ME(SSY)**2 stands for “Monte-carlo Experiments with Spherically SYmmetric Stellar SYstems." This code simulates the long term evolution of spherical clusters of stars; it was devised specifically to treat dense galactic nuclei. It is based on the pioneering Monte Carlo scheme proposed by Hénon in the 70's and includes all relevant physical ingredients (2-body relaxation, stellar mass spectrum, collisions, tidal disruption, ldots). It is basically a Monte Carlo resolution of the Fokker-Planck equation. It can cope with any stellar mass spectrum or velocity distribution. Being a particle-based method, it also allows one to take stellar collisions into account in a very realistic way. This unique code, featuring most important physical processes, allows million particle simulations, spanning a Hubble time, in a few CPU days on standard personal computers and provides a wealth of data only rivalized by N-body simulations. The current version of the software requires the use of routines from the "Numerical Recipes in Fortran 77" (http://www.nrbook.com/a/bookfpdf.php).
The Mechanic package is a numerical framework for dynamical astronomy, designed to help in massive numerical simulations by efficient task management and unified data storage. The code is built on top of the Message Passing Interface (MPI) and Hierarchical Data Format (HDF5) standards and uses the Task Farm approach to manage numerical tasks. It relies on the core-module approach. The numerical problem implemented in the user-supplied module is separated from the host code (core). The core is designed to handle basic setup, data storage and communication between nodes in a computing pool. It has been tested on large CPU-clusters, as well as desktop computers. The Mechanic may be used in computing dynamical maps, data optimization or numerical integration.
We describe an automated method for assigning the most probable physical parameters to the components of an eclipsing binary, using only its photometric light curve and combined colors. With traditional methods, one attempts to optimize a multi-parameter model over many iterations, so as to minimize the chi-squared value. We suggest an alternative method, where one selects pairs of coeval stars from a set of theoretical stellar models, and compares their simulated light curves and combined colors with the observations. This approach greatly reduces the parameter space over which one needs to search, and allows one to estimate the components' masses, radii and absolute magnitudes, without spectroscopic data. We have implemented this method in an automated program using published theoretical isochrones and limb-darkening coefficients. Since it is easy to automate, this method lends itself to systematic analyses of datasets consisting of photometric time series of large numbers of stars, such as those produced by OGLE, MACHO, TrES, HAT, and many others surveys.
MegaLUT is a simple and fast method to correct ellipticity measurements of galaxies from the distortion by the instrumental and atmospheric point spread function (PSF), in view of weak lensing shear measurements. The method performs a classification of galaxies and associated PSFs according to measured shape parameters, and builds a lookup table of ellipticity corrections by supervised learning. This new method has been applied to the GREAT10 image analysis challenge, and demonstrates a refined solution that obtains the highly competitive quality factor of Q = 142, without any power spectrum denoising or training. Of particular interest is the efficiency of the method, with a processing time below 3 ms per galaxy on an ordinary CPU.
megaman is a scalable manifold learning package implemented in python. It has a front-end API designed to be familiar to scikit-learn but harnesses the C++ Fast Library for Approximate Nearest Neighbors (FLANN) and the Sparse Symmetric Positive Definite (SSPD) solver Locally Optimal Block Precodition Gradient (LOBPCG) method to scale manifold learning algorithms to large data sets. It is designed for researchers and as such caches intermediary steps and indices to allow for fast re-computation with new parameters.
MEPSA (Multiple Excess Peak Search Algorithm) identifies peaks within a uniformly sampled time series affected by uncorrelated Gaussian noise. MEPSA scans the time series at different timescales by comparing a given peak candidate with a variable number of adjacent bins. While this has originally been conceived for the analysis of gamma-ray burst light (GRB) curves, its usage can be readily extended to other astrophysical transient phenomena whose activity is recorded through different surveys. MEPSA's high flexibility permits the mask of excess patterns it uses to be tailored and optimized without modifying the code.
MeqTrees is a software package for implementing Measurement Equations. This makes it uniquely suited for simulation and calibration of radioastronomical data, especially that involving new radiotelescopes and observational regimes. MeqTrees is implemented as a Python-based front-end called the meqbrowser, and an efficient (C++-based) computational back-end called the meqserver. Numerical models are defined on the front-end via a Python-based Tree Definition Language (TDL), then rapidly executed on the back-end. The use of TDL facilitates an extremely short turn-around time for experimentation with new ideas. This is also helped by unprecedented visualization capabilities for all final and intermediate results. A flexible data model and a number of important optimizations in the back-end ensures that the numerical performance is comparable to that of hand-written code.
MeqTrees includes a highly capable FITS viewer and sky model manager called Tigger, which can also work as a standalone tool.
Mercury-T calculates the evolution of semi-major axis, eccentricity, inclination, rotation period and obliquity of the planets as well as the rotation period evolution of the host body; it is based on the N-body code Mercury (Chambers 1999, ascl:1201.008). It is flexible, allowing computation of the tidal evolution of systems orbiting any non-evolving object (if its mass, radius, dissipation factor and rotation period are known), but also evolving brown dwarfs (BDs) of mass between 0.01 and 0.08 M⊙, an evolving M-dwarf of 0.1 M⊙, an evolving Sun-like star, and an evolving Jupiter.
