DICE is a C++ template library designed to solve collisionless fluid dynamics in 6D phase space using massively parallel supercomputers via an hybrid OpenMP/MPI parallelization. ColDICE, based on DICE, implements a cosmological and physical VLASOV-POISSON solver for cold systems such as dark matter (CDM) dynamics.
The Difference-smoothing MATLAB code measures the time delay from the light curves of images of a gravitationally lendsed quasar. It uses a smoothing timescale free parameter, generates more realistic synthetic light curves to estimate the time delay uncertainty, and uses X2 plot to assess the reliability of a time delay measurement as well as to identify instances of catastrophic failure of the time delay estimator. A systematic bias in the measurement of time delays for some light curves can be eliminated by applying a correction to each measured time delay.
DiffuseModel calculates the scattered radiation from dust scattering in the Milky Way based on stars from the Hipparcos catalog. It uses Monte Carlo to implement multiple scattering and assumes a user-supplied grid for the dust distribution. The output is a FITS file with the diffuse light over the Galaxy. It is intended for use in the UV (900 - 3000 A) but may be modified for use in other wavelengths and galaxies.
Diffusion.f is an exportable subroutine to calculate the diffusion of elements in stars. The routine solves exactly the Burgers equations and can include any number of elements as variables. The code has been used successfully by a number of different groups; applications include diffusion in the sun and diffusion in globular cluster stars. There are many other possible applications to main sequence and to evolved stars. The associated README file explains how to use the subroutine.
Difmap is a program developed for synthesis imaging of visibility data from interferometer arrays of radio telescopes world-wide. Its prime advantages over traditional packages are its emphasis on interactive processing, speed, and the use of Difference mapping techniques.
Software correlation, where a correlation algorithm written in a high-level language such as C++ is run on commodity computer hardware, has become increasingly attractive for small to medium sized and/or bandwidth constrained radio interferometers. In particular, many long baseline arrays (which typically have fewer than 20 elements and are restricted in observing bandwidth by costly recording hardware and media) have utilized software correlators for rapid, cost-effective correlator upgrades to allow compatibility with new, wider bandwidth recording systems and improve correlator flexibility. The DiFX correlator, made publicly available in 2007, has been a popular choice in such upgrades and is now used for production correlation by a number of observatories and research groups worldwide. Here we describe the evolution in the capabilities of the DiFX correlator over the past three years, including a number of new capabilities, substantial performance improvements, and a large amount of supporting infrastructure to ease use of the code. New capabilities include the ability to correlate a large number of phase centers in a single correlation pass, the extraction of phase calibration tones, correlation of disparate but overlapping sub-bands, the production of rapidly sampled filterbank and kurtosis data at minimal cost, and many more. The latest version of the code is at least 15% faster than the original, and in certain situations many times this value. Finally, we also present detailed test results validating the correctness of the new code.
DimReduce is a C++ package for performing nonlinear dimensionality reduction of very large datasets with Locally Linear Embedding (LLE) and its variants. DimReduce is built for speed, using the optimized linear algebra packages BLAS, LAPACK, and ARPACK. Because of the need for storing very large matrices (1000 by 10000, for our SDSS LLE work), DimReduce is designed to use binary FITS files as inputs and outputs. This means that using the code is a bit more cumbersome. For smaller-scale LLE, where speed of computation is not as much of an issue, the Modular Data Processing toolkit may be a better choice. It is a python toolkit with some LLE functionality, which VanderPlas contributed.
DIPSO plots spectroscopic data rapidly and combines analysis and high-quality graphical output in a simple command-line driven interactive environment. It can be used, for example, to fit emission lines, measure equivalent widths and fluxes, do Fourier analysis, and fit models to spectra. A macro facility allows convenient execution of regularly used sequences of commands, and a simple Fortran interface permits "personal" software to be integrated with the program. DIPSO is part of the Starlink software collection (ascl:1110.012).
The Mathematica code DirectDM takes the Wilson coefficients of relativistic operators that couple DM to the SM quarks, leptons, and gauge bosons and matches them onto a non-relativistic Galilean invariant EFT in order to calculate the direct detection scattering rates. A Python implementation of DirectDM is also available (ascl:1806.016).
DirectDM, written in Python, takes the Wilson coefficients of relativistic operators that couple DM to the SM quarks, leptons, and gauge bosons and matches them onto a non-relativistic Galilean invariant EFT in order to calculate the direct detection scattering rates. A Mathematica implementation of DirectDM is also available (ascl:1806.015).
DIRT is a Java applet for modelling astrophysical processes in circumstellar dust shells around young and evolved stars. With DIRT, you can:
Disc2vel derives tangential and radial velocity components in the equatorial plane of a barred stellar disc from the observed line-of-sight velocity, assuming geometry of a thin disc. The code is written in IDL, and the method assumes that the bar is close to steady state (i.e. does not evolve fast) and that both morphology and kinematics are symmetrical with respect to the major axis of the bar.
DISCO evolves orbital fluid motion in two and three dimensions, especially at high Mach number, for studying astrophysical disks. The software uses a moving-mesh approach with a dynamic cylindrical mesh that can shear azimuthally to follow the orbital motion of the gas, thus removing diffusive advection errors and permitting longer timesteps than a static grid. DISCO uses an HLLD Riemann solver and a constrained transport scheme compatible with the mesh motion to implement magnetohydrodynamics.
DiskFit implements procedures for fitting non-axisymmetries in either kinematic or photometric data. DiskFit can analyze H-alpha and CO velocity field data as well as HI kinematics to search for non-circular motions in the disk galaxies. DiskFit can also be used to constrain photometric models of the disc, bar and bulge. It deprecates an earlier version, by a subset of these authors, called velfit.
