scale, filament-like region in which they reside. Taking advantage of the simulated data, we test the results inferred from the X-ray analysis of the mock observations against the underlying, known solution. Remarkably, we are able to recover the theoretical temperature distribution of the two haloes by means of the multi-temperature fitting of the synthetic spectra. Moreover, the shapes of the reconstructed distributions allow us to trace the different thermal structure that distinguishes the dynamical state of the two haloes.

Photutils provides tools for detecting and performing photometry of astronomical sources. It can estimate the background and background rms in astronomical images, detect sources in astronomical images, estimate morphological parameters of those sources (e.g., centroid and shape parameters), and perform aperture and PSF photometry. Written in Python, it is an affiliated package of Astropy (ascl:1304.002).

PhotoRApToR (PHOTOmetric Research APplication TO Redshifts) solves regression and classification problems and is specialized for photo-z estimation. PhotoRApToR offers data table manipulation capabilities and 2D and 3D graphics tools for data visualization; it also provides a statistical report for both classification and regression experiments. The code is written in Java; the machine learning model is in C++ to increase the core execution speed.

PhotoParallax calculates photometric parallaxes for distant stars in the Gaia TGAS catalog without any use of physical stellar models or stellar density models of the Milky Way. It uses the geometric parallaxes to calibrate a photometric model that is purely statistical, which is a model of the data rather than a model of stars per se.

Photon makes simple 1D plots in python. It uses mainly matplotlib and PyQt5 and has been build to be fully customizable, allowing the user to change the fontstyle, fontsize, fontcolors, linewidth of the axes, thickness, and other parameters, and see the changes directly in the plot. Once a customization is created, it can be saved in a configuration file and reloaded for future use, allowing reuse of the customization for other plots. The main tool is a graphical user interface and it is started using a command line interface.

PHOTOMETRYPIPELINE (PP) provides calibrated photometry from imaging data obtained with small to medium-sized observatories. PP uses Source Extractor (ascl:1010.064) and SCAMP (ascl:1010.063) to register the image data and perform aperture photometry. Calibration is obtained through matching of field stars with reliable photometric catalogs. PP has been specifically designed for the measurement of asteroid photometry, but can also be used to obtain photometry of fixed sources.

PHOTOM performs photometry of digitized images. It has two basic modes of operation: using an interactive display to specify the positions for the measurements, or obtaining those positions from a file. In both modes of operation PHOTOM performs photometry using either the traditional aperture method or via optimal extraction. When using the traditional aperture extraction method the target aperture can be circular or elliptical and its size and shape can be varied interactively on the display, or by entering values from the keyboard. Both methods allow the background sky level to be either sampled interactively by the manual positioning of an aperture, or automatically from an annulus surrounding the target object. PHOTOM is the photometry backend for the GAIA tool (ascl:1403.024) and is part of the Starlink software collection (ascl:1110.012).

PHOTOe simulates the slowing down of photoelectrons in a gas with arbitrary amounts of H, He and O atoms, and thermal electrons, making PHOTOe useful for investigating the atmospheres of exoplanets. The multi-score scheme used in this code differs from other Monte Carlo approaches in that it efficiently handles rare collisional channels, as in the case of low-abundance excited atoms that undergo superelastic and inelastic collisions. PHOTOe outputs include production and energy yields, steady-state photoelectron flux, and estimates of the 'relaxation' time required by the photoelectrons to slow down from the injection energy to the cutoff energy. The model can also estimate the pathlength travelled by the photoelectrons while relaxing.

Photodynam facilitates so-called "photometric-dynamical" modeling. This model is quite simple and this is reflected in the code base. A N-body code provides coordinates and the photometric code produces light curves based on coordinates.

PhotochemPy finds the steady-state chemical composition of an atmosphere or evolves atmospheres through time. Given inputs such as the stellar UV flux and atmospheric temperature structure, the code creates a photochemical model of a planet's atmosphere. PhotochemPy is a distant fork of Atmos (ascl:2106.039). It provides a Python wrapper to Fortran source code but can also be used exclusively in Fortran.

Photo-z-SQL is a flexible template-based photometric redshift estimation framework that can be seamlessly integrated into a SQL database (or DB) server and executed on demand in SQL. The DB integration eliminates the need to move large photometric datasets outside a database for redshift estimation, and uses the computational capabilities of DB hardware. Photo-z-SQL performs both maximum likelihood and Bayesian estimation and handles inputs of variable photometric filter sets and corresponding broad-band magnitudes.

The Photon Simulator (PhoSim) is a set of fast photon Monte Carlo codes used to calculate the physics of the atmosphere, telescope, and detector by using modern numerical techniques applied to comprehensive physical models. PhoSim generates images by collecting photons into pixels. The code takes the description of what astronomical objects are in the sky at a particular time (the instance catalog) as well as the description of the observing configuration (the operational parameters) and produces a realistic data stream of images that are similar to what a real telescope would produce. PhoSim was developed for large aperture wide field optical telescopes, such as the planned design of LSST. The initial version of the simulator also targeted the LSST telescope and camera design, but the code has since been broadened to include existing telescopes of a related nature. The atmospheric model, in particular, includes physical approximations that are limited to this general context.

PHOENIX is a general-purpose state-of-the-art stellar and planetary atmosphere code. It can calculate atmospheres and spectra of stars all across the HR-diagram including main sequence stars, giants, white dwarfs, stars with winds, TTauri stars, novae, supernovae, brown dwarfs and extrasolar giant planets.

PHOEBE (PHysics Of Eclipsing BinariEs) is a modeling package for eclipsing binary stars, built on top of the widely used WD program (Wilson & Devinney 1971). This introductory paper overviews most important scientific extensions (incorporating observational spectra of eclipsing binaries into the solution-seeking process, extracting individual temperatures from observed color indices, main-sequence constraining and proper treatment of the reddening), numerical innovations (suggested improvements to WD's Differential Corrections method, the new Nelder & Mead's downhill Simplex method) and technical aspects (back-end scripter structure, graphical user interface). While PHOEBE retains 100% WD compatibility, its add-ons are a powerful way to enhance WD by encompassing even more physics and solution reliability.

Persistent_Homology_LSS analyzes halo catalogs using persistent homology to constrain cosmological parameters. It implements persistent homology on a point cloud composed of halos positions in a cubic box from N-body simulations of the universe at large scales. The output of the code are persistence diagrams and images that are used to constrain cosmological parameters from the halo catalog.

PhAst (Photometry-Astrometry) is an IDL astronomical image viewer based on the existing application ATV which displays and analyzes FITS images. It can calibrate raw images, provide astrometric solutions, and do circular aperture photometry. PhAst allows the user to load, process, and blink any number of images. Analysis packages include image calibration, photometry, and astrometry (provided through an interface with SExtractor, SCAMP, and missFITS). PhAst has been designed to generate reports for Minor Planet Center reporting.

PhaseTracer maps out cosmological phases, and potential transitions between them, for Standard Model extensions with any number of scalar fields. The code traces the minima of effective potential as the temperature changes, and then calculates the critical temperatures at which the minima are degenerate. PhaseTracer can use potentials provided by other packages and can be used to analyze cosmological phase transitions which played an important role in the early evolution of the Universe.

phase_space_cosmo_fisher produces Fisher matrix 2D contours from which the constraints on cosmological parameters can be derived. Given a specified redshift array and cosmological case, 2D marginalized contours of cosmological parameters are generated; the code can also plot the derivatives used in the Fisher matrix. In addition, this package can generate 3D plots of qH^2 and other cosmological quantities as a function of redshift and cosmology.

Phantom is a smoothed particle hydrodynamics and magnetohydrodynamics code focused on stellar, galactic, planetary, and high energy astrophysics. It is modular, and handles sink particles, self-gravity, two fluid and one fluid dust, ISM chemistry and cooling, physical viscosity, non-ideal MHD, and more. Its modular structure makes it easy to add new physics to the code.

Phantom-GRAPE is a numerical software library to accelerate collisionless $N$-body simulation with SIMD instruction set on x86 architecture. The Newton's forces and also central forces with an arbitrary shape f(r), which have a finite cutoff radius r_cut (i.e. f(r)=0 at r>r_cut), can be quickly computed.

The PGPLOT Graphics Subroutine Library is a Fortran- or C-callable, device-independent graphics package for making simple scientific graphs. It is intended for making graphical images of publication quality with minimum effort on the part of the user. For most applications, the program can be device-independent, and the output can be directed to the appropriate device at run time.

The PGPLOT library consists of two major parts: a device-independent part and a set of device-dependent "device handler" subroutines for output on various terminals, image displays, dot-matrix printers, laser printers, and pen plotters. Common file formats supported include PostScript and GIF.

PGPLOT itself is written mostly in standard Fortran-77, with a few non-standard, system-dependent subroutines. PGPLOT subroutines can be called directly from a Fortran-77 or Fortran-90 program. A C binding library (cpgplot) and header file (cpgplot.h) are provided that allow PGPLOT to be called from a C or C++ program; the binding library handles conversion between C and Fortran argument-passing conventions.

PGOPHER simulates and fits rotational, vibrational, and electronic spectra. It handles linear molecules and symmetric and asymmetric tops, including effects due to unpaired electrons and nuclear spin, with a separate mode for vibrational structure. The code performs many sorts of transitions, including Raman, multiphoton, and forbidden transitions. It can simulate multiple species and states simultaneously, including special effects such as perturbations and state dependent predissociation. Fitting can be to line positions, intensities, or band contours. PGOPHER uses a standard graphical user interface and makes comparison with, and fitting to, spectra from various sources easy. In addition to overlaying numerical spectra, it is also possible to overlay pictures from pdf files and even plate spectra to assist in checking that published constants are being used correctly.

PFITS performs data reduction of spectra, including dark removal and flat fielding; this software was a standard 1983 Reticon reduction package available at the University of Texas. It was based on the plotting program PCOSY by Gary Ferland, and in 1985 was updated by Andrew McWilliam.

pfits reads, manipulates and processes PSRFITS format search- and fold-mode pulsar astronomy data files. It summerizes the header information in a PSRFITS file, reproduces some of fv's (ascl:1205.005) functionality, and allows the user to obtain detailed information about the file. It can determine whether the data is search mode or fold mode and plot the profile, color scale image, frequency time, sum in frequency, and 4-pol data, as appropriate. pfits can also read in a search mode file, dedisperses, and frequency-sums (if requested), and offers an option to output multiple dispersed data files, among other tasks.

PFANT computes a synthetic spectrum assuming local thermodynamic equilibrium from a given stellar model atmosphere and lists of atomic and molecular lines; it provides large wavelength coverage and line lists from ultraviolet through the visible and near-infrared. PFANT has been optimized for speed, offers error reporting, and command-line configuration options.

PEXO provides a global modeling framework for ns timing, μas astrometry, and μm/s radial velocities. It can account for binary motion and stellar reflex motions induced by planetary companions and also treat various relativistic effects both in the Solar System and in the target system (Roemer, Shapiro, and Einstein delays). PEXO is able to model timing to a precision of 1 ns, astrometry to a precision of 1 μas, and radial velocity to a precision of 1 μm/s.

PETSc (Portable, Extensible Toolkit for Scientific Computation) provides a suite of data structures and routines for the scalable (parallel) solution of scientific applications modeled by partial differential equations, and is intended for use in large-scale application projects. The toolkit includes a large suite of parallel linear, nonlinear equation solvers and ODE integrators that are easily used in application codes written in C, C++, Fortran and Python. PETSc provides many of the mechanisms needed within parallel application codes, such as simple parallel matrix and vector assembly routines that allow the overlap of communication and computation. In addition, PETSc (pronounced PET-see) includes support for managing parallel PDE discretizations.

PetroFit calculates Petrosian properties, such as radii and concentration indices; it also fits galaxy light profiles. The package, built on Photutils (ascl:1609.011), includes tools for performing accurate photometry, segmentations, Petrosian properties, and fitting.

petitRADTRANS (pRT) calculates transmission and emission spectra of exoplanets for clear and cloudy planets. It also incorporates an easy subpackage for running retrievals with nested sampling. It allows the calculation of emission or transmission spectra, at low or high resolution, clear or cloudy, and includes a retrieval module to fit a petitRADTRANS model to spectral data. pRT has two different opacity treatment modes. The low resolution mode runs calculations at λ/Δλ ≤ 1000 using the so-called correlated-k treatment for opacities. The high resolution mode runs calculations at λ/Δλ ≤ 10⁶, using a line-by-line opacity treatment.

The N-body code PETAR (ParticlE Tree & particle-particle & Algorithmic Regularization) combines the methods of Barnes-Hut tree, Hermite integrator and slow-down algorithmic regularization (SDAR). It accurately handles an arbitrary fraction of multiple systems (e.g. binaries, triples) while keeping a high performance by using the hybrid parallelization methods with MPI, OpenMP, SIMD instructions and GPU. PETAR has very good agreement with NBODY6++GPU results on the long-term evolution of the global structure, binary orbits and escapers and is significantly faster when used on a highly configured GPU desktop computer. PETAR scales well when the number of cores increase on the Cray XC50 supercomputer, allowing a solution to the ten million-body problem which covers the region of ultra compact dwarfs and nuclear star clusters.

Period04 statistically analyzes large astronomical time series containing gaps. It calculates formal uncertainties, can extract the individual frequencies from the multiperiodic content of time series, and provides a flexible interface to perform multiple-frequency fits with a combination of least-squares fitting and the discrete Fourier transform algorithm. Period04, written in Java/C++, supports the SAMP communication protocol to provide interoperability with other applications of the Virtual Observatory. It is a reworked and extended version of Period98 (Sperl 1998) and PERIOD/PERDET (Breger 1990).

PERIOD searches for periodicities in data. It is distributed within the Starlink software collection (ascl:1110.012).

perfectns performs dynamic nested sampling and standard nested sampling for spherically symmetric likelihoods and priors, and analyses the samples produced. The spherical symmetry allows the nested sampling algorithm to be followed “perfectly” - i.e. without implementation-specific errors correlations between samples. It is intended for use in research into the statistical properties of nested sampling, and to provide a benchmark for testing the performance of nested sampling software packages used for practical problems - which rely on numerical techniques to produce approximately uncorrelated samples.

PEREGRINE performs full parameter estimation on gravitational wave signals. Using an internal Truncated Marginal Neural Ratio Estimation (TMNRE) algorithm and building upon the swyft (ascl:2302.016) code to efficiently access marginal posteriors, PEREGRINE conducts a sequential simulation-based inference approach to support the analysis of both transient and continuous gravitational wave sources. The code can fully reconstruct the posterior distributions for all parameters of spinning, precessing compact binary mergers using waveform approximants.