Mercury is a new general-purpose software package for carrying out orbital integrations for problems in solar-system dynamics. Suitable applications include studying the long-term stability of the planetary system, investigating the orbital evolution of comets, asteroids or meteoroids, and simulating planetary accretion. Mercury is designed to be versatile and easy to use, accepting initial conditions in either Cartesian coordinates or Keplerian elements in "cometary" or "asteroidal" format, with different epochs of osculation for different objects. Output from an integration consists of osculating elements, written in a machine-independent compressed format, which allows the results of a calculation performed on one platform to be transferred (e.g. via FTP) and decoded on another.
During an integration, Mercury monitors and records details of close encounters, sungrazing events, ejections and collisions between objects. The effects of non-gravitational forces on comets can also be modeled. The package supports integrations using a mixed-variable symplectic routine, the Bulirsch-Stoer method, and a hybrid code for planetary accretion calculations.
Merger Trees uses a Monte Carlo algorithm to generate merger trees describing the formation history of dark matter haloes; the algorithm is implemented in Fortran. The algorithm is a modification of the algorithm of Cole et al. used in the GALFORM semi-analytic galaxy formation model (ascl:1510.005) based on the Extended Press–Schechter theory. It should be applicable to hierarchical models with a wide range of power spectra and cosmological models. It is tuned to be in accurate agreement with the conditional mass functions found in the analysis of merger trees extracted from the Λ cold dark matter Millennium N-body simulation. The code should be a useful tool for semi-analytic models of galaxy formation and for modelling hierarchical structure formation in general.
Stellar physics and evolution calculations enable a broad range of research in astrophysics. Modules for Experiments in Stellar Astrophysics (MESA) is a suite of open source libraries for a wide range of applications in computational stellar astrophysics. A newly designed 1-D stellar evolution module, MESA star, combines many of the numerical and physics modules for simulations of a wide range of stellar evolution scenarios ranging from very-low mass to massive stars, including advanced evolutionary phases. MESA star solves the fully coupled structure and composition equations simultaneously. It uses adaptive mesh refinement and sophisticated timestep controls, and supports shared memory parallelism based on OpenMP. Independently usable modules provide equation of state, opacity, nuclear reaction rates, and atmosphere boundary conditions. Each module is constructed as a separate Fortran 95 library with its own public interface. Examples include comparisons to other codes and show evolutionary tracks of very low mass stars, brown dwarfs, and gas giant planets; the complete evolution of a 1 Msun star from the pre-main sequence to a cooling white dwarf; the Solar sound speed profile; the evolution of intermediate mass stars through the thermal pulses on the He-shell burning AGB phase; the interior structure of slowly pulsating B Stars and Beta Cepheids; evolutionary tracks of massive stars from the pre-main sequence to the onset of core collapse; stars undergoing Roche lobe overflow; and accretion onto a neutron star.
MeshLab processes and edits 3D triangular meshes. It includes tools for editing, cleaning, healing, inspecting, rendering, texturing and converting meshes, and offers features for processing raw data produced by 3D digitization tools and devices and for preparing models for 3D printing.
Meso-NH is the non-hydrostatic mesoscale atmospheric model of the French research community jointly developed by the Laboratoire d'Aérologie (UMR 5560 UPS/CNRS) and by CNRM (UMR 3589 CNRS/Météo-France). Meso-NH incorporates a non-hydrostatic system of equations for dealing with scales ranging from large (synoptic) to small (large eddy) scales while calculating budgets and has a complete set of physical parameterizations for the representation of clouds and precipitation. It is coupled to the surface model SURFEX for representation of surface atmosphere interactions by considering different surface types (vegetation, city, ocean, lake) and allows a multi-scale approach through a grid-nesting technique. Meso-NH is versatile, vectorized, parallelized, and operates in 1D, 2D or 3D; it is coupled with a chemistry module (including gas-phase, aerosol, and aqua-phase components) and a lightning module, and has observation operators that compare model output directly with satellite observations, radar, lidar and GPS.
MESS is a Monte Carlo simulation IDL code which uses either the results of the statistical analysis of the properties of discovered planets, or the results of the planet formation theories, to build synthetic planet populations fully described in terms of frequency, orbital elements and physical properties. They can then be used to either test the consistency of their properties with the observed population of planets given different detection techniques or to actually predict the expected number of planets for future surveys. It can be used to probe the physical and orbital properties of a putative companion within the circumstellar disk of a given star and to test constrain the orbital distribution properties of a potential planet population around the members of the TW Hydrae association. Finally, using in its predictive mode, the synergy of future space and ground-based telescopes instrumentation has been investigated to identify the mass-period parameter space that will be probed in future surveys for giant and rocky planets.