DiskJockey derives dynamical masses for T Tauri stars using the Keplerian motion of their circumstellar disks, applied to radio interferometric data from the Atacama Large Millimeter Array (ALMA) and the Submillimeter Array (SMA). The package relies on RADMC-3D (ascl:1202.015) to perform the radiative transfer of the disk model. DiskJockey is designed to work in a parallel environment where the calculations for each frequency channel can be distributed to independent processors. Due to the computationally expensive nature of the radiative synthesis, fitting sizable datasets (e.g., SMA and ALMA) will require a substantial amount of CPU cores to explore a posterior distribution in a reasonable timeframe.
DiskSim is a source-code distribution of the SPH accretion disk modeling code described in Simpson & Wood (1998) and Wood, Thomas, & Simpson (2009). The code had been released in a Windows executable form as FITDisk (Dolence, Wood & Simpson 2005; ascl:1305.011). The code released now is the full research code in Fortran, which can be modified as needed by the user.
DISKSTRUCT is a simple 1+1-D code for modeling protoplanetary disks. It is not based on multidimensional radiative transfer! Instead, a flaring-angle recipe is used to compute the irradiation of the disk, while the disk vertical structure at each cylindrical radius is computed in a 1-D fashion; the models computed with this code are therefore approximate. Moreover, this model cannot deal with the dust inner rim.
In spite of these simplifications and drawbacks, the code can still be very useful for disk studies, for the following reasons:
DISORT (DIScrete Ordinate Radiative Transfer) solves the problem of 1D scalar radiative transfer in a single optical medium, such as a planetary atmosphere. The code correctly accounts for multiple scattering by an isotropic or plane-parallel beam source, internal Planck sources, and reflection from a lower boundary. Provided that polarization effects can be neglected, DISORT efficiently calculates accurate fluxes and intensities at any user-specified angle and location within the user-specified medium.
DisPerSE is open source software for the identification of persistent topological features such as peaks, voids, walls and in particular filamentary structures within noisy sampled distributions in 2D, 3D. Using DisPerSE, structure identification can be achieved through the computation of the discrete Morse-Smale complex. The software can deal directly with noisy datasets via the concept of persistence (a measure of the robustness of topological features). Although developed for the study of the properties of filamentary structures in the cosmic web of galaxy distribution over large scales in the Universe, the present version is quite versatile and should be useful for any application where a robust structure identification is required, such as for segmentation or for studying the topology of sampled functions (for example, computing persistent Betti numbers). Currently, it can be applied can work indifferently on many kinds of cell complex (such as structured and unstructured grids, 2D manifolds embedded within a 3D space, discrete point samples using delaunay tesselation, and Healpix tesselations of the sphere). The only constraint is that the distribution must be defined over a manifold, possibly with boundaries.
DMATIS (Dark Matter ATtenuation Importance Sampling) calculates the trajectories of DM particles that propagate in the Earth's crust and the lead shield to reach the DAMIC detector using an importance sampling Monte-Carlo simulation. A detailed Monte-Carlo simulation avoids the deficiencies of the SGED/KS method that uses a mean energy loss description to calculate the lower bound on the DM-proton cross section. The code implementing the importance sampling technique makes the brute-force Monte-Carlo simulation of moderately strongly interacting DM with nucleons computationally feasible. DMATIS is written in Python 3 and MATHEMATICA.
The dmdd package enables simple simulation and Bayesian posterior analysis of recoil-event data from dark-matter direct-detection experiments under a wide variety of scattering theories. It enables calculation of the nuclear-recoil rates for a wide range of non-relativistic and relativistic scattering operators, including non-standard momentum-, velocity-, and spin-dependent rates. It also accounts for the correct nuclear response functions for each scattering operator and takes into account the natural abundances of isotopes for a variety of experimental target elements.
This code is a general Monte Carlo method based on Nested Sampling (NS) for sampling complex probability distributions and estimating the normalising constant. The method uses one or more particles, which explore a mixture of nested probability distributions, each successive distribution occupying ~e^-1 times the enclosed prior mass of the previous distribution. While NS technically requires independent generation of particles, Markov Chain Monte Carlo (MCMC) exploration fits naturally into this technique. This method can achieve four times the accuracy of classic MCMC-based Nested Sampling, for the same computational effort; equivalent to a factor of 16 speedup. An additional benefit is that more samples and a more accurate evidence value can be obtained simply by continuing the run for longer, as in standard MCMC.
DNest3 is a C++ implementation of Diffusive Nested Sampling (ascl:1010.029), a Markov Chain Monte Carlo (MCMC) algorithm for Bayesian Inference and Statistical Mechanics. Relative to older DNest versions, DNest3 has improved performance (in terms of the sampling overhead, likelihood evaluations still dominate in general) and is cleaner code: implementing new models should be easier than it was before. In addition, DNest3 is multi-threaded, so one can run multiple MCMC walkers at the same time, and the results will be combined together.
DOLPHOT is a stellar photometry package that was adapted from HSTphot for general use. It supports two modes; the first is a generic PSF-fitting package, which uses analytic PSF models and can be used for any camera. The second mode uses ACS PSFs and calibrations, and is effectively an ACS adaptation of HSTphot. A number of utility programs are also included with the DOLPHOT distribution, including basic image reduction routines.
The DAOSPEC Output Optimizer pipeline (DOOp) runs efficient and convenient equivalent widths measurements in batches of hundreds of spectra. It uses a series of BASH scripts to work as a wrapper for the FORTRAN code DAOSPEC (ascl:1011.002) and uses IRAF (ascl:9911.002) to automatically fix some of the parameters that are usually set by hand when using DAOSPEC. This allows batch-processing of quantities of spectra that would be impossible to deal with by hand. DOOp was originally built for the large quantity of UVES and GIRAFFE spectra produced by the Gaia-ESO Survey, but just like DAOSPEC, it can be used on any high resolution and high signal-to-noise ratio spectrum binned on a linear wavelength scale.