PEPITA (Prediction of Exoplanet Precisions using Information in Transit Analysis) makes predictions for the precision of exoplanet parameters using transit light-curves. The code uses information analysis techniques to predict the best precision that can be obtained by fitting a light-curve without actually needing to perform the fit, thus allowing more efficient planning of observations or re-observations.

Planetary Ephemeris Program (PEP) computes numerical ephemerides and simultaneously analyzes a heterogeneous collection of astrometric data. Written in Fortran, it is a general-purpose astrometric data-analysis program and models orbital motion in the solar system, determines orbital initial conditions and planetary masses, and has been used to, for example, measure general relativistic effects and test physics theories beyond the standard model. PEP also models pulsar motions and distant radio sources, and can solve for sky coordinates for radio sources, plasma densities, and the second harmonic of the Sun's gravitational field.

PENTACLE calculates gravitational interactions between particles within a cut-off radius and a Barnes-Hut tree method for gravity from particles beyond. It uses FDPS (ascl:1604.011) to parallelize a Barnes-Hut tree algorithm for a memory-distributed supercomputer. The software can handle 1-10 million particles in a high-resolution N-body simulation on CPU clusters for collisional dynamics, including physical collisions in a planetesimal disc.

The Pencil code is a high-order finite-difference code for compressible hydrodynamic flows with magnetic fields. It is highly modular and can easily be adapted to different types of problems. The code runs efficiently under MPI on massively parallel shared- or distributed-memory computers, like e.g. large Beowulf clusters. The Pencil code is primarily designed to deal with weakly compressible turbulent flows. To achieve good parallelization, explicit (as opposed to compact) finite differences are used. Typical scientific targets include driven MHD turbulence in a periodic box, convection in a slab with non-periodic upper and lower boundaries, a convective star embedded in a fully nonperiodic box, accretion disc turbulence in the shearing sheet approximation, self-gravity, non-local radiation transfer, dust particle evolution with feedback on the gas, etc. A range of artificial viscosity and diffusion schemes can be invoked to deal with supersonic flows. For direct simulations regular viscosity and diffusion is being used. The code is written in well-commented Fortran90.

Pelican is an efficient, lightweight C++ library for quasi-real time data processing. The library provides a framework to separate the acquisition and processing of data, allowing the scalability and flexibility to fit a number of scenarios. Though its origin was in radio astronomy, processing data as it arrives from a telescope, the framework is sufficiently generic to be useful to any application that requires the efficient processing of incoming data streams.

PÉGASE (Projet d'Étude des GAlaxies par Synthèse Évolutive) is a code to compute the spectral evolution of galaxies. The evolution of the stars, gas and metals is followed for a law of star formation and a stellar initial mass function. The stellar evolutionary tracks extend from the main sequence to the white dwarf stage. The emission of the gas in HII regions is also taken into account. The main improvement in version 2 is the use of evolutionary tracks of different metallicities (from 10-4 to 5×solar). The effect of extinction by dust is also modelled using a radiative transfer code. PÉGASE.2 uses the BaSeL library of stellar spectra and can therefore synthesize low-resolution (R~200) ultraviolet to near-infrared spectra of Hubble sequence galaxies as well as of starbursts.

PÉGASE-HR is a code aimed at computing synthetic evolutive optical spectra of galaxies with a very high resolution (R=10 000, or dlambda=0.55) in the range Lambda=[4000, 6800] Angstroms. PÉGASE-HR is the result of combining the code PÉGASE.2 with the high-resolution stellar library ÉLODIE. This code can also be used at low resolution (R=200) over the range covered by the BaSeL library (from far UV to the near IR), and then produces the same results as PÉGASE.2. In PEGASE-HR, the BaSeL library is replaced by a grid of spectra interpolated from the high-resolution ÉLODIE library of stellar spectra. The ÉLODIE library is a stellar database of 1959 spectra for 1503 stars, observed with the echelle spectrograph ÉLODIE on the 193 cm telescope at the Observatoire de Haute Provence.

The PEC (Period Error Calculator) algorithm estimates the period error for eclipsing binaries observed by the Kepler Mission. The algorithm is based on propagation of error theory and assumes that observation of every light curve peak/minimum in a long time-series observation can be unambiguously identified. A simple C implementation of the PEC algorithm is available.

The NVIDIA GPU-based pipeline code peasoup provides a one-step pulsar search, including searching for pulsars with up to moderate accelerations, with only one command. Its features include dedispersion, dereddening in the Fourier domain, resampling, peak detection, and optional time series folding. peasoup's output is the candidate list.

PDT removes systematic trends in light curves. It finds clusters of light curves that are highly correlated using machine learning, constructs one master trend per cluster and detrends an individual light curve using the constructed master trends by minimizing residuals while constraining coefficients to be positive.

pdspy fits Monte Carlo radiative transfer models for protostellar/protoplanetary disks to ALMA continuum and spectral line datasets using Markov Chain Monte Carlo fitting. It contains two tools, one to fit ALMA continuum visibilities and broadband spectral energy distributions (SEDs) with full radiative transfer models, and another to fit ALMA spectral line visibilities with protoplanetary disk models that include a vertically isothermal, power law temperature distribution. No radiative equilibrium calculation is done.

Ultraviolet photons from O and B stars strongly influence the structure and emission spectra of the interstellar medium. The UV photons energetic enough to ionize hydrogen (hν > 13.6 eV) will create the H II region around the star, but lower energy UV photons escape. These far-UV photons (6 eV < hν < 13.6 eV) are still energetic enough to photodissociate molecules and to ionize low ionization-potential atoms such as carbon, silicon, and sulfur. They thus create a photodissociation region (PDR) just outside the H II region. In aggregate, these PDRs dominate the heating and cooling of the neutral interstellar medium.

The PDR Toolbox is a science-enabling Python package for the community, designed to help astronomers determine the physical parameters of photodissociation regions from observations. Typical observations of both Galactic and extragalactic PDRs come from ground- and space-based millimeter, submillimeter, and far-infrared telescopes such as ALMA, SOFIA, JWST, Spitzer, and Herschel. Given a set of observations of spectral line or continuum intensities, PDR Toolbox can compute best-fit FUV incident intensity and cloud density based on our models of PDR emission.

PDM2 (Phase Dispersion Minimization) ddetermines periodic components of data sets with erratic time intervals, poor coverage, non-sine-wave curve shape, and/or large noise components. Essentially a least-squares fitting technique, the fit is relative to the mean curve as defined by the means of each bin; the code simultaneously obtains the best least-squares light curve and the best period. PDM2 allows an arbitrary degree of smoothing and provides improved curve fits, suppressed subharmonics, and beta function statistics.

PDFchem models the cold ISM at moderate and large scales using functions connecting the quantities of the local and the observed visual extinctions and the local number density with probability density functions. For any given observed visual extinction sampled with thousands of clouds, the algorithm instantly computes the average abundances of the most important species and performs radiative transfer calculations to estimate the average emission of the most commonly observed lines.

The Periodogram Comparison for Optimizing Small Transiting Planet Detection R code compares two periodogram algorithms for detecting transiting exoplanets: the Box-fitting Least Squares (BLS) and the Transit Comb Filter (TCF). It calculates the False Alarm Probability (FAP) based on extreme value theory and signal-to-noise ratio (SNR) metrics to quantify periodogram peak significance. The comparison approach is aimed at optimizing the detection of small transiting planets in future transiting exoplanet surveys. The code can be extended for comparing any set of periodograms.

PCCDPACK analyzes polarimetry data. The set of routines is written in CL-IRAF (including compiled Fortran codes) and analyzes dozens of point objects simultaneously on the same CCD image. A subpackage, specpol, is included to analyze spectropolarimetry data.

PCAT (Probabilistic Cataloger) samples from the posterior distribution of a metamodel, i.e., union of models with different dimensionality, to compare the models. This is achieved via transdimensional proposals such as births, deaths, splits and merges in addition to the within-model proposals. This method avoids noisy estimates of the Bayesian evidence that may not reliably distinguish models when sampling from the posterior probability distribution of each model.

The code has been applied in two different subfields of astronomy: high energy photometry, where transdimensional elements are gamma-ray point sources; and strong lensing, where light-deflecting dark matter subhalos take the role of transdimensional elements.

The mid-infrared spectra of ultraluminous infrared galaxies (ULIRGs) contain a variety of spectral features that can be used as diagnostics to characterize the spectra. However, such diagnostics are biased by our prior prejudices on the origin of the features. Moreover, by using only part of the spectrum they do not utilize the full information content of the spectra. Blind statistical techniques such as principal component analysis (PCA) consider the whole spectrum, find correlated features and separate them out into distinct components.

This code, written in IDL, classifies principal components of IRS spectra to define a new classification scheme using 5D Gaussian mixtures modelling. The five PCs and average spectra for the four classifications to classify objects are made available with the code.

The equation of state (EOS) of dense matter is a crucial input for the neutron-star structure calculations. This Fortran code can obtain a "unified EOS" in the many-body calculations based on a single effective nuclear Hamiltonian, and is valid in all regions of the neutron star interior. For unified EOSs, the transitions between the outer crust and the inner crust and between the inner crust and the core are obtained as a result of many-body calculations.

PBMC (Pre-Conditioned Backward Monte Carlo) solves the vector Radiative Transport Equation (vRTE) and can be applied to planetary atmospheres irradiated from above. The code builds the solution by simulating the photon trajectories from the detector towards the radiation source, i.e. in the reverse order of the actual photon displacements. In accounting for the polarization in the sampling of photon propagation directions and pre-conditioning the scattering matrix with information from the scattering matrices of prior (in the BMC integration order) photon collisions, PBMC avoids the unstable and biased solutions of classical BMC algorithms for conservative, optically-thick, strongly-polarizing media such as Rayleigh atmospheres.

We present Particle-Based Lensing (PBL), a new technique for gravitational lensing mass reconstructions of galaxy clusters. Traditionally, most methods have employed either a finite inversion or gridding to turn observational lensed galaxy ellipticities into an estimate of the surface mass density of a galaxy cluster. We approach the problem from a different perspective, motivated by the success of multi-scale analysis in smoothed particle hydrodynamics. In PBL, we treat each of the lensed galaxies as a particle and then reconstruct the potential by smoothing over a local kernel with variable smoothing scale. In this way, we can tune a reconstruction to produce constant signal-noise throughout, and maximally exploit regions of high information density.

PBL is designed to include all lensing observables, including multiple image positions and fluxes from strong lensing, as well as weak lensing signals including shear and flexion. In this paper, however, we describe a shear-only reconstruction, and apply the method to several test cases, including simulated lensing clusters, as well as the well-studied ``Bullet Cluster'' (1E0657-56). In the former cases, we show that PBL is better able to identify cusps and substructures than are grid-based reconstructions, and in the latter case, we show that PBL is able to identify substructure in the Bullet Cluster without even exploiting strong lensing measurements.

PASTA performs median stacking of astronomical sources. Written in Python, it can filter sources, provide stack statistics, generate Karma annotations, format source lists, and read information from stacked Flexible Image Transport System (FITS) images. PASTA was originally written to examine polarization stack properties and includes a Monte Carlo modeler for obtaining true polarized intensity from the observed polarization of a stack. PASTA is also useful as a generic stacking tool, even if polarization properties are not being examined.

In dense clusters a bewildering variety of interactions between stars can be observed, ranging from simple encounters to collisions and other mass-transfer encounters. With faster and special-purpose computers like GRAPE, the amount of data per simulation is now exceeding 1TB. Visualization of such data has now become a complex 4D data-mining problem, combining space and time, and finding interesting events in these large datasets. We have recently starting using the virtual reality simulator, installed in the Hayden Planetarium in the American Museum for Natural History, to tackle some of these problem. partiview is a program that enables you to visualize and animate particle data. partiview runs on relatively simple desktops and laptops, but is mostly compatible with its big brother VirDir.

ParticleGridMapper.jl interpolates particle data onto either a Cartesian (uniform) grid or an adaptive mesh refinement (AMR) grid where each cell contains no more than one particle. The AMR grid can be trimmed with a user-defined maximum level of refinement. Three different interpolation schemes are supported: nearest grid point (NGP), smoothed-particle hydrodynamics (SPH), and Meshless finite mass (MFM). It is multi-threading parallel.

Piernik is a multi-fluid grid magnetohydrodynamic (MHD) code based on the Relaxing Total Variation Diminishing (RTVD) conservative scheme. The original code has been extended by addition of dust described within the particle approximation. The dust is now described as a system of interacting particles. The particles can interact with gas, which is described as a fluid. The comparison between the test problem results and the results coming from fluid simulations made with Piernik code shows the most important differences between fluid and particle approximations used to describe dynamical evolution of dust under astrophysical conditions.

The Parthenon framework, derived from Athena++ (ascl:1912.005), handles massively-parallel, device-accelerated adaptive mesh refinement. It provides a device first/device resident approach, transparent packing of data across blocks (to reduce/hide kernel launch latency), and direct device-to-device communication via asynchronous, one-sided MPI communication to enable high performance. Parthenon uses an intermediate abstraction layer to hide complexity of device kernel launches, offers support for particles and abstract variable control via metadata tags, and has a flexible plug-in package system.

ParSNIP learns generative models of transient light curves from a large dataset of transient light curves. It is designed to work with light curves in sncosmo format using the lcdata package to handle large datasets. This code can be used for classification of transients, cosmological distance estimation, and identifying novel transients.

ParselTongue is a Python interface to classic AIPS, Obit and possibly other task-based data reduction packages. It serves as the software infrastructure for some of the ALBUS implementation. It allows you to run AIPS tasks, and access AIPS headers and extension tables from Python. There is also support for running Obit tasks and accessing data in FITS files. Full access to the visibilities in AIPS UV data is also available.

PARSEC (PARametrized Simulation Engine for Cosmic rays) is a simulation engine for fast generation of ultra-high energy cosmic ray data based on parameterizations of common assumptions of UHECR origin and propagation. Implemented are deflections in unstructured turbulent extragalactic fields, energy losses for protons due to photo-pion production and electron-pair production, as well as effects from the expansion of the universe. Additionally, a simple model to estimate propagation effects from iron nuclei is included. Deflections in the Galactic magnetic field are included using a matrix approach with precalculated lenses generated from backtracked cosmic rays. The PARSEC program is based on object oriented programming paradigms enabling users to extend the implemented models and is steerable with a graphical user interface.

PARS (Paint the Atmospheres of Rotating Stars) quickly computes magnitudes and spectra of rotating stellar models. It uses the star's mass, equatorial radius, rotational speed, luminosity, and inclination as input; the models incorporate Roche mass distribution (where all mass is at the center of the star), solid body rotation, and collinearity of effective gravity and energy flux.