The Meudon PDR code computes the atomic and molecular structure of interstellar clouds. It can be used to study the physics and chemistry of diffuse clouds, photodissociation regions (PDRs), dark clouds, or circumstellar regions. The model computes the thermal balance of a stationary plane-parallel slab of gas and dust illuminated by a radiation field and takes into account heating processes such as the photoelectric effect on dust, chemistry, cosmic rays, etc. and cooling resulting from infrared and millimeter emission of the abundant species. Chemistry is solved for any number of species and reactions. Once abundances of atoms and molecules and level excitation of the most important species have been computed at each point, line intensities and column densities can be deduced.
CAMB is a public Fortran 90 code written by Antony Lewis and Anthony Challinor for evaluating cosmological observables. MGCAMB is a modified version of CAMB in which the linearized Einstein equations of General Relativity (GR) are modified. MGCAMB can also be used in CosmoMC to fit different modified-gravity (MG) models to data.
MGE_FIT_SECTORS performs Multi-Gaussian Expansion (MGE) fits to galaxy images. The MGE parameterizations are useful in the construction of realistic dynamical models of galaxies, PSF deconvolution of images, the correction and estimation of dust absorption effects, and galaxy photometry. The algorithm is well suited for use with multiple-resolution images (e.g. Hubble Space Telescope (HST) and ground-based images).
We have developed MGGPOD, a user-friendly suite of Monte Carlo codes built around the widely used GEANT (Version 3.21) package. The MGGPOD Monte Carlo suite and documentation are publicly available for download. MGGPOD is an ideal tool for supporting the various stages of gamma-ray astronomy missions, ranging from the design, development, and performance prediction through calibration and response generation to data reduction. In particular, MGGPOD is capable of simulating ab initio the physical processes relevant for the production of instrumental backgrounds. These include the build-up and delayed decay of radioactive isotopes as well as the prompt de-excitation of excited nuclei, both of which give rise to a plethora of instrumental gamma-ray background lines in addition to continuum backgrounds.
MGHalofit is a modified gravity extension of the fitting formula for the matter power spectrum of HALOFIT and its improvement by Takahashi et al. MGHalofit is implemented in MGCAMB, which is based on CAMB. MGHalofit calculates the nonlinear matter power spectrum P(k) for the Hu-Sawicki model. Comparing MGHalofit predictions at various redshifts (z<=1) to the f(R) simulations, the accuracy on P(k) is 6% at k<1 h/Mpc and 12% at 1<k<10 h/Mpc respectively.
MHF is a Dark Matter halo finder that is based on the refinement grids of MLAPM. The grid structure of MLAPM adaptively refines around high-density regions with an automated refinement algorithm, thus naturally "surrounding" the Dark Matter halos, as they are simply manifestations of over-densities within (and exterior) to the underlying host halo. Using this grid structure, MHF restructures the hierarchy of nested isolated MLAPM grids into a "grid tree". The densest cell in the end of a tree branch marks center of a prospective Dark Matter halo. All gravitationally bound particles about this center are collected to obtain the final halo catalog. MHF automatically finds halos within halos within halos.
MIA+EWS is a package of two data reduction tools for MIDI data which uses power-spectrum analysis or the information contained in the spectrally-dispersed fringe measurements in order to estimate the correlated flux and the visibility as function of wavelength in the N-band. MIA, which stands for MIDI Interactive Analysis, uses a Fast Fourier Transformation to calculate the Fourier amplitudes of the fringe packets to calculate the correlated flux and visibility. EWS stands for Expert Work-Station, which is a collection of IDL tools to apply coherent visibility analysis to reduce MIDI data. The EWS package allows the user to control and examine almost every aspect of MIDI data and its reduction. The usual data products are the correlated fluxes, total fluxes and differential phase.
micrOMEGAs calculates the properties of cold dark matter in a generic model of particle physics. First developed to compute the relic density of dark matter, the code also computes the rates for dark matter direct and indirect detection. The code provides the mass spectrum, cross-sections, relic density and exotic fluxes of gamma rays, positrons and antiprotons. The propagation of charged particles in the Galactic halo is handled with a module that allows to easily modify the propagation parameters. The cross-sections for both spin dependent and spin independent interactions of WIMPS on protons are computed automatically as well as the rates for WIMP scattering on nuclei in a large detector. Annihilation cross-sections of the dark matter candidate at zero velocity, relevant for indirect detection of dark matter, are computed automatically, and the propagation of charged particles in the Galactic halo is also handled.
midIR_sensitivity is IDL code that calculates the sensitivity of a ground-based mid-infrared instrument for astronomy. The code was written for the Phase A study of the instrument METIS (http://www.strw.leidenuniv.nl/metis), the Mid-Infrared E-ELT Imager and Spectrograph, for the 42-m European Extremely Large Telescope. The model uses a detailed set of input parameters for site characteristics and atmospheric profiles, optical design, and thermal background. The code and all input parameters are highly tailored for the particular design parameters of the E-ELT and METIS, however, the program is structured in such a way that the parameters can easily be adjusted for a different system, or alternative input files used.