The parameters of the mutual orbit of eclipsing binaries that are physically connected can be obtained by precision timing of minima over time through light travel time effect, apsidal motion or orbital precession. This, however, requires joint analysis of data from different sources obtained through various techniques and with insufficiently quantified uncertainties. In particular, photometric uncertainties are often underestimated, which yields too small uncertainties in minima timings if determined through analysis of a χ2 surface. The task is even more difficult for double eclipsing binaries, especially those with periods close to a resonance such as CzeV344, where minima get often blended with each other.
This code solves the double binary parameters simultaneously and then uses these parameters to determine minima timings (or more specifically O-C values) for individual datasets. In both cases, the uncertainties (or more precisely confidence intervals) are determined through bootstrap resampling of the original data. This procedure to a large extent alleviates the common problem with underestimated photometric uncertainties and provides a check on possible degeneracies in the parameters and the stability of the results. While there are shortcomings to this method as well when compared to Markov Chain Monte Carlo methods, the ease of the implementation of bootstrapping is a significant advantage.
DPI is a FORTRAN77 library that supplies the symplectic mapping method for binary star systems for the Mercury N-Body software package (ascl:1201.008). The binary symplectic mapping is implemented as a hybrid symplectic method that allows close encounters and collisions between massive bodies and is therefore suitable for planetary accretion simulations.
DPPP (Default Pre-Processing Pipeline, also referred to as NDPPP) reads and writes radio-interferometric data in the form of Measurement Sets, mainly those that are created by the LOFAR telescope. It goes through visibilities in time order and contains standard operations like averaging, phase-shifting and flagging bad stations. Between the steps in a pipeline, the data is not written to disk, making this tool suitable for operations where I/O dominates. More advanced procedures such as gain calibration are also included. Other computing steps can be provided by loading a shared library; currently supported external steps are the AOFlagger (ascl:1010.017) and a bridge that enables loading python steps.
DPUSER is an interactive language capable of handling numbers (both real and complex), strings, and matrices. Its main aim is to do astronomical image analysis, for which it provides a comprehensive set of functions, but it can also be used for many other applications.
draco analyzes transit radio data with the m-mode formalism. It is telescope agnostic, and is used as part of the analysis and simulation pipeline for the CHIME (Canadian Hydrogen Intensity Mapping Experiment) telescope. It can simulate time stream data from maps of the sky (using the m-mode formalism) and add gain fluctuations and correctly correlated instrumental noise (i.e. Wishart distributed). Further, it can perform various cuts on the data and make maps of the sky from data using the m-mode formalism.
DRACULA classifies objects using dimensionality reduction and clustering. The code has an easy interface and can be applied to separate several types of objects. It is based on tools developed in scikit-learn, with some usage requiring also the H2O package.
DRAGON adopts a second-order Cranck-Nicholson scheme with Operator Splitting and time overrelaxation to solve the diffusion equation. This provides a fast solution that is accurate enough for the average user. Occasionally, users may want to have very accurate solutions to their problem. To enable this feature, users may get close to the accurate solution by using the fast method, and then switch to a more accurate solution scheme featuring the Alternating-Direction-Implicit (ADI) Cranck-Nicholson scheme.
A Monte Carlo generator of the final state of hadrons emitted from an ultrarelativistic nuclear collision is introduced. An important feature of the generator is a possible fragmentation of the fireball and emission of the hadrons from fragments. Phase space distribution of the fragments is based on the blast wave model extended to azimuthally non-symmetric fireballs. Parameters of the model can be tuned and this allows to generate final states from various kinds of fireballs. A facultative output in the OSCAR1999A format allows for a comprehensive analysis of phase-space distributions and/or use as an input for an afterburner. DRAGON's purpose is to produce artificial data sets which resemble those coming from real nuclear collisions provided fragmentation occurs at hadronisation and hadrons are emitted from fragments without any further scattering. Its name, DRAGON, stands for DRoplet and hAdron GeneratOr for Nuclear collisions. In a way, the model is similar to THERMINATOR, with the crucial difference that emission from fragments is included.
DRAMA is a fast, distributed environment for writing instrumentation control systems. It allows low level instrumentation software to be controlled from user interfaces running on UNIX, MS Windows or VMS machines in a consistent manner. Such instrumentation tasks can run either on these machines or on real time systems such as VxWorks. DRAMA uses techniques developed by the AAO while using the Starlink-ADAM environment, but is optimized for the requirements of instrumentation control, portability, embedded systems and speed. A special program is provided which allows seamless communication between ADAM and DRAMA tasks.
drive-casa provides a Python interface for scripting of CASA (ascl:1107.013) subroutines from a separate Python process, allowing for utilization alongside other Python packages which may not easily be installed into the CASA environment. This is particularly useful for embedding use of CASA subroutines within a larger pipeline. drive-casa runs plain-text casapy scripts directly; alternatively, the package includes a set of convenience routines which try to adhere to a consistent style and make it easy to chain together successive CASA reduction commands to generate a command-script programmatically.
DrizzlePac allows users to easily and accurately align and combine HST images taken at multiple epochs, and even with different instruments. It is a suite of supporting tasks for AstroDrizzle which includes:
Deprojection of X-ray data by methods such as PROJCT, which are model dependent, can produce large and unphysical oscillating temperature profiles. Direct Spectral Deprojection (DSDEPROJ) solves some of the issues inherent to model-dependent deprojection routines. DSDEPROJ is a model-independent approach, assuming only spherical symmetry, which subtracts projected spectra from each successive annulus to produce a set of deprojected spectra.
DSPSR, written primarily in C++, is an open-source, object-oriented, digital signal processing software library and application suite for use in radio pulsar astronomy. The library implements an extensive range of modular algorithms for use in coherent dedispersion, filterbank formation, pulse folding, and other tasks. The software is installed and compiled using the standard GNU configure and make system, and is able to read astronomical data in 18 different file formats, including FITS, S2, CPSR, CPSR2, PuMa, PuMa2, WAPP, ASP, and Mark5.