PARAVT offers massive parallel computation of Voronoi tessellations (VT hereafter) in large data sets. The code is focused for astrophysical purposes where VT densities and neighbors are widely used. There are several serial Voronoi tessellation codes, however no open source and parallel implementations are available to handle the large number of particles/galaxies in current N-body simulations and sky surveys. Parallelization is implemented under MPI and VT using Qhull library. Domain decomposition take into account consistent boundary computation between tasks, and support periodic conditions. In addition, the code compute neighbors lists, Voronoi density and Voronoi cell volumes for each particle, and can compute density on a regular grid.

ParaView is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView's batch processing capabilities.

ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of terascale as well as on laptops for smaller data.

ParaMonte contains serial and parallel Monte Carlo routines for sampling mathematical objective functions of arbitrary-dimensions. It is used for posterior distributions of Bayesian models in data science, Machine Learning, and scientific inference and unifies the automation of Monte Carlo simulations. ParaMonte is user friendly and accessible from multiple programming environments, including C, C++, Fortran, MATLAB, and Python, and offers high performance at runtime and scalability across many parallel processors.

Paramo (PArticle and RAdiation MOnitor) numerically solves the Fokker-Planck kinetic equation, which is used to model the dynamics of a particle distribution function, using a robust implicit method, for the proper modeling of the acceleration processes, and accounts for accurate cooling coefficient (e.g., radiative cooling with Klein-Nishina corrections). The numerical solution at every time step is used to calculate radiations processes, namely synchrotron and IC, with sophisticated numerical techniques, obtaining the multi-wavelength spectral evolution of the system.

We consider the problem of fitting a parametric model to time-series data that are afflicted by correlated noise. The noise is represented by a sum of two stationary Gaussian processes: one that is uncorrelated in time, and another that has a power spectral density varying as $1/f^gamma$. We present an accurate and fast [O(N)] algorithm for parameter estimation based on computing the likelihood in a wavelet basis. The method is illustrated and tested using simulated time-series photometry of exoplanetary transits, with particular attention to estimating the midtransit time. We compare our method to two other methods that have been used in the literature, the time-averaging method and the residual-permutation method. For noise processes that obey our assumptions, the algorithm presented here gives more accurate results for midtransit times and truer estimates of their uncertainties.

PARAMESH is a package of Fortran 90 subroutines designed to provide an application developer with an easy route to extend an existing serial code which uses a logically cartesian structured mesh into a parallel code with adaptive mesh refinement (AMR). Alternatively, in its simplest use, and with minimal effort, it can operate as a domain decomposition tool for users who want to parallelize their serial codes, but who do not wish to use adaptivity.

The package builds a hierarchy of sub-grids to cover the computational domain, with spatial resolution varying to satisfy the demands of the application. These sub-grid blocks form the nodes of a tree data-structure (quad-tree in 2D or oct-tree in 3D). Each grid block has a logically cartesian mesh. The package supports 1, 2 and 3D models. PARAMESH is released under the NASA-wide Open-Source software license.

Modern N-body cosmological simulations contain billions ($10^9$) of dark matter particles. These simulations require hundreds to thousands of gigabytes of memory, and employ hundreds to tens of thousands of processing cores on many compute nodes. In order to study the distribution of dark matter in a cosmological simulation, the dark matter halos must be identified using a halo finder, which establishes the halo membership of every particle in the simulation. The resources required for halo finding are similar to the requirements for the simulation itself. In particular, simulations have become too extensive to use commonly-employed halo finders, such that the computational requirements to identify halos must now be spread across multiple nodes and cores. Here we present a scalable-parallel halo finding method called Parallel HOP for large-scale cosmological simulation data. Based on the halo finder HOP, it utilizes MPI and domain decomposition to distribute the halo finding workload across multiple compute nodes, enabling analysis of much larger datasets than is possible with the strictly serial or previous parallel implementations of HOP. We provide a reference implementation of this method as a part of the toolkit yt, an analysis toolkit for Adaptive Mesh Refinement (AMR) data that includes complementary analysis modules. Additionally, we discuss a suite of benchmarks that demonstrate that this method scales well up to several hundred tasks and datasets in excess of $2000^3$ particles. The Parallel HOP method and our implementation can be readily applied to any kind of N-body simulation data and is therefore widely applicable. Parallel HOP is part of yt.

The PHANGS-ALMA pipeline process data from radio interferometer observations. It uses CASA (ascl:1107.013), AstroPy (ascl:1304.002), and other affiliated packages to process data from calibrated visibilities to science-ready spectral cubes and maps. The PHANGS-ALMA pipeline offers a flexible alternative to the scriptForImaging script distributed by ALMA. The pipeline runs in two separate software environments: CASA 5.6 or 5.7 (staging, imaging and post-processing) and Python 3.6 or later (derived products) with modern versions of several packages.

Pangloss reconstructs all the mass within a light cone through the Universe. Understanding complex mass distributions like this is important for accurate time delay lens cosmography, and also for accurate lens magnification estimation. It aspires to use all available data in an attempt to make the best of all mass maps.

Pandora searches for exomoons by employing an analytical photodynamical model that includes stellar limb darkening, full and partial planet-moon eclipses, and barycentric motion of planet and moon. The code can be used with nested samplers such as UltraNest (ascl:1611.001) or dynesty (ascl:1809.013). Pandora is fast, calculating 10,000 models and log-likelihood evaluation per second (give or take an order of magnitude, depending on parameters and data); this means that a retrieval with 250 Mio. evaluations until convergence takes about 5 hours on a single core. For searches in large amounts of data, it is most efficient to assign one core per light curve.

PandExo generates instrument simulations of JWST’s NIRSpec, NIRCam, NIRISS and NIRCam and HST WFC3 for planning exoplanet observations. It uses throughput calculations from STScI’s Exposure Time Calculator, Pandeia, and offers both an online tool and a python package.

panco2 extracts measurements of the pressure profile of the hot gas inside galaxy clusters from millimeter-wave observations. The extraction is performed using forward modeling the millimeter-wave signal of clusters and MCMC sampling of a posterior distribution for the parameters given the input data. Many characteristic features of millimeter-wave observations can be taken into account, such as filtering (both through PSF smearing and transfer functions), point source contamination, and correlated noise.

PampelMuse analyzes integral-field spectroscopic observations of crowded stellar fields and provides several subroutines to perform the individual steps of the data analysis. All analysis steps assume that the IFS data has been properly reduced and that all the instrumental artifacts have been removed. PampelMuse is designed to correctly handle IFS data regardless of which instrument was used to observe the data. In addition to the actual data, the software also requires an estimate of the variances for the analysis; optionally, it can use a bad pixel mask. The analysis relies on the presence of a reference catalogue, containing coordinates and magnitudes of the stars in and around the observed field.

PAMELA is an implementation of the optimal extraction algorithm for long-slit CCD spectroscopy and is well suited for time-series spectroscopy. It properly implements the optimal extraction algorithm for curved spectra, including on-the-fly cosmic ray rejection as well as proper calculation and propagation of the errors. The software is distributed as part of the Starlink software collection (ascl:1110.012).

paltas conducts simulation-based inference on strong gravitational lensing images. It builds on lenstronomy (ascl:1804.012) to create large datasets of strong lensing images with realistic low-mass halos, Hubble Space Telescope (HST) observational effects, and galaxy light from HST's COSMOS field. paltas also includes the capability to easily train neural posterior estimators of the parameters of the lensing system and to run hierarchical inference on test populations.

Palettable is a library of color palettes for Python. The code is written in pure Python with no dependencies; it can be used to supply color maps for matplotlib plots, customize matplotlib plots, and to supply colors for a web application.

The PAL library is a partial re-implementation of Pat Wallace's popular SLALIB library written in C using a Gnu GPL license and layered on top of the IAU's SOFA library (or the BSD-licensed ERFA) where appropriate. PAL attempts to stick to the SLA C API where possible.

PAHFIT is an IDL tool for decomposing Spitzer IRS spectra of PAH emission sources, with a special emphasis on the careful recovery of ambiguous silicate absorption, and weak, blended dust emission features. PAHFIT is primarily designed for use with full 5-35 micron Spitzer low-resolution IRS spectra. PAHFIT is a flexible tool for fitting spectra, and you can add or disable features, compute combined flux bands, change fitting limits, etc., without changing the code.

PAHFIT uses a simple, physically-motivated model, consisting of starlight, thermal dust continuum in a small number of fixed temperature bins, resolved dust features and feature blends, prominent emission lines (which themselves can be blended with dust features), as well as simple fully-mixed or screen dust extinction, dominated by the silicate absorption bands at 9.7 and 18 microns. Most model components are held fixed or are tightly constrained. PAHFIT uses Drude profiles to recover the full strength of dust emission features and blends, including the significant power in the wings of the broad emission profiles. This means the resulting feature strengths are larger (by factors of 2-4) than are recovered by methods which estimate the underlying continuum using line segments or spline curves fit through fiducial wavelength anchors.

PAHDecomp models mid-infrared spectra of galaxies; it is based on the popular PAHFIT code (ascl:1210.009). In contrast to PAHFIT, this model decomposes the continuum into a star-forming component and an obscured nuclear component based on Bayesian priors on the shape of the star-forming component (using templates + prior on extinction), making this tool ideally suited for modeling the spectra of heavily obscured galaxies. PAHDecomp successfully recovers properties of Compact Obscured Nuclei (CONs) where the inferred nuclear optical depth strongly correlates with the surface brightness of HCN-vib emission in the millimeter. This is currently set up to run on the short low modules of Spitzer IRS data (5.2 - 14.2 microns) but will be ideal for JWST/MIRI MRS data in the future.

PACSman provides an alternative for several reduction and analysis steps performed in HIPE (ascl:1111.001) on PACS spectroscopic data; it is written in IDL. Among the operations possible with it are transient correction, line fitting, map projection, and map analysis, and unchopped scan, chop/nod, and the decommissioned wavelength switching observation modes are supported.

PACMAN (Planetary Atmosphere, Crust, and MANtle geochemical evolution) runs a coupled redox-geochemical-climate evolution model. It runs Monte Carlo calculations over nominal parameter ranges, including number of iterations and number of cores for parallelization, which can be altered to reproduce different scenarios and sensitivity tests. Model outputs and corresponding input parameters are saved in separate files which are used to plot results; the the user can choose which outputs to plot, including all successful outputs, nominal Earth outputs, waterworld false positives, desertworld false positives, and high CO2:H2O false positives. Among other functions, PACMAN contains functions for interpolating the pre-computed Outgoing Longwave Radiation (OLR) grid, the atmosphere-ocean partitioning grid, and the stratospheric water vapor grid, calculating bond albedo and outgassing fluxes.

Pacerman, written in IDL, is a new method to calculate Faraday rotation measure maps from multi-frequency polarisation angle data. In order to solve the so called n-pi-ambiguity problem which arises from the observationally ambiguity of the polarisation angle which is only determined up to additions of n times pi, where n is an integer, we suggest using a global scheme. Instead of solving the n-pi-ambiguity for each data point independently, our algorithm, which we chose to call Pacerman solves the n-pi-ambiguity for a high signal-to-noise region "democratically" and uses this information to assist computations in adjacent low signal-to-noise areas.

PACCE (Perl Algorithm to Compute continuum and Equivalent Widths) computes continuum and equivalent widths. PACCE is able to determine mean continuum and continuum at line center values, which are helpful in stellar population studies, and is also able to compute the uncertainties in the equivalent widths using photon statistics.

p3d is semi-automatic data-reduction tool designed to be used with fiber-fed integral-field spectrographs. p3d is a highly general and freely available tool based on IDL but can be used with full functionality without an IDL license. It is easily extended to include improved algorithms, new visualization tools, and support for additional instruments. It uses a novel algorithm for automatic finding and tracing of spectra on the detector, and includes two methods of optimal spectrum extraction in addition to standard aperture extraction. p3d also provides tools to combine several images, perform wavelength calibration and flat field data.

P2SAD computes the Particle Phase Space Average Density (P2SAD) in galactic haloes. The model for the calculation is based on the stable clustering hypothesis in phase space, the spherical collapse model, and tidal disruption of substructures. The multiscale prediction for P2SAD computed by this IDL code can be used to estimate signals sensitive to the small scale structure of dark matter distributions (e.g. dark matter annihilation). The code computes P2SAD averaged over the whole virialized region of a Milky-Way-size halo at redshift zero.

P2DFFT is a parallelized version of 2DFFT (ascl:1608.015). It isolates and measures the spiral arm pitch angle of galaxies. The code allows direct input of FITS images, offers the option to output inverse Fourier transform FITS images, and generates idealized logarithmic spiral test images of a specified size that have 1 to 6 arms with pitch angles of -75 degrees to 75 degrees​​. Further, it can output Fourier amplitude versus inner radius and pitch angle versus inner radius for each Fourier component (m = 0 to m = 6), and calculates the Fourier amplitude weighted mean pitch angle across m = 1 to m = 6 versus inner radius.

p-winds produces simplified, 1-D models of the upper atmosphere of a planet and performs radiative transfer to calculate observable spectral signatures. The scalable implementation of 1D models allows for atmospheric retrievals to calculate atmospheric escape rates and temperatures. In addition, the modular implementation allows for a smooth plugging-in of more complex descriptions to forward model their corresponding spectral signatures (e.g., self-consistent or 3D models).

oxkat semi-automatically performs calibration and imaging of data from the MeerKAT radio telescope. Taking as input raw visibilities in Measurement Set format, the entire processing workflow is covered, from flagging and reference calibration, to imaging and self-calibration, and (optionally) direction-dependent calibration. The oxkat scripts use Python, and draw on numerous existing radio astronomy packages, including CASA (ascl:1107.013), WSClean (ascl:1408.023), and CubiCal (ascl:1805.031), among others, that are containerized using Singularity. Submission scripts for slurm and PBS job schedulers are automatically generated where necessary, catering for HPC facilities that are commonly used for processing MeerKAT data.

OXAF provides a simplified model of Seyfert Active Galactic Nucleus (AGN) continuum emission designed for photoionization modeling. It removes degeneracies in the effects of AGN parameters on model spectral shapes and reproduces the diversity of spectral shapes that arise in physically-based models. OXAF accepts three parameters which directly describe the shape of the output ionizing spectrum: the energy of the peak of the accretion disk emission E_peak, the photon power-law index of the non-thermal X-ray emission Γ, and the proportion of the total flux which is emitted in the non-thermal component p_NT. OXAF accounts for opacity effects where the accretion disk is ionized because it inherits the ‘color correction’ of OPTXAGNF, the physical model upon which OXAF is based.

ovejero conducts hierarchical inference of strongly-lensed systems with Bayesian neural networks. It requires lenstronomy (ascl:1804.012) and fastell (ascl:9910.003) to run lens models with elliptical mass distributions. The code trains Bayesian Neural Networks (BNNs) to predict posteriors on strong gravitational lensing images and can integrate with forward modeling tools in lenstronomy to allow comparison between BNN outputs and more traditional methods. ovejero also provides hierarchical inference tools to generate population parameter estimates and unbiased posteriors on independent test sets.