The Markwardt IDL Library contains routines for curve fitting and function minimization, including MPFIT (ascl:1208.019), statistical tests, and non-linear optimization (TNMIN); graphics programs including plotting three-dimensional data as a cube and fixed- or variable-width histograms; adaptive numerical integration (Quadpack), Chebyshev approximation and interpolation, and other mathematical tools; many ephemeris and timing routines; and array and set operations, such as computing the fast product of a large array, efficiently inserting or deleting elements in an array, and performing set operations on numbers and strings; and many other useful and varied routines.
Miex calculates Mie scattering coefficients and efficiency factors for broad grain size distributions and a very wide wavelength range (λ ≈ 10-10-10-2m) of the interacting radiation and incorporates standard solutions of the scattering amplitude functions. The code handles arbitrary size parameters, and single scattering by particle ensembles is calculated by proper averaging of the respective parameters.
This triggering code calculates the correlation function between two astrophysical data catalogs using the Landy-Szalay approximator generalized for heterogeneous datasets (Landy & Szalay, 1993; Bradshaw et al, 2011) or the auto-correlation function of one dataset. It assumes that one catalog has positional information as well as an object size (effective radius), and the other only positional information.
MillCgs clusters galaxies from the semi-analytic models run on top of the Millennium Simulation to identify Compact Groups. MillCgs uses a machine learning clustering algorithm to find the groups and then runs analytics to filter out the groups that do not fit the user specified criteria. The package downloads the data, processes it, and then creates graphs of the data.
millennium-tap-query is a simple wrapper for the Python package requests to deal with connections to the Millennium TAP Web Client. With this tool you can perform basic or advanced queries to the Millennium Simulation database and download the data products. millennium-tap-query is similar to the TAP query tool in the German Astrophysical Virtual Observatory (GAVO) VOtables package.
The millisearch.for code was used to generate a new search for the gravitational lens effects of a significant cosmological density of supermassive compact objects (SCOs) on gamma-ray bursts. No signal attributable to millilensing was found. We inspected the timing data of 774 BATSE-triggered GRBs for evidence of millilensing: repeated peaks similar in light-curve shape and spectra. Our null detection leads us to conclude that, in all candidate universes simulated, OmegaSCO < 0.1 is favored for 105 < MSCO/Modot < 109, while in some universes and mass ranges the density limits are as much as 10 times lower. Therefore, a cosmologically significant population of SCOs near globular cluster mass neither came out of the primordial universe, nor condensed at recombination.
Minerva is a cylindrical coordinate extension of the Athena astrophysical MHD code of Stone, Gardiner, Teuben, and Hawley. The extension follows the approach of Athena's original developers and has been designed to alter the existing Cartesian-coordinates code as minimally and transparently as possible. The numerical equations in cylindrical coordinates are formulated to maintain consistency with constrained transport (CT), a central feature of the Athena algorithm, while making use of previously implemented code modules such as the Riemann solvers. Angular momentum transport, which is critical in astrophysical disk systems dominated by rotation, is treated carefully.
MIRIAD is a radio interferometry data-reduction package, designed for taking raw visibility data through calibration to the image analysis stage. It has been designed to handle any interferometric array, with working examples for BIMA, CARMA, SMA, WSRT, and ATCA. A separate version for ATCA is available, which differs in a few minor ways from the CARMA version.
MIS is a pipeline toolkit using the package MIRIAD to combine Interferometric and Single Dish data. This was prompted by our observations made with the Combined Array For Research in Millimeter-wave Astronomy (CARMA) interferometer of the star-forming region NGC 1333, a large survey highlighting the new 23-element and singledish observing modes. The project consists of 20 CARMA datasets each containing interferometric as well as simultaneously obtained single dish data, for 3 molecular spectral lines and continuum, in 527 different pointings, covering an area of about 8 by 11 arcminutes. A small group of collaborators then shared this toolkit and their parameters via CVS, and scripts were developed to ensure uniform data reduction across the group. The pipeline was run end-to-end each night that new observations were obtained, producing maps that contained all the data to date. This approach could serve as a model for repeated calibration and mapping of large mixed-mode correlation datasets from ALMA.
MissFITS is a program that performs basic maintenance and packaging tasks on FITS files using an optimized FITS library. MissFITS can:
missForest imputes missing values particularly in the case of mixed-type data. It uses a random forest trained on the observed values of a data matrix to predict the missing values. It can be used to impute continuous and/or categorical data including complex interactions and non-linear relations. It yields an out-of-bag (OOB) imputation error estimate without the need of a test set or elaborate cross-validation and can be run in parallel to save computation time. missForest has been used to, among other things, impute variable star colors in an All-Sky Automated Survey (ASAS) dataset of variable stars with no NOMAD match.
mixT accurately predicts T derived from a single-temperature fit for a multi-component thermal plasma. It can be applied in the deprojection analysis of objects with the temperature and metallicity gradients, for correction of the PSF effects, for consistent comparison of numerical simulations of galaxy clusters and groups with the X-ray observations, and for estimating how emission from undetected components can bias the global X-ray spectral analysis.
mkj_libs provides a set of helper routines (vector operations, astrometry, statistical analysis of spherical data) for the main plane-fitting and analysis tools.