Dst is a fully parallel Python destriping code for polarimeter data; destriping is a well-established technique for removing low-frequency correlated noise from Cosmic Microwave Background (CMB) survey data. The software destripes correctly formatted HDF5 datasets and outputs hitmaps, binned maps, destriped maps and baseline arrays.
dStar is a collection of modules for computing neutron star structure and evolution, and uses the numerical, utility, and equation of state libraries of MESA (ascl:1010.083).
Duchamp is software designed to find and describe sources in 3-dimensional, spectral-line data cubes. Duchamp has been developed with HI (neutral hydrogen) observations in mind, but is widely applicable to many types of astronomical images. It features efficient source detection and handling methods, noise suppression via smoothing or multi-resolution wavelet reconstruction, and a range of graphical and text-based outputs to allow the user to understand the detections.
Duo computes rotational, rovibrational and rovibronic spectra of diatomic molecules. The software, written in Fortran 2003, solves the Schrödinger equation for the motion of the nuclei for the simple case of uncoupled, isolated electronic states and also for the general case of an arbitrary number and type of couplings between electronic states. Possible couplings include spin–orbit, angular momenta, spin-rotational and spin–spin. Introducing the relevant couplings using so-called Born–Oppenheimer breakdown curves can correct non-adiabatic effects.
Written in Python, dust calculates X-ray dust scattering and extinction in the intergalactic and local interstellar media.
DustEM computes the extinction and the emission of interstellar dust grains heated by photons. It is written in Fortran 95 and is jointly developed by IAS and CESR. The dust emission is calculated in the optically thin limit (no radiative transfer) and the default spectral range is 40 to 108 nm. The code is designed so dust properties can easily be changed and mixed and to allow for the inclusion of new grain physics.
DUSTY solves the problem of radiation transport in a dusty environment. The code can handle both spherical and planar geometries. The user specifies the properties of the radiation source and dusty region, and the code calculates the dust temperature distribution and the radiation field in it. The solution method is based on a self-consistent equation for the radiative energy density, including dust scattering, absorption and emission, and does not introduce any approximations. The solution is exact to within the specified numerical accuracy. DUSTY has built in optical properties for the most common types of astronomical dust and comes with a library for many other grains. It supports various analytical forms for the density distribution, and can perform a full dynamical calculation for radiatively driven winds around AGB stars. The spectral energy distribution of the source can be specified analytically as either Planckian or broken power-law. In addition, arbitrary dust optical properties, density distributions and external radiation can be entered in user supplied files. Furthermore, the wavelength grid can be modified to accommodate spectral features. A single DUSTY run can process an unlimited number of models, with each input set producing a run of optical depths, as specified. The user controls the detail level of the output, which can include both spectral and imaging properties as well as other quantities of interest.
Written in Fortran, DUSTYWAVE computes the exact solution for linear waves in a two-fluid mixture of gas and dust. The solutions are general with respect to both the dust-to-gas ratio and the amplitude of the drag coefficient.
dynesty is a Dynamic Nested Sampling package for estimating Bayesian posteriors and evidences. dynesty samples from a given distribution when provided with a loglikelihood function, a prior_transform function (that transforms samples from the unit cube to the target prior), and the dimensionality of the parameter space.
Written in Python and utilizing ParselTongue (ascl:1208.020) to interface with AIPS (ascl:9911.003), the e-MERLIN data reduction pipeline processes, calibrates and images data from the UK's radio interferometric array (Multi-Element Remote-Linked Interferometer Network). Driven by a plain text input file, the pipeline is modular and can be run in stages. The software includes options to load raw data, average in time and/or frequency, flag known sources of interference, flag more comprehensively with SERPent (ascl:1312.001), carry out some or all of the calibration procedures (including self-calibration), and image in either normal or wide-field mode. It also optionally produces a number of useful diagnostic plots at various stages so data quality can be assessed.
E3D is a package of tools for the analysis and visualization of IFS data. It is capable of reading, writing, and visualizing reduced data from 3D spectrographs of any kind.
EARL (Exoplanet Analytic Reflected Lightcurves) computes the analytic form of a reflected lightcurve, given a spherical harmonic decomposition of the planet albedo map and the viewing and orbital geometries. The EARL Mathematica notebook allows rapid computation of reflected lightcurves, thus making lightcurve numerical experiments accessible.
EarthShadow calculates the impact of Earth-scattering on the distribution of Dark Matter (DM) particles. The code calculates the speed and velocity distributions of DM at various positions on the Earth and also helps with the calculation of the average scattering probabilities. Tabulated data for DM-nuclear scattering cross sections and various numerical results, plots and animations are also included in the code package.
Terrestrial albedo can be determined from observations of the relative intensity of earthshine. Images of the Moon at different lunar phases can be analyzed to derive the semi-hemispheric mean albedo of the Earth, and an important tool for doing this is simulations of the appearance of the Moon for any time. This software produces idealized images of the Moon for arbitrary times. It takes into account the libration of the Moon and the distances between Sun, Moon and the Earth, as well as the relevant geometry. The images of the Moon are produced as FITS files. User input includes setting the Julian Day of the simulation. Defaults for image size and field of view are set to produce approximately 1x1 degree images with the Moon in the middle from an observatory on Earth, currently set to Mauna Loa.
The possibility that we live in a special place in the universe, close to the centre of a large void, seems an appealing alternative to the prevailing interpretation of the acceleration of the universe in terms of a LCDM model with a dominant dark energy component. In this paper we confront the asymptotically flat Lemaitre-Tolman-Bondi (LTB) models with a series of observations, from Type Ia Supernovae to Cosmic Microwave Background and Baryon Acoustic Oscillations data. We propose two concrete LTB models describing a local void in which the only arbitrary functions are the radial dependence of the matter density Omega_M and the Hubble expansion rate H. We find that all observations can be accommodated within 1 sigma, for our models with 4 or 5 independent parameters. The best fit models have a chi^2 very close to that of the LCDM model. We perform a simple Bayesian analysis and show that one cannot exclude the hypothesis that we live within a large local void of an otherwise Einstein-de Sitter model.