Ostrich emulates surrogate models for complex and expensive functions using Principal Component Analysis (PCA) to decompose a signal, then interpolate the PCA weights over the parameters θ using a Gaussian Process interpolator. The code is trained on samples from the expensive functions, recreating and interpolating between those training samples with reduced computational cost, and recalculating for each use.

Comparing properties of discovered trans-Neptunian Objects (TNOs) with dynamical models is impossible due to the observational biases that exist in surveys. The OSSOS Survey Simulator takes an intrinsic orbital model (from, for example, the output of a dynamical Kuiper belt emplacement simulation) and applies the survey biases, so the biased simulated objects can be directly compared with real discoveries.

OSPREI simulates the Sun-to-Earth (or satellite) behavior of CMEs. It is comprised of three separate models: ForeCAT, ANTEATR, and FIDO. ForeCAT uses the PFSS background to determine the external magnetic forces on a CME; ANTEATR takes the ForeCAT CME and propagates it to the final satellite distance, and outputs the final CME speed (both propagation and expansion), size, and shape (and their profiles with distance) as well as the arrival time and internal thermal and magnetic properties of the CME. FIDO takes the evolved CME from ANTEATR with the position and orientation from ForeCAT and passes the CME over a synthetic spacecraft. The relative location of the spacecraft within the CME determines the in situ magnetic field vector and velocity. It also calculates the Kp index from these values. OSPREI includes tools for creating figures from the results, including histograms, contour plots, and ensemble correlation plots, and new figures can be created using the results object that contains all the simulation data in an easily accessible format.

OSPEX (Object Spectral Executive) is an object-oriented interface for X-ray spectral analysis of solar data. The next generation of SPEX (ascl:2007.017), it reads and displays input data, selects and subtracts background, selects time intervals of interest, selects a combination of photon flux model components to describe the data, and fits those components to the spectrum in each time interval selected. During the fitting process, the response matrix is used to convert the photon model to the model counts to compare with the input count data. The resulting time-ordered fit parameters are stored and can be displayed and analyzed with OSPEX. The entire OSPEX session can be saved in the form of a script and the fit results stored in the form of a FITS file. Part of the SolarSoft (ascl:1208.013) package, OSPEX works with any type of data structured in the form of time-ordered count spectra; RHESSI, Fermi, SOXS, MESSENGER, Yohkoh, SMM, and SMART data analysis have all been implemented in OSPEX.

OSIRIS Toolbox reduces data for the Keck OSIRIS instrument, an integral field spectrograph that works with the Keck Adaptive Optics System. It offers real-time reduction of raw frames into cubes for display and basic analysis. In this real-time mode, it takes about one minute for a preliminary data cube to appear in the “quicklook” display package. The reduction system also includes a growing set of final reduction steps including correction of telluric absorption and mosaicing of multiple cubes.

oscode solves oscillatory ordinary differential equations efficiently. It is designed to deal with equations of the form x¨(t)+2γ(t)x˙(t)+ω2(t)x(t)=0, where γ(t) and ω(t) can be given as explicit functions or sequence containers (Eigen::Vectors, arrays, std::vectors, lists) in C++ or as numpy.arrays in Python. oscode makes use of an analytic approximation of x(t) embedded in a stepping procedure to skip over long regions of oscillations, giving a reduction in computing time. The approximation is valid when the frequency changes slowly relative to the timescales of integration, it is therefore worth applying when this condition holds for at least some part of the integration range.

orvara (Orbits from Radial Velocity, Absolute, and/or Relative Astrometry) fits orbits of bright stars and their faint companions (exoplanets, brown dwarfs, white dwarfs, and low-mass stars). It can use any combination of radial velocity, relative astrometry, and absolute astrometry data and offers a variety of plots from the orbital fit, such as the radial velocity orbit over an extended time baseline, position angle between two companions, and a density plot of the predicted position at a chosen epoch. orvara can also check convergence of fitted parameters in the HDU1 extension, save the results from the fitted and inferred parameters from the HDU1 extension, and plot the results of a three-body or multiple-body fit.

ORSA is an interactive tool for scientific grade Celestial Mechanics computations. Asteroids, comets, artificial satellites, solar and extra-solar planetary systems can be accurately reproduced, simulated, and analyzed. The software uses JPL ephemeris files for accurate planets positions and has a Qt-based graphical user interface. It offers an advanced 2D plotting tool and 3D OpenGL viewer and the standalone numerical library liborsa and can import asteroids and comets from all the known databases (MPC, JPL, Lowell, AstDyS, and NEODyS). In addition, it has an integrated download tool to update databases.

ORIGIN performs blind detection of faint emitters in MUSE datacubes. The algorithm is tuned to detect faint spatial-spectral emission signatures while allowing for a stable false detection rate over the data cube, and providing in the same time an automated and reliable estimation of the purity. ORIGIN implements a nuisance removal part based on a continuum subtraction combining a Discrete Cosine Transform and an iterative Principal Component Analysis and a detection part based on the local maxima of Generalized Likelihood Ratio test statistics obtained for a set of spatial-spectral profiles of emission line emitters. In addition, it performs a purity estimation in which the proportion of true emission lines is estimated from the data itself: the distribution of the local maxima in the noise only configuration is estimated from that of the local minima.

ORIGAMI is a dynamical method of determining the morphology of particles in a cosmological simulation by checking for whether, and in how many dimensions, a particle has undergone shell-crossing. The code is written in C and makes use of the Delaunay tessellation calculation routines from the VOBOZ package (which relies on the Qhull package).

ORCS (Outils de Réduction de Cubes Spectraux) is an analysis engine for SITELLE spectral cubes. The software extracts integrated spectra, fits the sinc emission lines, and recalibrates data in wavelength, astrometry and flux. ORCS offers a choice between a Bayesian or a classical fitting algorithm
, and also provides automatic source detection and radial velocity correction.

OrbWeaver extracts orbits from halo catalogs, enabling large statistical studies of their orbital parameters. The code is run in two stages. For the first run, a configuration file is used to modify orbit host selection and the region around orbit host used for the superset of orbiting halos. Each orbit host has a orbit forest (containing halos that passed within the region of interest); the code generates a pre-processed catalog which contains a superset of orbiting halo for each identified orbit host. The second run uses the file list generated in the first stage for the creation of the orbit catalog, which is the final output.

ORBS merges, corrects, transforms and calibrates interferometric data cubes and produces a spectral cube of the observed region for analysis. It is a fully automatic data reduction software for use with SITELLE (installed at the Canada-France-Hawaii Telescope) and SpIOMM (a prototype attached to the Observatoire du Mont Mégantic); these imaging Fourier transform spectrometers obtain a hyperspectral data cube which samples a 12 arc-minutes field of view into 4 millions of visible spectra. ORBS is highly parallelized; its core classes (ORB) have been designed to be used in a suite of softwares for data analysis (ORCS and OACS), data simulation (ORUS) and data acquisition (IRIS).

orbitN generates accurate and reproducible long-term orbital solutions for near-Keplerian planetary systems with a dominant mass M0. The code focuses on hierarchical systems without close encounters but can be extended to include additional features. Among other features, the package includes M0's quadrupole moment, a lunar contribution, and post-Newtonian corrections (1PN) due to M0 (fast symplectic implementation). To reduce numerical roundoff errors, orbitN features Kahan compensated summation.

orbitize fits the orbits of directly-imaged objects by packaging the Orbits for the Impatient (OFTI) algorithm and a parallel-tempered Markov Chain Monte Carlo (MCMC) algorithm into a consistent API. It accepts observations in three measurement formats, which can be mixed in the same input file, generates orbits, and plots the computed orbital parameters. orbitize offers numerous ways to visualize the data, including histograms, corner plots, and orbit plots. Generated orbits can be saved in HDF5 format for future use and analysis.

orbit-estimation tests and evaluates the Stäckel approximation method for estimating orbit parameters in galactic potentials. It relies on the approximation of the Galactic potential as a Stäckel potential, in a prolate confocal coordinate system, under which the vertical and horizontal motions decouple. By solving the Hamilton Jacobi equations at the turning points of the horizontal and vertical motions, it is possible to determine the spatial boundary of the orbit, and hence calculate the desired orbit parameters.

OrbFit is a software system allowing one to compute the orbits of asteroids starting from the observations, to propagate these orbits, and to compute predictions on the future (and past) position on the celestial sphere. It is a tool to be used to find a well known asteroid, to recover a lost one, to attribute a small group of observations, to identify two orbits with each other, to study the future (and/or past) close approaches to Earth, thus to assess the risk of an impact, and more.

Orbfit determines positions and orbital elements, and associated uncertainties, of outer solar system planets. The orbit-fitting procedure is greatly streamlined compared with traditional methods because acceleration can be treated as a perturbation to the inertial motion of the body. Orbfit quickly and accurately calculates orbital elements and ephemerides and their associated uncertainties for targets ≳ 10 AU from the Sun and produces positional estimates and uncertainty ellipses even in the face of the substantial degeneracies of short-arc orbit fits; the sole a priori assumption is that the orbit should be bound or nearly so.

ORBE performs numerical integration of an arbitrary planetary system composed by a central star and up to 100 planets and minor bodies. ORBE calculates the orbital evolution of a system of bodies by means of the computation of the time evolution of their orbital elements. It is easy to use and is suitable for educational use by undergraduate students in the classroom as a first approach to orbital integrators.

ORBADV adopts a ZEUS-like scheme to solve magnetohydrodynamic equations of motion in a shearing sheet. The magnetic field is discretized on a staggered mesh, and magnetic field variables represent fluxes through zone faces. The code uses obital advection to ensure fast and accurate integration in a large shearing box.

ORAC-DR is a generic data reduction pipeline infrastructure; it includes specific data processing recipes for a number of instruments. It is used at the James Clerk Maxwell Telescope, United Kingdom Infrared Telescope, AAT, and LCOGT. This pipeline runs at the JCMT Science Archive hosted by CADC to generate near-publication quality data products; the code has been in use since 1998.

OPUS (Observatoire de Paris UWS System) provides interoperable access to analysis and simulation codes on local machines or work clusters. This job control system was developed using the micro-framework bottle.py, and executes jobs asynchronously to better manage jobs with a long execution duration. The software follows the proposed IVOA Provenance Data Model to capture and expose the provenance information of jobs and results.

Optool computes dust opacities and scattering matrices, for specific grain sizes or averaged over size distributions. It is derived from OpacityTool (ascl:2104.009) and implements the Distribution of Hollow Spheres (DHS) statistical method to approximate irregular and low porosity grains. Mie theory is available as a limiting case of DHS. It also implements the Tazaki Modified Mean Field Theory (MMF) to treat fractal and highly porous aggregates. The refractive index data for many astronomically relevant materials are compiled into the code, and external refractive index data can be used as well. A compact and intuitive command line interface makes it easy to construct complex particles on the fly. Available output formats are ASCII and FITS, including files directly readable by RADMC-3D (ascl:1202.015). A python interface to the FORTRAN program is included.

optBINS (optimal binning) determines the optimal number of bins in a uniform bin-width histogram by deriving the posterior probability for the number of bins in a piecewise-constant density model after assigning a multinomial likelihood and a non-informative prior. The maximum of the posterior probability occurs at a point where the prior probability and the the joint likelihood are balanced. The interplay between these opposing factors effectively implements Occam's razor by selecting the most simple model that best describes the data.

Optab, written in Fortran90, generates ideal-gas opacity tables. It computes opacity based on user-provided chemical equilibrium abundances, and outputs mean opacities as well as monochromatic opacities, thus providing opacity tables that are consistent with one's equation of state for radiation hydrodynamics simulations. For convenience, Optab also provides interfaces for FastChem (ascl:1804.025) or TEA (ascl:1505.031) for computing chemical abundances.

The Opik method gives the mean probability of collision of a small body with a given planet. It is a statistical value valid for an orbit with given (a,e,i) and undefined argument of perihelion. In some cases, the planet can eject the small body from the solar system; in these cases, the program estimates the mean time for the ejection. The Opik method does not take into account other perturbers than the planet considered, so it only provides an idea of the timescales involved.

OPERA (Open-source Pipeline for Espadons Reduction and Analysis) is an open-source collaborative software reduction pipeline for ESPaDOnS data. ESPaDOnS is a bench-mounted high-resolution echelle spectrograph and spectro-polarimeter designed to obtain a complete optical spectrum (from 370 to 1,050 nm) in a single exposure with a mode-dependent resolving power between 68,000 and 81,000. OPERA is fully automated, calibrates on two-dimensional images and reduces data to produce one-dimensional intensity and polarimetric spectra. Spectra are extracted using an optimal extraction algorithm. Though designed for CFHT ESPaDOnS data, the pipeline is extensible to other echelle spectrographs.

OPERA (Objective Prism Enhanced Reduction Algorithms) automatically analyzes astronomical images using the objective-prism (OP) technique to register thousands of low resolution spectra in large areas. It detects objects in an image, extracts one-dimensional spectra, and identifies the emission line feature. The main advantages of this method are: 1) to avoid subjectivity inherent to visual inspection used in past studies; and 2) the ability to obtain physical parameters without follow-up spectroscopy.

OpenSPH runs hydrodynamical and N-body simulations and was written for asteroid collisions and subsequent gravitational evolution. The code offers SPH and N-body solvers with several different equations of state and material rheologies. It is written in C++14 with a modular object-oriented design, focused on extensibility and maintainability, and it can be used either as a library or as a standalone graphical program that allows to set up the problem in a convenient graphical node editor. The graphical program further allows real-time visualization of the simulation, diagnostics and tools for analysis of the results.

OpenOrb (OOrb) contains tools for rigorously estimating the uncertainties resulting from the inverse problem of computing orbital elements using scarce astrometry. It uses the least-squares method and also contains both Monte-Carlo (MC) and Markov-Chain MC versions of the statistical ranging method. Ranging obtains sampled, non-Gaussian orbital-element probability-density functions and is optimized for cases where the amount of astrometry is scarce or spans a relatively short time interval.