MLAPM simulates structure formation from collisionless matter. The code, written in C, is purely grid-based and uses a recursively refined Cartesian grid to solve Poisson's equation for the potential, rather than obtaining the potential from a Green's function. Refinements can have arbitrary shapes and in practice closely follow the complex morphology of the density field that evolves. The timestep shortens by a factor two with each successive refinement. It is argued that an appropriate choice of softening length is of great importance and that the softening should be at all points an appropriate multiple of the local inter-particle separation. Unlike tree and P3M codes, multigrid codes automatically satisfy this requirement.
The parallel Python framework MLZ (Machine Learning and photo-Z) computes fast and robust photometric redshift PDFs using Machine Learning algorithms. It uses a supervised technique with prediction trees and random forest through TPZ that can be used for a regression or a classification problem, or a unsupervised methods with self organizing maps and random atlas called SOMz. These machine learning implementations can be efficiently combined into a more powerful one resulting in robust and accurate probability distributions for photometric redshifts.
Make Me A Star (MMAS) quickly generates stellar collision remnants and can be used in combination with realistic dynamical simulations of star clusters that include stellar collisions. The code approximates the merger process (including shock heating, hydrodynamic mixing, mass ejection, and angular momentum transfer) with simple algorithms based on conservation laws and a basic qualitative understanding of the hydrodynamics. These simple models agree very well with those from SPH (smoothed particle hydrodynamics) calculations of stellar collisions, and the subsequent stellar evolution of these models also matches closely that of the more accurate hydrodynamic models.
MOCASSIN is a fully 3D or 2D photoionisation and dust radiative transfer code which employs a Monte Carlo approach to the transfer of radiation through media of arbitrary geometry and density distribution. Written in Fortran, it was originally developed for the modelling of photoionised regions like HII regions and planetary nebulae and has since expanded and been applied to a variety of astrophysical problems, including modelling clumpy dusty supernova envelopes, star forming galaxies, protoplanetary disks and inner shell fluorence emission in the photospheres of stars and disk atmospheres. The code can deal with arbitrary Cartesian grids of variable resolution, it has successfully been used to model complex density fields from SPH calculations and can deal with ionising radiation extending from Lyman edge to the X-ray. The dust and gas microphysics is fully coupled both in the radiation transfer and in the thermal balance.
ModeCode is a publicly available code that computes the primordial scalar and tensor power spectra for single field inflationary models. ModeCode solves the inflationary mode equations numerically, avoiding the slow roll approximation. It provides an efficient and robust numerical evaluation of the inflationary perturbation spectrum, and allows the free parameters in the inflationary potential to be estimated within an MCMC computation. ModeCode also allows the estimation of reheating uncertainties once a potential has been specified. It is interfaced with CAMB and CosmoMC to compute cosmic microwave background angular power spectra and perform likelihood analysis and parameter estimation. It can be run as a standalone code as well. Errors in the results from ModeCode contribute negligibly to the error budget for analyses of data from Planck or other next generation experiments.
MOKA simulates the gravitational lensing signal from cluster-sized haloes. This algorithm implements recent results from numerical simulations to create realistic lenses with properties independent of numerical resolution and can be used for studies of the strong lensing cross section in dependence of halo structure.
Molecfit corrects astronomical observations for atmospheric absorption features based on fitting synthetic transmission spectra to the astronomical data, which saves a significant amount of valuable telescope time and increases the instrumental efficiency. Molecfit can also estimate molecular abundances, especially the water vapor content of the Earth’s atmosphere. The tool can be run from a command-line or more conveniently through a GUI.
MOLIERE-5 (Microwave Observation LIne Estimation and REtrieval) is a versatile forward and inversion model for the millimeter and submillimeter wavelengths range and includes an inversion model. The MOLIERE-5 forward model includes modules for the calculation of absorption coefficients, radiative transfer, and instrumental characteristics. The radiative transfer model is supplemented by a sensitivity module for estimating the contribution to the spectrum of each catalog line at its center frequency enabling the model to effectively filter for small spectral lines. The instrument model consists of several independent modules, including the calculation of the convolution of spectra and weighting functions with the spectrometer response functions. The instrument module also provides several options for modeling of frequency-switched observations. The MOLIERE-5 inversion model calculates linear Optimal Estimation, a least-squares retrieval method which uses statistical apriori knowledge on the retrieved parameters for the regularization of ill-posed inversion problems and computes diagnostics such as the measurement and smoothing error covariance matrices along with contribution and averaging kernel functions.