EAZY, Easy and Accurate Zphot from Yale, determines photometric redshifts. The program is optimized for cases where spectroscopic redshifts are not available, or only available for a biased subset of the galaxies. The code combines features from various existing codes: it can fit linear combinations of templates, it includes optional flux- and redshift-based priors, and its user interface is modeled on the popular HYPERZ (ascl:1108.010) code. The default template set, as well as the default functional forms of the priors, are not based on (usually highly biased) spectroscopic samples, but on semi-analytical models. Furthermore, template mismatch is addressed by a novel rest-frame template error function. This function gives different wavelength regions different weights, and ensures that the formal redshift uncertainties are realistic. A redshift quality parameter, Q_z, provides a robust estimate of the reliability of the photometric redshift estimate.
Observational and theoretical evidence suggests that coronal heating is impulsive and occurs on very small cross-field spatial scales. A single coronal loop could contain a hundred or more individual strands that are heated quasi-independently by nanoflares. It is therefore an enormous undertaking to model an entire active region or the global corona. Three-dimensional MHD codes have inadequate spatial resolution, and 1D hydro codes are too slow to simulate the many thousands of elemental strands that must be treated in a reasonable representation. Fortunately, thermal conduction and flows tend to smooth out plasma gradients along the magnetic field, so "0D models" are an acceptable alternative. We have developed a highly efficient model called Enthalpy-Based Thermal Evolution of Loops (EBTEL) that accurately describes the evolution of the average temperature, pressure, and density along a coronal strand. It improves significantly upon earlier models of this type--in accuracy, flexibility, and capability. It treats both slowly varying and highly impulsive coronal heating; it provides the differential emission measure distribution, DEM(T), at the transition region footpoints; and there are options for heat flux saturation and nonthermal electron beam heating. EBTEL gives excellent agreement with far more sophisticated 1D hydro simulations despite using four orders of magnitude less computing time. It promises to be a powerful new tool for solar and stellar studies.
ECCSAMPLES solves the inverse cumulative density function (CDF) of a Beta distribution, sometimes called the IDF or inverse transform sampling. This allows one to sample from the relevant priors directly. ECCSAMPLES actually provides joint samples for both the eccentricity and the argument of periastron, since for transiting systems they display non-zero covariance.
Echelle++ simulates realistic raw spectra based on the Zemax model of any spectrograph, with a particular emphasis on cross-dispersed Echelle spectrographs.
Echelle++ generates realistic spectra of astronomical and calibration sources, with accurate representation of optical aberrations, the shape of the point spread function, detector characteristics, and photon noise. It produces high-fidelity spectra fast, a very important feature when testing data reduction pipelines with a large set of different input spectra, when making critical choices about order spacing in the design phase of the instrument, or while aligning the spectrograph during construction. Echelle++ also works with low resolution, low signal to noise, multi-object, IFU, or long slit spectra, for simulating a wide array of spectrographs. We chose to initially generate our own spectrograph model from the optical prescription in Zemax. Echelle++ can then be used independently, without access to commercial raytracing software.
ECHOMOP extracts spectra from 2-D data frames. These data can be single-order spectra or multi-order echelle spectra. A substantial degree of automation is provided, particularly in the traditionally manual functions for cosmic-ray detection and wavelength calibration; manual overrides are available. Features include robust and flexible order tracing, optimal extraction, support for variance arrays, and 2-D distortion fitting and extraction. ECHOMOP is distributed as part of the Starlink software collection (ascl:1110.012).
Written in ANSI C, eclipse is a library offering numerous services related to astronomical image processing: FITS data access, various image and cube loading methods, binary image handling and filtering (including convolution and morphological filters), 2-D cross-correlation, connected components, cube and image arithmetic, dead pixel detection and correction, object detection, data extraction, flat-fielding with robust fit, image generation, statistics, photometry, image-space resampling, image combination, and cube stacking. It also contains support for mathematical tools like random number generation, FFT, curve fitting, matrices, fast median computation, and point-pattern matching. The main feature of this library is its ability to handle large amounts of input data (up to 2GB in the current version) regardless of the amount of memory and swap available on the local machine. Another feature is the very high speed allowed by optimized C, making it an ideal base tool for programming efficient number-crunching applications, e.g., on parallel (Beowulf) systems.
The Electronography Data Reduction System (EDRS) reduces and analyzes large format astronomical images and was written to be used from within ASPIC (ascl:1510.006). In its original form it specialized in the reduction of electronographic data but was built around a set of utility programs which were widely applicable to astronomical images from other sources. The programs align and calibrate images, handle lists of (X,Y) positions, apply linear geometrical transformations and do some stellar photometry. This package is now obsolete.
EDRSX extends the Electronography Data Reduction System (EDRS, ascl:1512.0030). It makes more versatile analysis of IRAS images than was otherwise available possible. EDRSX provides facilities for converting images into and out of EDRS format, accesses RA and DEC information stored with IRAS images, and performs several standard image processing operations such as displaying image histograms and statistics, and Fourier transforms. This enables such operations to be performed as estimation and subtraction of non-linear backgrounds, de-striping of IRAS images, modelling of image features, and easy aligning of separate images, among others.
The Empirical Galaxy Generator (EGG) generates fake galaxy catalogs and images with realistic positions, morphologies and fluxes from the far-ultraviolet to the far-infrared. The catalogs are generated by egg-gencat and stored in binary FITS tables (column oriented). Another program, egg-2skymaker, is used to convert the generated catalog into ASCII tables suitable for ingestion by SkyMaker (ascl:1010.066) to produce realistic high resolution images (e.g., Hubble-like), while egg-gennoise and egg-genmap can be used to generate the low resolution images (e.g., Herschel-like). These tools can be used to test source extraction codes, or to evaluate the reliability of any map-based science (stacking, dropout identification, etc.).