OpenMHD is a Godunov-type finite-volume code for ideal/resistive magnetohydrodynamics (MHD). It is written in Fortran 90 and is parallelized by using MPI-3 and OpenMP. The code was originally developed for studying magnetic reconnection problems and has been made publicly available in the hope that others may find it useful.

OpacityTool computes dust opacities for disc modelling; it includes a number of robust facts obtained from observations and theory and goes beyond astronomical silicates. It provides output files with κext(λ),κabs(λ),κsca(λ) as a function of wavelength λ, and the 6 scattering matrix elements for randomly oriented particles, F11(λ,θ), F12(λ,θ), F22(λ,θ), F33(λ, θ), F34(λ, θ), F44(λ, θ) as functions of wavelength and scattering angle θ.

This code is superseded by optool (ascl:2104.010).

OoT (Out-of-Transit) calculates the light curves and radial velocity signals due to a planet orbiting a star. It explicitly models the effects of tides, orbital motion. relativistic beaming, and reflection of the stars light by the planet. The code can also be used to model secondary eclipses.

OneLoopBispectrum computes the one-loop bispectrum of galaxies in redshift space. It computes and simplifies the bispectrum kernels using Mathematica; this is cosmology-independent. The code also computes the full and flattened bispectrum templates, given the pre-computed integration kernels. OneLoopBispectrum uses Mathematica to read in and combine the bispectrum templates, and Python to interpolate and extract the one-loop bispectrum.

OMNICAL calibrates antennas in the redundant subset of the array. The code consists of two algorithms, a logarithmic method (logcal) and a linearized method (lincal). OMNICAL makes visibilities from physically redundant baselines agree with each other and also explicitly minimizes the variance within redundant visibilities.

Omega solves the photon equations of motion in the environment surrounding a black hole. This black hole can be either Schwarzschild (nonrotating) or Kerr (rotating) by choice of the user. The software offers numerous options, such as the geometrical setup of the accretion disk around the black hole (including no disk, band, slab, wedge, among others, the spin parameter of the central black hole, and the thickness of the accretion disk. Other options that can be set includ the azimuthal angle of the photon emission/reception, the poloidal angle of the photon emission/reception, and how far away or close to the system to look.

OMEGA (One-zone Model for the Evolution of GAlaxies) calculates the global chemical evolution trends of galaxies. From an input star formation history, it uses SYGMA to create as a function of time multiple simple stellar populations with different masses, ages, and initial compositions. OMEGA offers several prescriptions for modeling the star formation efficiency and the evolution of galactic inflows and outflows. OMEGA is part of the NuGrid (ascl:1610.015) chemical evolution package.

In the context of optical interferometry, only undersampled power spectrum and bispectrum data are accessible, creating an ill-posed inverse problem for image recovery. Recently, a tri-linear model was proposed for monochromatic imaging, leading to an alternated minimization problem; in that work, only a positivity constraint was considered, and the problem was solved by an approximated Gauss–Seidel method.

The Optical-Interferometry-Trilinear code improves the approach on three fundamental aspects. First, the estimated image is defined as a solution of a regularized minimization problem, promoting sparsity in a fixed dictionary using either an l1 or a (re)weighted-l1 regularization term. Second, the resultant non-convex minimization problem is solved using a block-coordinate forward–backward algorithm. This algorithm is able to deal both with smooth and non-smooth functions, and benefits from convergence guarantees even in a non-convex context. Finally, the model and algorithm are generalized to the hyperspectral case, promoting a joint sparsity prior through an l2,1 regularization term.

Odyssey is a GPU-based General Relativistic Radiative Transfer (GRRT) code for computing images and/or spectra in Kerr metric describing the spacetime around a rotating black hole. Odyssey is implemented in CUDA C/C++. For flexibility, the namespace structure in C++ is used for different tasks; the two default tasks presented in the source code are the redshift of a Keplerian disk and the image of a Keplerian rotating shell at 340GHz. Odyssey_Edu, an educational software package for visualizing the ray trajectories in the Kerr spacetime that uses Odyssey, is also available.

ODUSSEAS (Observing Dwarfs Using Stellar Spectroscopic Energy-Absorption Shapes) uses machine learning to derive the Teff and [Fe/H] of M dwarf stars by using their optical spectra obtained by different spectrographs with different resolutions. The software uses the measurement of the pseudo equivalent widths for more than 4000 stellar absorption lines and the machine learning Python package scikit-learn (https://scikit-learn.org/stable/) to predict the stellar parameters.

ODTBX (Orbit Determination Toolbox) provides orbit determination analysis, advanced mission simulation, and analysis for concept exploration, proposal, early design phase, and/or rapid design center environments. The core ODTBX functionality is realized through a set of estimation commands that incorporate Monte Carlo data simulation, linear covariance analysis, and measurement processing at a generic level; its functions and utilities are combined in a flexible architecture to allow modular development of navigation algorithms and simulations. ODTBX is written in Matlab and Java.

ODNet uses a convolutional neural network to examine frames of a given observation, using the flux of a targeted star along time, to detect occultations. This is particularly useful to reliably detect asteroid occultations for the Unistellar Network, which consists of 10,000 digital telescopes owned by citizen scientists that is regularly used to record asteroid occultations. ODNet is not costly in term of computing power, opening the possibility for embedding the code on the telescope directly. ODNet's models were developed and trained using TensorFlow version 2.4.

ODEPACK solves for the initial value problem for ordinary differential equation systems. It consists of nine solvers, a basic solver called LSODE and eight variants of it: LSODES, LSODA, LSODAR, LSODPK, LSODKR, LSODI, LSOIBT, and LSODIS. The collection is suitable for both stiff and nonstiff systems. It includes solvers for systems given in explicit form, dy/dt = f(t,y), and also solvers for systems given in linearly implicit form, A(t,y) dy/dt = g(t,y). The ODEPACK solvers are written in standard Fortran and there are separate double and single precision versions. Each solver consists of a main driver subroutine having the same name as the solver and some number of subordinate routines. For each solver, there is also a demonstration program, which solves one or two simple problems in a somewhat self-checking manner.

Octo-Tiger models mass transfer in binary systems using a Cartesian adaptive mesh refinement grid. It simulates the evolution of star systems based on a modified fast multipole method (FMM) on adaptive octrees. The code takes shock heating into account and uses the dual energy formalism with an ideal gas equation of state; it also conserves linear and angular momenta to machine precision. Octo-Tiger is implemented in C++ and is parallelized using the High Performance ParalleX (HPX) runtime system.

Octgrav is a very fast tree-code which runs on massively parallel Graphical Processing Units (GPU) with NVIDIA CUDA architecture. The algorithms are based on parallel-scan and sort methods. The tree-construction and calculation of multipole moments is carried out on the host CPU, while the force calculation which consists of tree walks and evaluation of interaction list is carried out on the GPU. In this way, a sustained performance of about 100GFLOP/s and data transfer rates of about 50GB/s is achieved. It takes about a second to compute forces on a million particles with an opening angle of $ heta approx 0.5$.

To test the performance and feasibility, we implemented the algorithms in CUDA in the form of a gravitational tree-code which completely runs on the GPU. The tree construction and traverse algorithms are portable to many-core devices which have support for CUDA or OpenCL programming languages. The gravitational tree-code outperforms tuned CPU code during the tree-construction and shows a performance improvement of more than a factor 20 overall, resulting in a processing rate of more than 2.8 million particles per second.

The code has a convenient user interface and is freely available for use.

The OctApps library provides various functions, written in Octave, for performing searches for the weak signatures of continuous gravitational waves from rapidly-rotating neutron stars amidst the instrumental noise of the LIGO and Virgo detectors.

OCFit fits and analyzes O-C diagrams using Genetic Algorithms and Markov chain Monte Carlo methods. The MC method is used to determine a very good estimation of errors of the parameters. Unlike some other fitting routines, OCFit does not need any initial values of fitted parameters. An intuitive graphic user interface is provided for ease of fitting, and nine common models of periodic O-C changes are included.

OCD (O'Connell Effect Detector) detects eclipsing binaries that demonstrate the O'Connell Effect. This time-domain signature extraction methodology uses a supporting supervised pattern detection algorithm. The methodology maps stellar variable observations (time-domain data) to a new representation known as Distribution Fields (DF), the properties of which enable efficient handling of issues such as irregular sampling and multiple values per time instance. Using this representation, the code applies a metric learning technique directly on the DF space capable of specifically identifying the stars of interest; the metric is tuned on a set of labeled eclipsing binary data from the Kepler survey, targeting particular systems exhibiting the O’Connell Effect. This code is useful for large-scale data volumes such as that expected from next generation telescopes such as LSST.

Obsplanning is a suite of tools to help plan astronomical observations from ground-based observatories, for traditional single-site as well as multi-station (VLBI) observing. Conveniently determine observability of objects in the sky from your observatory, and produce plots to help you prepare for your observations over the course of a session. Celestial source coordinates (including solar system objects) can be queried or created, and transformed. Calibrator or reference sources can be selected by proximity, and slew order can be optimized to save valuable telescope time. Plots and visualizations can be easily made to chart source elevation and transits, source proximity to the Sun and Moon, concurrent 'up time' of sources at multiple sites (for VLBI or tandem observations), 'dark time' at a telescope site for a given year, finder plots made from real images (with options to query online databases), and more.

Simple program for planning and managing astronomical observations as observational diary or logs.

Obit is a group of software packages for handling radio astronomy data, especially interferometric and single dish OTF imaging. Obit is primarily an environment in which new data processing algorithms can be developed and tested but which can also be used for production processing of a certain range of scientific problems. The package supports both prepackaged, compiled tasks and a python interface to the major class functionality to allow rapid prototyping using python scripts; it allows access to multiple disk--resident data formats, in particular access to either AIPS disk data or FITS files. Obit applications are interoperable with Classic AIPS and the ObitTalk python interface gives access to AIPS tasks as well as Obit libraries and tasks.

OBERON (OBliquity and Energy balance Run on N-body systems) models the climate of Earthlike planets under the effects of an arbitrary number and arrangement of other bodies, such as stars, planets and moons. The code, written in C++, simultaneously computes N body motions using a 4th order Hermite integrator, simulates climates using a 1D latitudinal energy balance model, and evolves the orbital spin of bodies using the equations of Laskar (1986a,b).

O₂scl is an object-oriented library for scientific computing in C++ useful for solving, minimizing, differentiating, integrating, interpolating, optimizing, approximating, analyzing, fitting, and more. Many classes operate on generic function and vector types; it includes classes based on GSL and CERNLIB. O₂scl also contains code for computing the basic thermodynamic integrals for fermions and bosons, for generating almost all of the most common equations of state of nuclear and neutron star matter, and for solving the TOV equations. O₂scl can be used on Linux, Mac and Windows (Cygwin) platforms and has extensive documentation.

The O'TRAIN package identifies transients in astronomical images based on a Convolutional Neural Network (CNN). It works on images from different telescopes and, through the use of Docker, can be deployed on different operating systems. O'TRAIN uses image cutouts containing real and false transients provided by the user to train a CNN algorithm implemented with Keras. Built-in diagnostics help to characterize the accuracy of the training, and a trained model is used to classify any new cutouts.

Nyx code solves equations of compressible hydrodynamics on an adaptive grid hierarchy coupled with an N-body treatment of dark matter. The gas dynamics in Nyx use a finite volume methodology on an adaptive set of 3-D Eulerian grids; dark matter is represented as discrete particles moving under the influence of gravity. Particles are evolved via a particle-mesh method, using Cloud-in-Cell deposition/interpolation scheme. Both baryonic and dark matter contribute to the gravitational field. In addition, Nyx includes physics for accurately modeling the intergalactic medium; in optically thin limits and assuming ionization equilibrium, the code calculates heating and cooling processes of the primordial-composition gas in an ionizing ultraviolet background radiation field.

NWelch uses Welch's method to estimate the power spectra, complex cross-spectrum, magnitude-squared coherence, and phase spectrum of bivariate time series with nonuniform observing cadence. For univariate time series, users can apply the Welch's power spectrum estimator or compute a nonuniform fast Fourier transform-based periodogram. Options include tapering in the time domain and computing bootstrap false alarm levels. Users may choose standard 50%-overlapping Welch's segments or apply a custom-made segmentation scheme. NWelch was designed for Doppler planet searches but may be applied to any type of time series.

nway is a source cross-matching tool for arbitrarily many astronomical catalogs. It features Bayesian match probabilities based on astronomical sky coordinates (RA, DEC), works with arbitrarily many catalogs, and can handle varying errors. nway can also incorporate additional prior information, such as the magnitude or color distributions of the sources to match, and works accurately and fast in small areas and all-sky catalogs.

nuSpaceSim simulates upward-going extensive air showers caused by neutrino interactions with the atmosphere. It is an end-to-end, neutrino flux to space-based signal detection, modeling tool for the design of sub-orbital and space-based neutrino detection experiments. This comprehensive suite of modeling packages accepts an experimental design input and then models the experiment's sensitivity to both the diffuse, cosmogenic neutrino flux as well as astrophysical neutrino transient events, such as that postulated from binary neutron star (BNS) mergers. nuSpaceSim calculates the tau neutrino acceptance for the Optical Cherenkov technique; tau propagation is interpolated using included data tables from nupyprop (ascl:2306.044). The simulation is parameterized by an input XML configuration file, with settings for detector characteristics and global parameters; nuSpaceSim also provides a python API for programmatic access.

NuRadioMC simulates ultra-high energy neutrino detectors that rely on the radio detection method, which exploits the radio emission generated in the electromagnetic component of a particle shower following a neutrino interaction. The code simulates the neutrino interaction in a medium, subsequent Askaryan radio emission, propagation of the radio signal to the detector and the detector response. NuRadioMC is a Monte Carlo framework that combines flexibility in detector design with user-friendliness. It includes an event generator, improved modeling of the radio emission, a revisited approach to signal propagation, and increased flexibility and precision in the detector simulation.

nuPyProp simulates tau neutrino and muon neutrino interactions in the Earth and predicts the spectrum of the τ-leptons and muons that emerge. The code produces tables of charged lepton exit probabilities and energies that can be used directly or as inputs to nuSpaceSim (ascl:2306.043), which is designed to simulate optical and radio signals from extensive air showers induced by the emerging charged leptons.

The NuGrid Python Chemical Evolution Environment (NuPyCEE) simulates the chemical enrichment and stellar feedback of stellar populations. It contains three modules. The Stellar Yields for Galactic Modeling Applications module (SYGMA) models the enrichment and feedback of simple stellar populations which can be included in hydrodynamic simulations and semi-analytic models of galaxies. It is the basic building block of the One-zone Model for the Evolution of GAlaxies (OMEGA, ascl:1806.018) module which models the chemical evolution of galaxies such as the Milky Way and its dwarf satellites. The STELLAB (STELLar ABundances) module provides a library of observed stellar abundances useful for comparing predictions of SYGMA and OMEGA.