MOLSCAT is a FORTRAN code for quantum mechanical (coupled channel) solution of the nonreactive molecular scattering problem and was developed to obtain collision rates for molecules in the interstellar gas which are needed to understand microwave and infrared astronomical observations. The code is implemented for various types of collision partners. In addition to the essentially exact close coupling method several approximate methods, including the Coupled States and Infinite Order Sudden approximations, are provided.
Montage is an open source code toolkit for assembling Flexible Image Transport System (FITS) images into custom mosaics. It runs on all common Linux/Unix platforms, on desktops, clusters and computational grids, and supports all World Coordinate System (WCS) projections and common coordinate systems. Montage preserves spatial and calibration fidelity of input images, processes 40 million pixels in up to 32 minutes on 128 nodes on a Linux cluster, and provides independent engines for analyzing the geometry of images on the sky, re-projecting images, rectifying background emission to a common level, and co-adding images. It offers convenient tools for managing and manipulating large image files.
Montblanc, written in Python, is a GPU implementation of the Radio interferometer measurement equation (RIME) in support of the Bayesian inference for radio observations (BIRO) technique. The parameter space that BIRO explores results in tens of thousands of computationally expensive RIME evaluations before reduction to a single X2 value. The RIME is calculated over four dimensions, time, baseline, channel and source and the values in this 4D space can be independently calculated; therefore, the RIME is particularly amenable to a parallel implementation accelerated by Graphics Programming Units (GPUs). Montblanc is implemented for NVIDIA's CUDA architecture and outperforms MeqTrees (ascl:1209.010) and OSKAR.
MontePython 3 provides numerous ways to explore parameter space using Monte Carlo Markov Chain (MCMC) sampling, including Metropolis-Hastings, Nested Sampling, Cosmo Hammer, and a Fisher sampling method. This improved version of the Monte Python (ascl:1307.002) parameter inference code for cosmology offers new ingredients that improve the performance of Metropolis-Hastings sampling, speeding up convergence and offering significant time improvement in difficult runs. Additional likelihoods and plotting options are available, as are post-processing algorithms such as Importance Sampling and Adding Derived Parameter.
MOOG performs a variety of LTE line analysis and spectrum synthesis tasks. The typical use of MOOG is to assist in the determination of the chemical composition of a star. The basic equations of LTE stellar line analysis are followed. The coding is in various subroutines that are called from a few driver routines; these routines are written in standard FORTRAN. The standard MOOG version has been developed on unix, linux and macintosh computers.
One of the chief assets of MOOG is its ability to do on-line graphics. The plotting commands are given within the FORTRAN code. MOOG uses the graphics package SM, chosen for its ease of implementation in FORTRAN codes. Plotting calls are concentrated in just a few routines, and it should be possible for users of other graphics packages to substitute other appropriate FORTRAN commands.
MOOGStokes is a version of the MOOG one-dimensional local thermodynamic equilibrium radiative transfer code that incorporates a Stokes vector treatment of polarized radiation through a magnetic medium. It consists of three complementary programs that together can synthesize the disk-averaged emergent spectrum of a star with a magnetic field. The MOOGStokes package synthesizes emergent spectra of stars with magnetic fields in a familiar computational framework and produces disk-averaged spectra for all Stokes vectors ( I, Q, U, V ), normalized by the continuum.
MOPEX (MOsaicker and Point source EXtractor) is a package for reducing and analyzing imaging data, as well as MIPS SED data. MOPEX includes the point source extraction package, APEX.
MOPEX is designed to allow the user to:
MOPSIC was created to analyze bolometer data but can be used for much more versatile tasks. It is an extension of MOPSI; this software had been merged with the command interpreter of GILDAS. For data reduction, MOPSIC uses a special method to calculate the chopped signal. This gives much better results than the straight difference of the signals obtained at both chopper positions. In addition there are also scripts to reduce pointings, skydips, and to calculate the RCPs (Receiver Channel Parameters) from calibration maps. MOPSIC offers a much broader range of applications including advanced planning functions for mapping and onoff observations, post-reduction data analysis and processing and even reduction of non-bolometer data (optical, IR, spectroscopy).
MOSFiT (Modular Open-Source Fitter for Transients) downloads transient datasets from open online catalogs (e.g., the Open Supernova Catalog), generates Monte Carlo ensembles of semi-analytical light curve fits to those datasets and their associated Bayesian parameter posteriors, and optionally delivers the fitting results back to those same catalogs to make them available to the rest of the community. MOSFiT helps bridge the gap between observations and theory in time-domain astronomy; in addition to making the application of existing models and creation of new models as simple as possible, MOSFiT yields statistically robust predictions for transient characteristics, with a standard output format that includes all the setup information necessary to reproduce a given result.
MPDAF, the MUSE Python Data Analysis Framework, provides tools to work with MUSE-specific data (for example, raw data and pixel tables), and with more general data such as spectra, images, and data cubes. Originally written to work with MUSE data, it can also be used for other data, such as that from the Hubble Space Telescope. MPDAF also provides MUSELET, a SExtractor-based tool to detect emission lines in a data cube, and a format to gather all the information on a source in one FITS file. MPDAF was developed and is maintained by CRAL (Centre de Recherche Astrophysique de Lyon).