The Einstein Toolkit is a collection of software components and tools for simulating and analyzing general relativistic astrophysical systems. Such systems include gravitational wave space-times, collisions of compact objects such as black holes or neutron stars, accretion onto compact objects, core collapse supernovae and Gamma-Ray Bursts.
The Einstein Toolkit builds on numerous software efforts in the numerical relativity community including CactusEinstein, Whisky, and Carpet. The Einstein Toolkit currently uses the Cactus Framework as the underlying computational infrastructure that provides large-scale parallelization, general computational components, and a model for collaborative, portable code development.
ellc analyzes the light curves of detached eclipsing binary stars and transiting exoplanet systems. The model represents stars as triaxial ellipsoids, and the apparent flux from the binary is calculated using Gauss-Legendre integration over the ellipses that are the projection of these ellipsoids on the sky. The code can also calculate the fluxweighted radial velocity of the stars during an eclipse (Rossiter-McLaghlin effect). ellc can model a wide range of eclipsing binary stars and extrasolar planetary systems, and can enable the use of modern Monte Carlo methods for data analysis and model testing.
A Monte Carlo program for the simulation of electromagnetic cascades initiated by high-energy photons and electrons interacting with extragalactic background light (EBL) is presented. Pair production and inverse Compton scattering on EBL photons as well as synchrotron losses and deflections of the charged component in extragalactic magnetic fields (EGMF) are included in the simulation. Weighted sampling of the cascade development is applied to reduce the number of secondary particles and to speed up computations. As final result, the simulation procedure provides the energy, the observation angle, and the time delay of secondary cascade particles at the present epoch. Possible applications are the study of TeV blazars and the influence of the EGMF on their spectra or the calculation of the contribution from ultrahigh energy cosmic rays or dark matter to the diffuse extragalactic gamma-ray background. As an illustration, we present results for deflections and time-delays relevant for the derivation of limits on the EGMF.
The star cluster evolution code Evolve Me A Cluster of StarS (EMACSS) is a simple yet physically motivated computational model that describes the evolution of some fundamental properties of star clusters in static tidal fields. The prescription is based upon the flow of energy within the cluster, which is a constant fraction of the total energy per half-mass relaxation time. According to Henon's predictions, this flow is independent of the precise mechanisms for energy production within the core, and therefore does not require a complete description of the many-body interactions therein. Dynamical theory and analytic descriptions of escape mechanisms is used to construct a series of coupled differential equations expressing the time evolution of cluster mass and radius for a cluster of equal-mass stars. These equations are numerically solved using a fourth-order Runge-Kutta integration kernel; the results were benchmarked against a data base of direct N-body simulations. EMACSS is publicly available and reproduces the N-body results to within ~10 per cent accuracy for the entire post-collapse evolution of star clusters.
emcee is an extensible, pure-Python implementation of Goodman & Weare's Affine Invariant Markov chain Monte Carlo (MCMC) Ensemble sampler. It's designed for Bayesian parameter estimation. The algorithm behind emcee has several advantages over traditional MCMC sampling methods and has excellent performance as measured by the autocorrelation time (or function calls per independent sample). One advantage of the algorithm is that it requires hand-tuning of only 1 or 2 parameters compared to $sim N^2$ for a traditional algorithm in an N-dimensional parameter space. Exploiting the parallelism of the ensemble method, emcee permits any user to take advantage of multiple CPU cores without extra effort.
The determination of the EM gain of the CCD is best done by fitting the histogram of many low-light frames. Typically, the dark+CIC noise of a 30ms frame itself is a sufficient amount of signal to determine accurately the EM gain with about 200 512x512 frames. The IDL code emGain takes as an input a cube of frames and fit the histogram of all the pixels with the EM stage output probability function. The function returns the EM gain of the frames as well as the read-out noise and the mean signal level of the frames.
empiriciSN generates realistic supernova parameters given photometric observations of a potential host galaxy, based entirely on empirical correlations measured from supernova datasets. It is intended to be used to improve supernova simulation for DES and LSST. It is extendable such that additional datasets may be added in the future to improve the fitting algorithm or so that additional light curve parameters or supernova types may be fit.
Emu CMB is a fast emulator the CMB temperature power spectrum based on CAMB (Jan 2010 version). Emu CMB is based on a "space-filling" Orthogonal Array Latin Hypercube design in a de-correlated parameter space obtained by using a fiducial WMAP5 CMB Fisher matrix as a rotation matrix. This design strategy allows for accurate interpolation with small numbers of simulation design points. The emulator presented here is calibrated with 100 CAMB runs that are interpolated over the design space using a global quadratic polynomial fit.
We present a method to numerically estimate the densities of a discretely sampled data based on a binary space partitioning tree. We start with a root node containing all the particles and then recursively divide each node into two nodes each containing roughly equal number of particles, until each of the nodes contains only one particle. The volume of such a leaf node provides an estimate of the local density and its shape provides an estimate of the variance. We implement an entropy-based node splitting criterion that results in a significant improvement in the estimation of densities compared to earlier work. The method is completely metric free and can be applied to arbitrary number of dimensions. We use this method to determine the appropriate metric at each point in space and then use kernel-based methods for calculating the density. The kernel-smoothed estimates were found to be more accurate and have lower dispersion. We apply this method to determine the phase-space densities of dark matter haloes obtained from cosmological N-body simulations. We find that contrary to earlier studies, the volume distribution function v(f) of phase-space density f does not have a constant slope but rather a small hump at high phase-space densities. We demonstrate that a model in which a halo is made up by a superposition of Hernquist spheres is not capable in explaining the shape of v(f) versus f relation, whereas a model which takes into account the contribution of the main halo separately roughly reproduces the behaviour as seen in simulations. The use of the presented method is not limited to calculation of phase-space densities, but can be used as a general purpose data-mining tool and due to its speed and accuracy it is ideally suited for analysis of large multidimensional data sets.