NumCosmo is a free software C library whose main purposes are to test cosmological models using observational data and to provide a set of tools to perform cosmological calculations. The software implements three different probes: cosmic microwave background (CMB), supernovae type Ia (SNeIa) and large scale structure (LSS) information, such as baryonic acoustic oscillations (BAO) and galaxy cluster abundance. The code supports a joint analysis of these data and the parameter space can include cosmological and phenomenological parameters. NumCosmo matter power spectrum and CMB codes were written independent of other implementations such as CMBFAST (ascl:9909.004), CAMB (ascl:1102.026), etc.

The library structure simplifies the inclusion of non-standard cosmological models. Besides the functions related to cosmological quantities, this library also implements mathematical and statistical tools. The former were developed to enable the inclusion of other probes and/or theoretical models and to optimize the codes. The statistical framework comprises algorithms which define likelihood functions, minimization, Monte Carlo, Fisher Matrix and profile likelihood methods.

Nulike is software for including full event-level information in likelihood calculations for neutrino telescope searches for dark matter annihilation. It includes both angular and spectral information about neutrino events as well as their total number, and can be used for single models without reference to the rest of a parameter space.

nudec_BSM uses a simplified approach to solve for the neutrino decoupling, allowing one to capture the time dependence of the process while accounting for all possible interactions that can alter it.

NuCraft calculates oscillation probabilities for atmospheric neutrinos, taking into account matter effects and the Earth's atmosphere, and supports an arbitrary number of sterile neutrino flavors with easily configurable continuous Earth models. Continuous modeling of the Earth instead of the often-used approximation of four layers with constant density and consideration of the smearing of baseline lengths due to the variable neutrino production heights in Earth's atmosphere each lead to deviations of 10% or more for conventional neutrinos between 1 and 10 GeV.

NSCool is a 1D (i.e., spherically symmetric) neutron star cooling code written in Fortran 77. The package also contains a series of EOSs (equation of state) to build stars, a series of pre-built stars, and a TOV (Tolman- Oppenheimer-Volkoff) integrator to build stars from an EOS. It can also handle “strange stars” that have a huge density discontinuity between the quark matter and the covering thin baryonic crust. NSCool solves the heat transport and energy balance equations in whole GR, resulting in a time sequence of temperature profiles (and, in particular, a Teff - age curve). Several heating processes are included, and more can easily be incorporated. In particular it can evolve a star undergoing accretion with the resulting deep crustal heating, under a steady or time-variable accretion rate. NSCool is robust, very fast, and highly modular, making it easy to add new subroutines for new processes.

The NOIRLab Source Catalog Generator generates the NOIRLab Source Catalog (NSC), a catalog of all publicly available imagining data in the NOIRLab Astro Data Archive. The second data release (DR2) of the archive contains over 3.9 billion unique objects, 68 billion individual source measurements, covers 35,000 square degrees of the sky, has depths of 23rd magnitude in most broadband filters with 1-2% photometric precision, and astrometric accuracy of 7 mas. NSCG is written in Python and IDL. Three main steps generate the NSC: (1) Source Extractor (ascl:1010.064) is used to detect and measure sources in individual images; (2) astrometrics are calibrated with Gaia DR2 and photometric calibration using large public photometric catalogs such as Pan-STARRS1 and ATLAS-Refcat2; and, (3) measurements are clustered into unique objects, averaging photometric and morphological properties, and calculating proper motions and photometric variability indices.

NRPy+ (Python-based Code generation for Numerical Relativity and Beyond) generates highly-optimized C code from complex tensorial expressions input in Einstein-like notation. NRPy+ uses SymPy as its computer algebra system backend. It is part of the NRPy+/SENR numerical relativity code package for solving Einstein's equations of general relativity to model compact objects at about 1/100 the cost in memory of more traditional, AMR-based numerical relativity codes, thus allowing desktop computers to be used for gravitational wave astrophysics.

The NRDD_constraints tool provides simple interpolating functions written in Python that return the most constraining limit on the dark matter-nucleon scattering cross section for a list of non-relativistic effective operators. The package contains four files: the main code, NRDD_constraints.py; a simple driver, NRDD_constraints-example.py; and two data files, NRDD_data1.npy and NRDD_data2.npy

NR-code applies nonlinear reconstruction to the dark matter density field in redshift space and solves for the nonlinear mapping from the initial Lagrangian positions to the final redshift space positions; this reverses the large-scale bulk flows and improves the precision measurement of the baryon acoustic oscillations (BAO) scale.

NPTFit is a specialized Python/Cython package that implements Non-Poissonian Template Fitting (NPTF), originally developed for characterizing populations of unresolved point sources. It offers fast evaluation of likelihoods for NPTF analyses and has an easy-to-use interface for performing non-Poissonian (as well as standard Poissonian) template fits using MultiNest (ascl:1109.006) or other inference tools. It allows inclusion of an arbitrary number of point source templates, with an arbitrary number of degrees of freedom in the modeled flux distribution, and has modules for analyzing and plotting the results of an NPTF.

nProFit analyzes surface brightness profiles. It obtains the best-fit structural, scale, and shape parameters of star clusters in Hubble Space Telescope images of nearby galaxies. The code fits dynamical models and can derive physically-relevant parameters. Among these are central volume and luminosity densities, total masses and luminosities, central velocity dispersions, core radius, half-light radius, tidal radius, and binding energy.

NOVAS is an integrated package of subroutines and functions for computing various commonly needed quantities in positional astronomy. The package can provide, in one or two subroutine or function calls, the instantaneous coordinates of any star or planet in a variety of coordinate systems. At a lower level, NOVAS also supplies astrometric utility transformations, such as those for precession, nutation, aberration, parallax, and the gravitational deflection of light. The computations are accurate to better than one milliarcsecond. The NOVAS package is an easy-to-use facility that can be incorporated into data reduction programs, telescope control systems, and simulations. The U.S. parts of The Astronomical Almanac are prepared using NOVAS. Three editions of NOVAS are available: Fortran, C, and Python.

NonnegMFPy solves nonnegative matrix factorization (NMF) given a dataset with heteroscedastic uncertainties and missing data with a vectorized multiplicative update rule; this can be used create a mask and iterate the process to exclude certain new data by updating the mask. The code can work on multi-dimensional data, such as images, if the data are first flattened to 1D.

We have constructed a grid of non-LTE disk models for a wide range of black hole mass and mass accretion rate, for several values of viscosity parameter alpha, and for two extreme values of the black hole spin: the maximum-rotation Kerr black hole, and the Schwarzschild (non-rotating) black hole. Our procedure calculates self-consistently the vertical structure of all disk annuli together with the radiation field, without any approximations imposed on the optical thickness of the disk, and without any ad hoc approximations to the behavior of the radiation intensity. The total spectrum of a disk is computed by summing the spectra of the individual annuli, taking into account the general relativistic transfer function. The grid covers nine values of the black hole mass between M = 1/8 and 32 billion solar masses with a two-fold increase of mass for each subsequent value; and eleven values of the mass accretion rate, each a power of 2 times 1 solar mass/year. The highest value of the accretion rate corresponds to 0.3 Eddington. We show the vertical structure of individual annuli within the set of accretion disk models, along with their local emergent flux, and discuss the internal physical self-consistency of the models. We then present the full disk-integrated spectra, and discuss a number of observationally interesting properties of the models, such as optical/ultraviolet colors, the behavior of the hydrogen Lyman limit region, polarization, and number of ionizing photons. Our calculations are far from definitive in terms of the input physics, but generally we find that our models exhibit rather red optical/UV colors. Flux discontinuities in the region of the hydrogen Lyman limit are only present in cool, low luminosity models, while hotter models exhibit blueshifted changes in spectral slope.

Non-Gaussian Realisations provides code based on a spectral distortion/quantile transformation that generates a realization of a field on a cubic grid that has a specified probability distribution function and a specified power spectrum.

NOD3 processes and analyzes maps from single-dish observations affected by scanning effects from clouds, receiver instabilities, or radio-frequency interference. Its “basket-weaving” tool combines orthogonally scanned maps into a final map that is almost free of scanning effects. A restoration tool for dual-beam observations reduces the noise by a factor of about two compared to the NOD2 version. Combining single-dish with interferometer data in the map plane ensures the full recovery of the total flux density.

NNKCDE is a simple and easily interpretable Conditional Density Estimation (CDE) method. It computes a kernel density estimate of y using the k nearest neighbors of the evaluation point x. The model has only two tuning parameters: the number of nearest neighbors k and the bandwidth h of the smoothing kernel in y-space. Both tuning parameters are chosen in a principled way by minimizing the CDE loss on validation data.

NMMA probes nuclear physics and cosmology with multimessenger analysis. This fully featured, Bayesian multi-messenger pipeline targets joint analyses of gravitational-wave and electromagnetic data (focusing on the optical). Using bilby (ascl:1901.011) as the back-end, the software uses a variety of samplers to sampling these data sets. NMMA uses chiral effective field theory based neutron star equation of states when performing inference, and is also capable of estimating the Hubble Constant.

The library NLopt performs nonlinear local and global optimization for functions with and without gradient information. It provides a simple, unified interface and wraps many algorithms for global and local, constrained or unconstrained, optimization, and provides interfaces for many other languages, including C++, Fortran, Python, Matlab or GNU Octave, OCaml, GNU Guile, GNU R, Lua, Rust, and Julia.

The NIRVANA code is capable of the simulation of multi-scale self-gravitational magnetohydrodynamics problems in three space dimensions employing the technique of adaptive mesh refinement. The building blocks of NIRVANA are (i) a fully conservative, divergence-free Godunov-type central scheme for the solution of the equations of magnetohydrodynamics; (ii) a block-structured mesh refinement algorithm which automatically adds and removes elementary grid blocks whenever necessary to achieve adequate resolution and; (iii) an adaptive mesh Poisson solver based on multigrid philosophy which incorporates the so-called elliptic matching condition to keep the gradient of the gravitational potential continous at fine/coarse mesh interfaces.

NIRDust uses K-band (2.2 micrometers) spectra to measure the temperature of the dust heated by an Active Galactic Nuclei (AGN) accretion disk. The package provides several functionalities to pre-process spectra and fit the hot dust component of a AGN K-band spectrum with a blackbody function. NIRDust needs a minimum of two spectra to run: a target spectrum, where the dust temperature will be estimated, and a reference spectrum, where the emission is considered to be purely stellar. The reference spectrum will be used by NIRDust to model the stellar emission from the target spectrum.

nimbus is a hierarchical Bayesian framework to infer the intrinsic luminosity parameters of kilonovae (KNe) associated with gravitational-wave (GW) events, based purely on non-detections. This framework makes use of GW 3-D distance information and electromagnetic upper limits from a given survey for multiple events, and self-consistently accounts for finite sky-coverage and probability of astrophysical origin.

NIMBLE (Non-parametrIc jeans Modeling with B-spLinEs) inferrs the cumulative mass distribution of a gravitating system from full 6D phase space coordinates of its tracers via spherical Jeans modeling. It models the Milky Way's dark matter halo using Gaia and Dark Energy Spectroscopic Instrument Milky Way Survey (DESI MWS) data. NIMBLE includes a basic inverse modeling Jeans routine that assumes perfect and complete data is available and a more complex forward modeling Jeans routine that deconvolves observational effects (uncertainties and limited survey volume) characteristic of Gaia and the DESI-MWS. It also includes tools for generating simple equilibrium model galaxies using Agama (ascl:1805.008) and imposing mock Gaia+DESI errors on 6D phase space input data.

Nii implements an automatic parallel tempering Markov chain Monte Carlo (APT-MCMC) framework for sampling multidimensional posterior distributions and provides an observation simulation platform for the differential astrometric measurement of exoplanets. Although this code specifically focuses on the orbital parameter retrieval problem of differential astrometry, Nii can be applied to other scientific problems with different posterior distributions and offers many control parameters in the APT part to facilitate the adjustment of the MCMC sampling strategy; these include the number of parallel chains, the β values of different chains, the dynamic range of the sampling step sizes, and frequency of adjusting the step sizes.

Nigraha identifies and evaluates planet candidates from TESS light curves. Using a combination of high signal to noise ratio (SNR) shallow transits, supervised machine learning, and detailed vetting, the neural network-based pipeline identifies planet candidates missed by prior searches. The pipeline runs in four stages. It first performs period finding using the Transit Least Squares (TLS) package and runs sector by sector to build a per-sector catalog. It then transforms the flux values in .fits lightcurve files to global/local views and write out the output in .tfRecords files, builds a model on training data, and saves a checkpoint. Finally, it loads a previously saved model to generate predictions for new sectors. Nigraha provides helper scripts to generate candidates in new sectors, thus allowing others to perform their own analyses.

NIGO (Numerical Integrator of Galactic Orbits) predicts the orbital evolution of test particles moving within a fully-analytical gravitational potential generated by a multi-component galaxy. The code can simulate the orbits of stars in elliptical and disc galaxies, including non-axisymmetric components represented by a spiral pattern and/or rotating bar(s).

Nightfall is an astronomy application for fun, education, and science. It can produce animated views of eclipsing binary stars, calculate synthetic lightcurves and radial velocity curves, and eventually determine the best-fit model for a given set of observational data of an eclipsing binary star system.

Nightfall comes with a user guide and a set of observational data for several eclipsing binary star systems.

NIFTy (Numerical Information Field Theory) facilitates the construction of Bayesian field reconstruction algorithms for fields being defined over multidimensional domains. A NIFTy algorithm can be developed for 1D field inference and then be used in 2D or 3D, on the sphere, or on product spaces thereof. NIFTy5 is a complete redesign of the previous framework (ascl:1302.013), and requires only the specification of a probabilistic generative model for all involved fields and the data in order to be able to recover the former from the latter. This is achieved via Metric Gaussian Variational Inference, which also provides posterior samples for all unknown quantities jointly.

NIFTY (Numerical Information Field TheorY) is a versatile library enables the development of signal inference algorithms that operate regardless of the underlying spatial grid and its resolution. Its object-oriented framework is written in Python, although it accesses libraries written in Cython, C++, and C for efficiency. NIFTY offers a toolkit that abstracts discretized representations of continuous spaces, fields in these spaces, and operators acting on fields into classes. Thereby, the correct normalization of operations on fields is taken care of automatically. This allows for an abstract formulation and programming of inference algorithms, including those derived within information field theory. Thus, NIFTY permits rapid prototyping of algorithms in 1D and then the application of the developed code in higher-dimensional settings of real world problems. NIFTY operates on point sets, n-dimensional regular grids, spherical spaces, their harmonic counterparts, and product spaces constructed as combinations of those.