These IDL routines provide a robust and relatively fast way to perform least-squares curve and surface fitting. The algorithms are translated from MINPACK-1, which is a rugged minimization routine found on Netlib, and distributed with permission. This algorithm is more desirable than CURVEFIT because it is generally more stable and less likely to crash than the brute-force approach taken by CURVEFIT, which is based upon Numerical Recipes.
MPgrafic is a parallel MPI version of Grafic-1 which can produce large cosmological initial conditions on a cluster without requiring shared memory. The real Fourier transforms are carried in place using fftw while minimizing the amount of used memory (at the expense of performance) in the spirit of Grafic-1. The writing of the output file is also carried in parallel. In addition to the technical parallelization, it provides three extensions over Grafic-1:
MPI_XSTAR parallelizes execution of multiple XSTAR runs using Message Passing Interface (MPI). XSTAR (ascl:9910.008), part of the HEASARC's HEAsoft (ascl:1408.004) package, calculates the physical conditions and emission spectra of ionized gases. MPI_XSTAR invokes XSTINITABLE from HEASoft to generate a job list of XSTAR commands for given physical parameters. The job list is used to make directories in ascending order, where each individual XSTAR is spawned on each processor and outputs are saved. HEASoft's XSTAR2TABLE program is invoked upon the contents of each directory in order to produce table model FITS files for spectroscopy analysis tools.
MPI-AMRVAC is an MPI-parallelized Adaptive Mesh Refinement code, with some heritage (in the solver part) to the Versatile Advection Code or VAC, initiated by Gábor Tóth at the Astronomical Institute at Utrecht in November 1994, with help from Rony Keppens since 1996. Previous incarnations of the Adaptive Mesh Refinement version of VAC were of restricted use only, and have been used for basic research in AMR strategies, or for well-targeted applications. This MPI version uses a full octree block-based approach, and allows for general orthogonal coordinate systems. MPI-AMRVAC aims to advance any system of (primarily hyperbolic) partial differential equations by a number of different numerical schemes. The emphasis is on (near) conservation laws, with shock-dominated problems as a main research target. The actual equations are stored in separate modules, can be added if needed, and they can be selected by a simple configuration of the VACPP preprocessor. The dimensionality of the problem is also set through VACPP. The numerical schemes are able to handle discontinuities and smooth flows as well.
MPI-Defrost extends Frolov’s Defrost to an MPI-based cluster environment. This version has been restricted to a single field. Restoring two-field support should be straightforward, but will require some code changes. Some output options may also not be fully supported under MPI.
This code was produced to support our own work, and has been made available for the benefit of anyone interested in either oscillon simulations or an MPI capable version of Defrost, and it is provided on an "as-is" basis. Andrei Frolov is the primary developer of Defrost and we thank him for placing his work under the GPL (GNU Public License), and thus allowing us to distribute this modified version.
MPWide is a light-weight communication library for distributed computing. It is specifically developed to allow message passing over long-distance networks using path-specific optimizations. An early version of MPWide was used in the Gravitational Billion Body Project to allow simulations across multiple supercomputers.
The MRLENS package offers a new method for the reconstruction of weak lensing mass maps. It uses the multiscale entropy concept, which is based on wavelets, and the False Discovery Rate which allows us to derive robust detection levels in wavelet space. We show that this new restoration approach outperforms several standard techniques currently used for weak shear mass reconstruction. This method can also be used to separate E and B modes in the shear field, and thus test for the presence of residual systematic effects. We concentrate on large blind cosmic shear surveys, and illustrate our results using simulated shear maps derived from N-Body Lambda-CDM simulations with added noise corresponding to both ground-based and space-based observations.
MrMoose (Multi-Resolution Multi-Object/Origin Spectral Energy) fits user-defined models onto a set of multi-wavelength data using a Bayesian framework. The code can handle blended sources, large variation in resolution, and even upper limits consistently. It also generates a series of outputs allowing for an quick interpretation of the results. The code uses emcee (ascl:1303.002), and saves the emcee sampler object, thus allowing users to transfer the output to a personal graphical interface.
mrpy calculates the MRP parameterization of the Halo Mass Function. It calculates basic statistics of the truncated generalized gamma distribution (TGGD) with the TGGD class, including mean, mode, variance, skewness, pdf, and cdf. It generates MRP quantities with the MRP class, such as differential number counts and cumulative number counts, and offers various methods for generating normalizations. It can generate the MRP-based halo mass function as a function of physical parameters via the mrp_b13 function, and fit MRP parameters to data in the form of arbitrary curves and in the form of a sample of variates with the SimFit class. mrpy also calculates analytic hessians and jacobians at any point, and allows the user to alternate parameterizations of the same form via the reparameterize module.
MRrelation calculates the posterior predictive mass distribution for an individual planet. The probabilistic mass-radius relationship (M-R relation) is evaluated within a Bayesian framework, which both quantifies this intrinsic dispersion and the uncertainties on the M-R relation parameters.