Encube is a qualitative, quantitative and comparative visualization and analysis framework, with application to high-resolution, immersive three-dimensional environments and desktop displays, providing a capable visual analytics experience across the display ecology. Encube includes mechanisms for the support of: 1) interactive visual analytics of sufficiently large subsets of data; 2) synchronous and asynchronous collaboration; and 3) documentation of the discovery workflow. The framework is modular, allowing additional functionalities to be included as required.
Enrico analyzes Fermi data. It produces spectra (model fit and flux points), maps and lightcurves for a target by editing a config file and running a python script which executes the Fermi science tool chain.
Enzo is an adaptive mesh refinement (AMR), grid-based hybrid code (hydro + N-Body) which is designed to do simulations of cosmological structure formation. It uses the algorithms of Berger & Collela to improve spatial and temporal resolution in regions of large gradients, such as gravitationally collapsing objects. The Enzo simulation software is incredibly flexible, and can be used to simulate a wide range of cosmological situations with the available physics packages.
Enzo has been parallelized using the MPI message-passing library and can run on any shared or distributed memory parallel supercomputer or PC cluster. Simulations using as many as 1024 processors have been successfully carried out on the San Diego Supercomputing Center's Blue Horizon, an IBM SP.
E-field Parallel Imaging Correlator (EPIC), a highly parallelized Object Oriented Python package, implements the Modular Optimal Frequency Fourier (MOFF) imaging technique. It also includes visibility-based imaging using the software holography technique and a simulator for generating electric fields from a sky model. EPIC can accept dual-polarization inputs and produce images of all four instrumental cross-polarizations.
EPICS is a set of software tools and applications developed collaboratively and used to create distributed soft real-time control systems for scientific instruments such as particle accelerators and telescopes. Such distributed control systems typically comprise tens or even hundreds of computers, networked together to allow communication between them and to provide control and feedback of the various parts of the device from a central control room, or even remotely over the internet. EPICS uses Client/Server and Publish/Subscribe techniques to communicate between the various computers. A Channel Access Gateway allows engineers and physicists elsewhere in the building to examine the current state of the IOCs, but prevents them from making unauthorized adjustments to the running system. In many cases the engineers can make a secure internet connection from home to diagnose and fix faults without having to travel to the site.
EPICS is used by many facilities worldwide, including the Advanced Photon Source at Argonne National Laboratory, Fermilab, Keck Observatory, Laboratori Nazionali di Legnaro, Brazilian Synchrotron Light Source, Los Alamos National Laboratory, Australian Synchrotron, and Stanford Linear Accellerator Center.
epsnoise simulates pixel noise in weak-lensing ellipticity and shear measurements. This open-source python code can efficiently create an intrinsic ellipticity distribution, shear it, and add noise, thereby mimicking a "perfect" measurement that is not affected by shape-measurement biases. For theoretical studies, we provide the Marsaglia distribution, which describes the ratio of normal variables in the general case of non-zero mean and correlation. We also added a convenience method that evaluates the Marsaglia distribution for the ratio of moments of a Gaussian-shaped brightness distribution, which gives a very good approximation of the measured ellipticity distribution also for galaxies with different radial profiles. We provide four shear estimators, two based on the ε ellipticity measure, two on χ. While three of them are essentially plain averages, we introduce a new estimator which requires a functional minimization.
eqpair computes the electron energy distribution resulting from a balance between heating and direct acceleration of particles, and cooling processes. Electron-positron pair balance, bremstrahlung, and Compton cooling, including external soft photon input, are among the processes considered, and the final electron distribution can be hybrid, thermal, or non-thermal.
The Fortran program EQUIB solves the statistical equilibrium equation for each ion and yields atomic level populations and line emissivities for given physical conditions, namely electron temperature and electron density, appropriate to the zones in an ionized nebula where the ions are expected to exist.
The ESO-MIDAS system provides general tools for image processing and data reduction with emphasis on astronomical applications including imaging and special reduction packages for ESO instrumentation at La Silla and the VLT at Paranal. In addition it contains applications packages for stellar and surface photometry, image sharpening and decomposition, statistics, data fitting, data presentation in graphical form, and more.
EsoRex (ESO Recipe Execution Tool) lists, configures, and executes Common Pipeline Library (CPL) (ascl:1402.010) recipes from the command line. Its features include automatically generating configuration files, recursive recipe-path searching, command line and configuration file parameters, and recipe product naming control, among many others.
ESP (Extended Surface Photometry) determines the photometric properties of galaxies and other extended objects. It has applications that detect flatfielding faults, remove cosmic rays, median filter images, determine image statistics and local background values, perform galaxy profiling, fit 2-D Gaussian profiles to galaxies, generate pie slice cross-sections of galaxies, and display profiling results. It is distributed as part of the Starlink software collection (ascl:1110.012).
The ESTER code computes the steady state of an isolated star of mass larger than two solar masses. The only convective region computed as such is the core where isentropy is assumed. ESTER provides solutions of the partial differential equations, for the pressure, density, temperature, angular velocity and meridional velocity for the whole volume. The angular velocity (differential rotation) and meridional circulation are computed consistently with the structure and are driven by the baroclinic torque. The code uses spectral methods, both radially and horizontally, with spherical harmonics and Chebyshev polynomials. The iterations follow Newton's algorithm. The code is object-oriented and is written in C++; a python suite allows an easy visualization of the results. While running, PGPLOT graphs are displayed to show evolution of the iterations.
Written for the Wide-Field Infrared Survey Telescope (WFIRST) high-latitude survey, the exposure time calculator (ETC) works in both imaging and spectroscopic modes. In addition to the standard ETC functions (e.g. background and S/N determination), the calculator integrates over the galaxy population and forecasts the density and redshift distribution of galaxy shapes usable for weak lensing (in imaging mode) and the detected emission lines (in spectroscopic mode). The program may be useful outside of WFIRST but no warranties are made regarding its suitability for general purposes. The software is available for download; IPAC maintains a web interface for those who wish to run a small number of cases without having to download the package.