NICOLE, written in Fortran 90, seeks the model atmosphere that provides the best fit to the Stokes profiles (in a least-squares sense) of an arbitrary number of simultaneously-observed spectral lines from solar/stellar atmospheres. The inversion core used for the development of NICOLE is the LORIEN engine (the Lovely Reusable Inversion ENgine), which combines the SVD technique with the Levenberg-Marquardt minimization method to solve the inverse problem.

NICIL (Non-Ideal magnetohydrodynamics Coefficients and Ionisation Library) calculates the ionization values and the coefficients of the non-ideal magnetohydrodynamics terms of Ohmic resistivity, the Hall effect, and ambipolar diffusion. Written as a standalone Fortran90 module that can be implemented in existing codes, NICIL is fully parameterizable, allowing the user to choose which processes to include and decide the values of the free parameters. The module includes both cosmic ray and thermal ionization; the former includes two ion species and three species of dust grains (positively charged, negatively charged and neutral), and the latter includes five elements which can be doubly ionized.

nicaea calculates cosmology and weak-lensing quantities and functions from theoretical models of the large-scale structure. Written in C, it can compute the Hubble parameter, distances, and geometry for background cosmology, and linear perturbations, including growth factor, transfer function, cluster mass function, and linear 3D power spectra. It also calculates fitting formulae for non-linear power spectra, emulators, and halo model for Non-linear evolution, and the HOD model for galaxy clustering. In addition, nicaea can compute quantities for cosmic shear such as the convergence power spectrum, second-order correlation functions and derived second-order quantities, and third-order aperture mass moment; it can also calculate CMB anisotropies via CAMB (ascl:1102.026).

NGMIX implements Gaussian mixture models for 2D images. Both the PSF profile and the galaxy are modeled using mixtures of Gaussians. Convolutions are thus performed analytically, resulting in fast model generation as compared to methods that perform the convolution in Fourier space. For the galaxy model, NGMIX supports exponential disks and de Vaucouleurs and Sérsic profiles; these are implemented approximately as a sum of Gaussians using the fits from Hogg & Lang (2013). Additionally, any number of Gaussians can be fit, either completely free or constrained to be cocentric and co-elliptical.

Available in R and Python, the simple analytic scheme NFWdist performs highly efficient and exact sampling of the Navarro, Frenk & White (NFW) profile as a true probability distribution function, with the only variable being the concentration.

nFITSview is a simple, user-friendly and open-source FITS image viewer available for Linux and Windows. One of the main concepts of nFITSview is to provide an intuitive user interface which may be helpful both for scientists and for amateur astronomers. nFITSview has different color mapping and manipulation schemes, supports different formats of FITS data files as well as exporting them to different popular image formats. It also supports command-line exporting (with some restrictions) of FITS files to other image formats.
The application is written in C++/Qt for achieving better performance, and with every next version the performance aspect is taken into account.
nFITSview uses its own libnfits library (can be used separately as well) for parsing the FITS files.

nfield uses a stochastic formalism to compute the IR correlation functions of quantum fields during cosmic inflation in n-field dimensions. This is a necessary 1-loop resummation of the correlation functions to render them finite. The code supports the implementation of n-numbers of coupled test fields (energetically sub-dominant) as well as non-test fields.

Nextflow enables scalable and reproducible scientific workflows using software containers. It allows the adaptation of pipelines written in the most common scripting languages. Its fluent DSL simplifies the implementation and the deployment of complex parallel and reactive workflows on clouds and clusters. Nextflow supports deploying workflows on a variety of execution platforms including local, HPC schedulers, AWS Batch, Google Cloud Life Sciences, and Kubernetes. Additionally, it provides support for workflow dependencies through built-in support for, for example, Conda, Spack, Docker, Podman, Singularity, and Modules.

NeutrinoFog calculates the neutrino floor based on the derivative of a hypothetical experimental discovery limit as a function of exposure, and leads to a neutrino floor that is only influenced by the systematic uncertainties on the neutrino flux normalizations.

The first step in a science project is the acquisition and understanding of the relevant data. The tools range from simple data transfer methods to more complex browser-emulating scripts. When integrated with a defined sample or catalog, these scripts provide seamless techniques to retrieve and store data of varying types. These tools can be used to leapfrog from website to website to acquire multi-wavelength datasets. This project demonstrates the capability to use multiple data websites, in conjunction, to perform the type of calculations once reserved for on-site datasets.

We have developed a method to efficiently simulate the dynamics of the magnetic flux in the solar network. We call this method Network Flux Transport (NFT). Implemented using a Spherical Centroidal Voronoi Tessellation (SCVT) based network model, magnetic flux is advected by photospheric plasma velocity fields according to the geometry of the SCVT model. We test NFT by simulating the magnetism of the Solar poles. The poles of the sun above 55 deg latitude are free from flux emergence from active regions or ephemeral regions. As such, they are ideal targets for a simplified simulation that relies on the strengths of the NFT model. This simulation method reproduces the magnetic and spatial distributions for the solar poles over two full solar cycles.

nestle is a pure Python implementation of nested sampling algorithms for evaluating Bayesian evidence. Nested sampling integrates posterior probability in order to compare models in Bayesian statistics. It is similar to Markov Chain Monte Carlo (MCMC) in that it generates samples that can be used to estimate the posterior probability distribution. Unlike MCMC, the nature of the sampling also allows one to calculate the integral of the distribution. It is also a pretty good method for robustly finding global maxima.

Nestcheck analyzes nested sampling runs and estimates numerical uncertainties on calculations using them. The package can load results from a number of nested sampling software packages, including MultiNest (ascl:1109.006), PolyChord (ascl:1502.011), dynesty (ascl:1809.013) and perfectns (ascl:1809.005), and offers the flexibility to add input functions for other nested sampling software packages. Nestcheck utilities include error analysis, diagnostic tests, and plots for nested sampling calculations.

NEST (Noble Element Simulation Technique) offers comprehensive, accurate, and precise simulation of the excitation, ionization, and corresponding scintillation and electroluminescence processes in liquid noble elements, useful for direct dark matter detectors, double beta decay searches, PET scans, and general radiation detection technology. Written in C++, NEST is an add-on module for the Geant4 simulation package that incorporates more detailed physics than is currently available into the simulation of scintillation. NEST is of particular use for low-energy nuclear recoils. All available liquid xenon data on nuclear recoils and electron recoils to date have been taken into consideration in arriving at the current models. NEST also handles the magnitude of the light and charge yields of nuclear recoils, including their electric field dependence, thereby shedding light on the possibility of detection or exclusion of a low-mass dark matter WIMP by liquid xenon detectors.

The NEOexchange web portal and Target and Observation Manager ingests solar system objects, including Near-Earth Object (NEO) candidates from the Minor Planet Center, schedules observations on the Las Cumbres Observatory global telescope network and reduces, displays, and analyzes the resulting data. NEOexchange produces calibrated photometry from the imaging data and uses Source Extractor (ascl:1010.064) and SCAMP (ascl:1010.063) to perform object detection and astrometric fitting and calviacat (ascl:2207.015) to perform photometric calibration against photometric catalogs. It also has the ability to perform image registration and subtraction using SWARP (ascl:1010.068) and HOTPANTS (ascl:1504.004) and image stacking, alignment, and faint feature detection using gnuastro (ascl:1801.009).

Nemo detects millimeter-wave Sunyaev-Zel'dovich galaxy clusters and compact sources. Originally developed for the Atacama Cosmology Telescope project, the code is capable of analyzing the next generation of deep, wide multifrequency millimeter-wave maps that will be produced by experiments such as the Simons Observatory. Nemo provides several modules for analyzing ACT/SO data in addition to the command-line programs provided in the package.

NEMO is an extendible Stellar Dynamics Toolbox, following an Open-Source Software model. It has various programs to create, integrate, analyze and visualize N-body and SPH like systems, following the pipe and filter architecture. In addition there are various tools to operate on images, tables and orbits, including FITS files to export/import to/from other astronomical data reduction packages. A large growing fraction of NEMO has been contributed by a growing list of authors. The source code consist of a little over 4000 files and a little under 1,000,000 lines of code and documentation, mostly C, and some C++ and Fortran. NEMO development started in 1986 in Princeton (USA) by Barnes, Hut and Teuben. See also ZENO (ascl:1102.027) for the version that Barnes maintains.

nemiss calculates neutrino emission from an astrophysical jet. nemiss works as part of the PLUTO-nemiss-rlos pipeline. PLUTO (ascl:1010.045) produces a hydrodynamical jet. Then, nemiss calculates beamed neutrino emission at each eligible cell along a given direction in space. Finally, rlos (ascl:1811.009) produces a synthetic neutrino image of the jet along the given direction, taking into consideration the finite nature of the speed of light.

NEMESIS (Non-linear optimal Estimator for MultivariatE spectral analySIS) is the general purpose correlated-k/LBL retrieval code developed from the RADTRAN project (ascl:2210.008). Originally based on the correlated-k approximation, NEMESIS also works in line-by-line (LBL) mode. It has been designed to be generally applicable to any planet and with any observing mode and so is suitable for both solar-system studies and also exoplanetary studies.

NeedATool (Needlet Analysis Tool) performs data analysis based on needlets, a wavelet rendition powerful for the analysis of fields defined on a sphere. Needlets have been applied successfully to the treatment of astrophysical and cosmological observations, particularly to the analysis of cosmic microwave background (CMB) data. Wavelets have emerged as a useful tool for CMB data analysis, as they combine most of the advantages of both pixel space, where it is easier to deal with partial sky coverage and experimental noise, and the harmonic domain, in which beam treatment and comparison with theoretical predictions are more effective due in large part to their sharp localization.

NEBULAR synthesizes the spectrum of a mixed hydrogen helium gas in collisional ionization equilibrium. It is not a spectral fitting code, but it can be used to resample a model spectrum onto the wavelength grid of a real observation. It supports a wide range of temperatures and densities. NEBULAR includes free-free, free-bound, two-photon and line emission from HI, HeI and HeII. The code will either return the composite model spectrum, or, if desired, the unrescaled atomic emission coefficients. It is written in C++ and depends on the GNU Scientific Library (GSL).

NEBULA performs the radiative transfer of the 3He+ hyperfine transition, radio recombination lines (RRLs), and free-free continuum emission through a model nebula. The model nebula is composed of only H and He within a three-dimension Cartesian grid with arbitrary density, temperature, and ionization structure. The 3He+ line is assumed to be in local thermodynamic equilibrium (LTE), but non-LTE effects and pressure broadening from electron impacts can be included for the RRLs. All spectra are broadened by thermal and microturbulent motions.

NEAT is a fully automated code which carries out a complete analysis of lists of emission lines to estimate the amount of interstellar extinction, calculate representative temperatures and densities, compute ionic abundances from both collisionally excited lines and recombination lines, and finally to estimate total elemental abundances using an ionization correction scheme. NEAT uses a Monte Carlo technique to robustly propagate uncertainties from line flux measurements through to the derived abundances.

NE2001p is a fully Python implementation of the NE2001 Galactic electron density model. NE2001p forward models the dispersion and scattering of compact radio sources, including pulsars, fast radio bursts, AGNs, and masers, and the model predicts the distances of radio sources that lack independent distance measures.

This paper presents an overview and introduction to Smoothed Particle Hydrodynamics and Magnetohydrodynamics in theory and in practice. Firstly, we give a basic grounding in the fundamentals of SPH, showing how the equations of motion and energy can be self-consistently derived from the density estimate. We then show how to interpret these equations using the basic SPH interpolation formulae and highlight the subtle difference in approach between SPH and other particle methods. In doing so, we also critique several `urban myths' regarding SPH, in particular the idea that one can simply increase the `neighbour number' more slowly than the total number of particles in order to obtain convergence. We also discuss the origin of numerical instabilities such as the pairing and tensile instabilities. Finally, we give practical advice on how to resolve three of the main issues with SPMHD: removing the tensile instability, formulating dissipative terms for MHD shocks and enforcing the divergence constraint on the particles, and we give the current status of developments in this area. Accompanying the paper is the first public release of the NDSPMHD SPH code, a 1, 2 and 3 dimensional code designed as a testbed for SPH/SPMHD algorithms that can be used to test many of the ideas and used to run all of the numerical examples contained in the paper.

The Extensible N-Dimensional Data Format (NDF) stores bulk data in the form of N-dimensional arrays of numbers. It is typically used for storing spectra, images and similar datasets with higher dimensionality. The NDF format is based on the Hierarchical Data System (HDS) and is extensible; not only does it provide a comprehensive set of standard ancillary items to describe the data, it can also be extended indefinitely to handle additional user-defined information of any type. The NDF library is used to read and write files in the NDF format. It is distributed with the Starlink software (ascl:1110.012).

Comparing galaxies across redshifts via cumulative number densities is a popular way to estimate the evolution of specific galaxy populations. nd-redshift uses abundance matching in the ΛCDM paradigm to estimate the median change in number density with redshift. It also provides estimates for the 1σ range of number densities corresponding to galaxy progenitors and descendants.

NBSymple is a numerical code which numerically integrates the equation of motions of N 'particles' interacting via Newtonian gravitation and move in an external galactic smooth field. The force evaluation on every particle is done by mean of direct summation of the contribution of all the other system's particle, avoiding truncation error. The time integration is done with second-order and sixth-order symplectic schemes. NBSymple has been parallelized twice, by mean of the Computer Unified Device Architecture to make the all-pair force evaluation as fast as possible on high-performance Graphic Processing Units NVIDIA TESLA C 1060, while the O(N) computations are distributed on various CPUs by mean of OpenMP Application Program. The code works both in single precision floating point arithmetics or in double precision. The use of single precision allows the use at best of the GPU performances but, of course, limits the precision of simulation in some critical situations. We find a good compromise in using a software reconstruction of double precision for those variables that are most critical for the overall precision of the code.

nbodykit provides algorithms for analyzing cosmological datasets from N-body simulations and large-scale structure surveys, and takes advantage of the abundance and availability of large-scale computing resources. The package provides a unified treatment of simulation and observational datasets by insulating algorithms from data containers, and reduces wall-clock time by scaling to thousands of cores. All algorithms are parallel and run with Message Passing Interface (MPI); the code is designed to be deployed on large super-computing facilities. nbodykit offers an interactive user interface that performs as well in a Jupyter notebook as on super-computing machines.

nbody6tt, based on Aarseth's nbody6 (ascl:1102.006) code, includes the treatment of complex galactic tides in a direct N-body simulation of a star cluster through the use of tidal tensors (tt) and offers two complementary methods. The first allows consideration of any kind of galaxy and orbit, thus offering versatility; this method cannot be used to study tidal debris, as it relies on the tidal approximation (linearization of the tidal force). The second method is not limited by this and does not require a galaxy simulation; the user defines a numerical function which takes position and time as arguments, and the galactic potential is returned. The space and time derivatives of the potential are used to (i) integrate the motion of the cluster on its orbit in the galaxy (starting from user-defined initial position and velocity vector), and (ii) compute the tidal acceleration on the stars.