Future cosmological surveys will provide 3D large scale structure maps with large sky coverage, for which a 3D Spherical Fourier-Bessel (SFB) analysis is natural. Wavelets are particularly well-suited to the analysis and denoising of cosmological data, but a spherical 3D isotropic wavelet transform does not currently exist to analyse spherical 3D data. We present a new fast Discrete Spherical Fourier-Bessel Transform (DSFBT) based on both a discrete Bessel Transform and the HEALPIX angular pixelisation scheme. We tested the 3D wavelet transform and as a toy-application, applied a denoising algorithm in wavelet space to the Virgo large box cosmological simulations and found we can successfully remove noise without much loss to the large scale structure. The new spherical 3D isotropic wavelet transform, called MRS3D, is ideally suited to analysing and denoising future 3D spherical cosmological surveys; it uses a novel discrete spherical Fourier-Bessel Transform. MRS3D is based on two packages, IDL and Healpix and can be used only if these two packages have been installed.
Multi-Source Self-Calibration (MSSC) provides direction-dependent calibration to standard phase referencing. The code combines multiple faint sources detected within the primary beam to derive phase corrections. Each source has its CLEAN model divided into the visibilities which results in multiple point sources that are stacked in the uv plane to increase the S/N, thus permitting self-calibration. This process applies only to wide-field VLBI data sets that detect and image multiple sources within one epoch.
MSWAVEF calculates hydrogenic and non-hydrogenic momentum-space electronic wavefunctions. Such wavefunctions are often required to calculate various collision processes, such as excitation and line broadening cross sections. The hydrogenic functions are calculated using the standard analytical expressions. The non-hydrogenic functions are calculated within quantum defect theory according to the method of Hoang Binh and van Regemorter (1997). Required Hankel transforms have been determined analytically for angular momentum quantum numbers ranging from zero to 13 using Mathematica. Calculations for higher angular momentum quantum numbers are possible, but slow (since calculated numerically). The code is written in IDL.
mTransport computes the 2-point-correlation function of the curvature and tensor perturbations in multifield models of inflation in the presence of a curved field space. It is a Mathematica implementation of the transport method which encompasses scenarios with violations of slow-roll conditions and turns of the trajectory in field space. It can be used for an arbitrary mass spectrum, including massive modes, particle production and models with quasi-single-field dynamics.
muLAn analyzes and fits light curves of gravitational microlensing events. The code includes all classical microlensing models (for example, single and binary microlenses, ground- and space-based parallax effects, orbital motion, finite-source effects, and limb-darkening); these can be combined into several time intervals of the analyzed light curve. Minimization methods include an Affine-Invariant Ensemble Sampler to generate a multivariate proposal function while running several Markov Chain Monte Carlo (MCMC) chains, for the set of parameters which is chosen to be fit; non-fitting parameters can be either kept fixed or set on a grid defined by the user. Furthermore, the software offers a model-free option to align all data sets together and allow inspection the light curve before any modeling work. It also comes with many useful routines (export publication-quality figures, data formatting and cleaning) and state-of-the-art statistical tools.
Modeling results can be interpreted using an interactive html page which contains all information about the light curve model, caustics, source trajectory, best-fit parameters and chi-square. Parameters uncertainties and statistical properties (such as multi-modal features of the posterior density) can be assessed from correlation plots. The code is modular, allowing the addition of other computation or minimization routines by directly adding their Python files without modifying the main code. The software has been designed to be easy to use even for the newcomer in microlensing, with external, synthetic and self-explanatory setup files containing all important commands and option settings. The user may choose to launch the code through command line instructions, or to import muLAn within another Python project like any standard Python package.
MulensModel calculates light curves of microlensing events. Both single and binary lens events are modeled and various higher-order effects can be included: extended source (with limb-darkening), annual microlensing parallax, and satellite microlensing parallax. The code is object-oriented and written in Python3, and requires AstroPy (ascl:1304.002).
The multiband periodogram is a general extension of the well-known Lomb-Scargle approach for detecting periodic signals in time-domain data. In addition to advantages of the Lomb-Scargle method such as treatment of non-uniform sampling and heteroscedastic errors, the multiband periodogram significantly improves period finding for randomly sampled multiband light curves (e.g., Pan-STARRS, DES and LSST). The light curves in each band are modeled as arbitrary truncated Fourier series, with the period and phase shared across all bands.
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.
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.
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.
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.
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.
The MUSE pipeline turns the complex raw data of the MUSE integral field spectrograph into a ready-to-use datacube for scientific analysis.
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.
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.
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.
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.
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 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.
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.
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.
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.
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.
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.
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).
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.
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.
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.
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).
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.
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.
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.
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.
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.
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.
Density, distribution function, quantile function and random generation for the 3D Navarro, Frenk & White (NFW) profile. The novel aspect to this is the quantile function, which provides an analytic transform for generating random samples. Functionally identical codes are provided in R and Python.
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