I review the development of direct N-body codes at Cambridge over nearly 40 years, highlighting the main stepping stones. The first code (NBODY1) was based on the simple concepts of a force polynomial combined with individual time steps, where numerical problems due to close encounters were avoided by a softened potential. Fortuitously, the elegant Kustaanheimo-Stiefel two-body regularization soon permitted small star clusters to be studied (NBODY3). Subsequent extensions to unperturbed three-body and four-body regularization proved beneficial in dealing with multiple interactions. Investigations of larger systems became possible with the Ahmad-Cohen neighbor scheme which was used more than 20 years ago for expanding universe models of 4000 galaxies (NBODY2). Combining the neighbor scheme with the regularization procedures enabled more realistic star clusters to be considered (NBODY5). After a period of simulations with no apparent technical progress, chain regularization replaced the treatment of compact subsystems (NBODY3, NBODY5). More recently, the Hermite integration method provided a major advance and has been implemented on the special-purpose HARP computers (NBODY4) together with an alternative version for workstations and supercomputers (NBODY6). These codes also include a variety of algorithms for stellar evolution based on fast lookup functions. The treatment of primordial binaries contains efficient procedures for chaotic two-body motion as well as tidal circularization, and special attention is paid to hierarchical systems and their stability. This family of N-body codes constitutes a powerful tool for dynamical simulations which is freely available to the astronomical community, and the massive effort owes much to collaborators.

NAVanalysis studies the non-baryonic, or non-Newtonian, contribution to galaxy rotation curves straight from a given data sample. Conclusions on the radial profile of a given model can be drawn without individual galaxy fits to provide an efficient sample comparison. The method can be used to eliminate model parameter regions, find the most probable parameter regions, and uncover trends not easy to find from standard fits. Further, NAVanalysis can compare different approaches and models.

Nauyaca infers planetary masses and orbits from mid-transit times fitting. The code requires transit ephemeris per planet and stellar mass and radius, and uses minimization routines and a Markov chain Monte Carlo method to find planet parameters that best reproduce the transit times based on numerical simulations. The code package provides customized plotting tools for analyzing the results.

NAPLES (Numerical Analysis of PLanetary EncounterS) performs batch propagations of close encounters in the three-body problem and computes the numerical error with respect to reference trajectories computed in quadruple precision. It uses the LSODAR integrator from ODEPACK (ascl:1905.021) and the equations of motion correspond to several regularized formulations.

nanopipe is a data reduction pipeline for calibration, RFI removal, and pulse time-of-arrival measurement from radio pulsar data. It was developed primarily for use by the NANOGrav project. nanopipe is written in Python, and depends on the PSRCHIVE (ascl:1105.014) library.

NaMaster computes full-sky angular cross-power spectra of masked, spin-0 and spin-2 fields with an arbitrary number of known contaminants using a pseudo-Cl (aka MASTER) approach. The code also implements E/B-mode purification and offers both full-sky and flat-sky modes. NaMaster is available as a C library, Python module, and standalone program.

Naima computes non-thermal radiation from relativistic particle populations. It includes tools to perform MCMC fitting of radiative models to X-ray, GeV, and TeV spectra using emcee (ascl:1303.002), an affine-invariant ensemble sampler for Markov Chain Monte Carlo. Naima is an Astropy (ascl:1304.002) affiliated package.

naif extracts frequencies and respective amplitudes from time-series, such as that of an orbital coordinate. Based on the Numerical Analysis of Fundamental Frequencies (NAFF) algorithm and written in Python, naif offers some improvements, particularly in computation time. It also offers functions to plot the power-spectrum before extraction of each frequency, which can be useful for debugging particular orbits.

Nahoon is a gas-phase chemical model that computes the chemical evolution in a 1D temperature and density structure. It uses chemical networks downloaded from the KInetic Database for Astrochemistry (KIDA) but the model can be adapted to any network. The program is written in Fortran 90 and uses the DLSODES (double precision) solver from the ODEPACK package (ascl:1905.021) to solve the coupled stiff differential equations. The solver computes the chemical evolution of gas-phase species at a fixed temperature and density and can be used in one dimension (1D) if a grid of temperature, density, and visual extinction is provided. Grains, both neutral and negatively charged, and electrons are considered as chemical species and their concentrations are computed at the same time as those of the other species. Nahoon contains a test to check the temperature range of the validity of the rate coefficients and avoid extrapolations outside this range. A test is also included to check for duplication of chemical reactions, defined over complementary ranges of temperature.

NAFE (Noise Adaptive Fuzzy Equalization) is an image processing method allowing for visualization of fine structures in SDO AIA high dynamic range images. It produces artifact-free images and gives significantly better results than methods based on convolution or Fourier transform.

N-MODY is a parallel particle-mesh code for collisionless N-body simulations in modified Newtonian dynamics (MOND). N-MODY is based on a numerical potential solver in spherical coordinates that solves the non-linear MOND field equation, and is ideally suited to simulate isolated stellar systems. N-MODY can be used also to compute the MOND potential of arbitrary static density distributions. A few applications of N-MODY indicate that some astrophysically relevant dynamical processes are profoundly different in MOND and in Newtonian gravity with dark matter.

N-GenIC is an initial conditions code for cosmological structure formation that can be used to set-up random N-body realizations of Gaussian random fields with a prescribed power spectrum in a homogeneously sampled periodic box. The code creates cosmological initial conditions based on the Zeldovich approximation, in a format directly compatible with GADGET (ascl:0003.001) or AREPO (ascl:1909.010).

MYRIAD is a C++ code for collisional N-body simulations of star clusters. The code uses the Hermite fourth-order scheme with block time steps, for advancing the particles in time, while the forces and neighboring particles are computed using the GRAPE-6 board. Special treatment is used for close encounters, binary and multiple sub-systems that either form dynamically or exist in the initial configuration. The structure of the code is modular and allows the appropriate treatment of more physical phenomena, such as stellar and binary evolution, stellar collisions and evolution of close black-hole binaries. Moreover, it can be easily modified so that the part of the code that uses GRAPE-6 could be replaced by another module that uses other accelerating-hardware like the Graphics Processing Units (GPUs). Appropriate choice of the free parameters give a good accuracy and speed for simulations of star clusters up to and beyond core collapse. The code accuracy becomes comparable and even better than the accuracy of existing codes when a number of close binary systems is dynamically created in a simulation; this is due to the high accuracy of the method that is used for close binary and multiple sub-systems. The code can be used for evolving star clusters containing equal-mass stars or star clusters with an initial mass function (IMF) containing an intermediate mass black hole (IMBH) at the center and/or a fraction of primordial binaries, which are systems of particular astrophysical interest.

MYRaf is a practicable astronomical image reduction and photometry software and interface for IRAF (ascl:9911.002). The library uses IRAF, PyRAF (ascl:1207.011), Ginga (ascl:1303.020), and other python packages with a Qt framework for automated software processing of data from robotic telescopes.

myRadex solves essentially the same problem as RADEX (ascl:1010.075), except that it takes a different approach to solve the statistical equilibrium problem. Given an initial distribution, myRadex evolves the system towards equilibrium using an ODE solver. Frequencies in the input file are used by default, and a function for calculating critical densities of all the transitions of a molecule is included.

The original MUSIC code (ascl:1311.011) was designed to provide initial conditions for zoom initial conditions and is limited for applications to large-scale cosmological simulations. MUSIC2-monofonIC generates high order LPT/PPT cosmological initial conditions for single resolution cosmological simulations, and can be used for rapid predictions of large-scale structure. MUSIC2-monofonIC offers support for up to 3rd order Lagrangian perturbation theory, PPT (Semiclassical PT for Eulerian grids) up to 2nd order, and for mixed CDM+baryon sims. It direct interfaces with CLASS and can use file input from CAMB; it offers multiple output modules for RAMSES (ascl:1011.007), Arepo (ascl:1909.010), Gadget-2/3 (ascl:0003.001), and HACC via plugins, and new modules/plugins can be easily added.

MUSIC generates multi-scale initial conditions with multiple levels of refinements for cosmological ‘zoom-in’ simulations. The code uses an adaptive convolution of Gaussian white noise with a real-space transfer function kernel together with an adaptive multi-grid Poisson solver to generate displacements and velocities following first- (1LPT) or second-order Lagrangian perturbation theory (2LPT). MUSIC achieves rms relative errors of the order of 10−4 for displacements and velocities in the refinement region and thus improves in terms of errors by about two orders of magnitude over previous approaches. In addition, errors are localized at coarse-fine boundaries and do not suffer from Fourier space-induced interference ringing.

MUSE-PSFR reconstructs a PSF for the MUSE WFM-AO mode using telemetry data from SPARTA. The algorithm conducts a Fourier analysis of the laser-assisted ground layer adaptive optics (GLAO) residual phase statistics and has been test in end-to-end simulations. A sensitivity analysis was conducted to determine the required accuracy in terms of input parameters. MUSE-PSFR is capable of reconstructing the critical parameters of a PSF and can be used with MUSE 3D data by all MUSE users.

The MUSE pipeline turns the complex raw data of the MUSE integral field spectrograph into a ready-to-use datacube for scientific analysis.

MUSCLE (MUltiscale Spherical ColLapse Evolution) produces low-redshift approximate N-body realizations accurate to few-Megaparsec scales. It applies a spherical-collapse prescription on multiple Gaussian-smoothed scales. It achieves higher accuracy than perturbative schemes (Zel'dovich and second-order Lagrangian perturbation theory - 2LPT), and by including the void-in-cloud process (voids in large-scale collapsing regions), solves problems with a single-scale spherical-collapse scheme.

MuSCAT2_transit_pipeline provides photometry and transit analysis pipelines for MuSCAT2. It consists of a set of executable scripts and two Python packages: muscat2ph for photometry, and muscat2ta for transit analysis. The MuSCAT2 photometry can be carried out using the scripts only. The transit analysis can also in most cases be done using the main transit analysis script m2fit, but the muscat2ta package also offers high-level classes that can be used to carry out more customized transit analysis as a Python script (or Jupyter notebook).

Munipack provides easy-to-use tools for all astronomical astrometry and photometry, access to Virtual Observatory as well as FITS files operations and a simple user interface along with a powerful processing engine. Its many features include a FITS images viewer that allows for basic (astronomical) operations with frames, advanced image processor supporting an infinite dynamic range and advanced color management, and astrometric calibration of images. The astrometry module uses robust statistical estimators and algorithms. The photometry module provides the classical method detection of stars and implements the aperture photometry, calibrated on the basis of photon statistics, and allows for the automatic detection and aperture photometry of stars; calibration on absolute fluxes is possible. The software also provides a standard way to correct for all the bias, dark and flat-field frames, and many other features.

Multipoles, written in Python, calculates the quadrupole and hexadecapole approximations of the finite-source magnification: quadrupole (Wk,rho,Gamma) and hexadecapole (Wk,rho,Gamma). The code is efficient and faster than previously available methods, and could be generalized for use on large portions of the light curves.

We propose a novel representation of cosmic microwave anisotropy maps, where each multipole order l is represented by l unit vectors pointing in directions on the sky and an overall magnitude. These "multipole vectors and scalars" transform as vectors under rotations. Like the usual spherical harmonics, multipole vectors form an irreducible representation of the proper rotation group SO(3). However, they are related to the familiar spherical harmonic coefficients, alm, in a nonlinear way, and are therefore sensitive to different aspects of the CMB anisotropy. Nevertheless, it is straightforward to determine the multipole vectors for a given CMB map and we present an algorithm to compute them. Using the WMAP full-sky maps, we perform several tests of the hypothesis that the CMB anisotropy is statistically isotropic and Gaussian random. We find that the result from comparing the oriented area of planes defined by these vectors between multipole pairs 2<=l1!=l2<=8 is inconsistent with the isotropic Gaussian hypothesis at the 99.4% level for the ILC map and at 98.9% level for the cleaned map of Tegmark et al. A particular correlation is suggested between the l=3 and l=8 multipoles, as well as several other pairs. This effect is entirely different from the now familiar planarity and alignment of the quadrupole and octupole: while the aforementioned is fairly unlikely, the multipole vectors indicate correlations not expected in Gaussian random skies that make them unusually likely. The result persists after accounting for pixel noise and after assuming a residual 10% dust contamination in the cleaned WMAP map. While the definitive analysis of these results will require more work, we hope that multipole vectors will become a valuable tool for various cosmological tests, in particular those of cosmic isotropy.

We present further development and the first public release of our multimodal nested sampling algorithm, called MultiNest. This Bayesian inference tool calculates the evidence, with an associated error estimate, and produces posterior samples from distributions that may contain multiple modes and pronounced (curving) degeneracies in high dimensions. The developments presented here lead to further substantial improvements in sampling efficiency and robustness, as compared to the original algorithm presented in Feroz & Hobson (2008), which itself significantly outperformed existing MCMC techniques in a wide range of astrophysical inference problems. The accuracy and economy of the MultiNest algorithm is demonstrated by application to two toy problems and to a cosmological inference problem focusing on the extension of the vanilla $Lambda$CDM model to include spatial curvature and a varying equation of state for dark energy. The MultiNest software is fully parallelized using MPI and includes an interface to CosmoMC (ascl:1106.025). It will also be released as part of the SuperBayeS package (ascl:1109.007) for the analysis of supersymmetric theories of particle physics.

MultiModes extracts the most significant frequencies of a sample of classical pulsating stars. The code takes a directory with light curves and initial parameters as input. For every light curve, the code calculates the frequencies spectrum, or periodogram, with the Fast Lomb Scargle algorithm, extracts the higher amplitude peak, and evaluates whether it is a real signal or noise. It fits frequency, amplitude, and phase through non-linear optimization, using a multisine function. This function is redefined with the new calculated parameters. MultiModes then does a simultaneous fit of a number of peaks (20 by default), subtracts them from the original signal, and goes back to the beginning of the loop with the residual, repeating the same process until the stop criterion is reached. After that, the code can filter suspicious spurious frequencies, those of low amplitude below the Rayleigh resolution, and possible combined frequencies.