ETC++ is a exposure-time calculator that considers the effect of cosmic rays, undersampling, dithering, and imperfect pixel response functions. Errors on astrometry and galaxy shape measurements can be predicted as well as photometric errors.
EVEREST (EPIC Variability Extraction and Removal for Exoplanet Science Targets) removes instrumental noise from light curves with pixel level decorrelation and Gaussian processes. The code, written in Python, generates the EVEREST catalog and offers tools for accessing and interacting with the de-trended light curves. EVEREST exploits correlations across the pixels on the CCD to remove systematics introduced by the spacecraft’s pointing error. For K2, it yields light curves with precision comparable to that of the original Kepler mission. Interaction with the EVEREST catalog catalog is available via the command line and through the Python interface. Though written for K2, EVEREST can be applied to additional surveys, such as the TESS mission, to correct for instrumental systematics and enable the detection of low signal-to-noise transiting exoplanets.
The EXtraction of COsmological Parameters software (EXCOP) is a set of C and IDL programs together with a very large database of cosmological models generated by CMBFAST that will compute likelihood functions for cosmological parameters given some CMB data. This is the software and database used in the Stompor et al. (2001) analysis of a high resoultion Maxima1 CMB anisotropy map.
EXO-NAILER (EXOplanet traNsits and rAdIal veLocity fittER) efficiently fits exoplanet transit lightcurves, radial velocities (RVs) or both. The code handles data taken with different instruments. For RVs, a different center-of-mass velocity can be fitted for each instrument to account for offsets between them; if jitter is included, a different jitter term can also fitted for each instrument. For transits, a different photometric jitter can be fitted to each instrument as can different limb-darkening coefficients and different transit depths. In addition to general options that need to be set, EXO-NAILER also requires that photometry and radial velocity options be defined for each instrument.
Exo-Transmit calculates the transmission spectrum of an exoplanet atmosphere given specified input information about the planetary and stellar radii, the planet's surface gravity, the atmospheric temperature-pressure (T-P) profile, the location (in terms of pressure) of any cloud layers, the composition of the atmosphere, and opacity data for the atoms and molecules that make up the atmosphere. The code solves the equation of radiative transfer for absorption of starlight passing through the planet's atmosphere as it transits, accounting for the oblique path of light through the planetary atmosphere along an Earth-bound observer's line of sight. The fraction of light absorbed (or blocked) by the planet plus its atmosphere is calculated as a function of wavelength to produce the wavelength-dependent transmission spectrum. Functionality is provided to simulate the presence of atmospheric aerosols in two ways: an optically thick (gray) cloud deck can be generated at a user-specified height in the atmosphere, and the nominal Rayleigh scattering can be increased by a specified factor.
exocartographer solves the exo-cartography inverse problem. This flexible forward-modeling framework, written in Python, retrieves the albedo map and spin geometry of a planet based on time-resolved photometry; it uses a Markov chain Monte Carlo method to extract albedo maps and planet spin and their uncertainties. Gaussian Processes use the data to fit for the characteristic length scale of the map and enforce smooth maps.
ExoCross generates spectra and thermodynamic properties from molecular line lists in ExoMol, HITRAN, or several other formats. The code is parallelized and also shows a high degree of vectorization; it works with line profiles such as Doppler, Lorentzian and Voigt and supports several broadening schemes. ExoCross is also capable of working with the recently proposed method of super-lines. It supports calculations of lifetimes, cooling functions, specific heats and other properties. ExoCross converts between different formats, such as HITRAN, ExoMol and Phoenix, and simulates non-LTE spectra using a simple two-temperature approach. Different electronic, vibronic or vibrational bands can be simulated separately using an efficient filtering scheme based on the quantum numbers.
ExoData is a python interface for accessing and exploring the Open Exoplanet Catalogue. It allows searching of planets (including alternate names) and easy navigation of hierarchy, parses spectral types and fills in missing parameters based on programmable specifications, and provides easy reference of planet parameters such as GJ1214b.ra, GJ1214b.T, and GJ1214b.R. It calculates values such as transit duration, can easily rescale units, and can be used as an input catalog for large scale simulation and analysis of planets.
EXOFAST is a fast, robust suite of routines written in IDL which is designed to fit exoplanetary transits and radial velocity variations simultaneously or separately, and characterize the parameter uncertainties and covariances with a Differential Evolution Markov Chain Monte Carlo method. Our code self-consistently incorporates both data sets to simultaneously derive stellar parameters along with the transit and RV parameters, resulting in consistent, but tighter constraints on an example fit of the discovery data of HAT-P-3b that is well-mixed in under two minutes on a standard desktop computer. EXOFAST has an easy-to-use online interface for several basic features of our transit and radial velocity fitting. A more robust version of EXOFAST, EXOFASTv2 (ascl:1710.003), is also available.
EXOFASTv2 improves upon EXOFAST (ascl:1207.001) for exoplanet modeling. It uses a differential evolution Markov Chain Monte Carlo code to fit an arbitrary number of transits (each with their own error scaling, normalization, TTV, and/or detrending parameters), an arbitrary number of RV sources (each with their own zero point and jitter), and an arbitrary number of planets, changing nothing but command line arguments and configuration files. The global model includes integrated isochrone and SED models to constrain the stellar properties and can accept priors on any fitted or derived quantities (e.g., parallax from Gaia). It is easily extensible to add additional effects or parameters.
ExoFit is a freely available software package for estimating orbital parameters of extra-solar planets. ExoFit can search for either one or two planets and employs a Bayesian Markov Chain Monte Carlo (MCMC) method to fit a Keplerian radial velocity curve onto the radial velocity data.
exoinformatics computes the entropy of a planetary system's size ordering using three different entropy methods: tally-scores, integral path, and change points.
ExoPlanet provides a graphical interface for the construction, evaluation and application of a machine learning model in predictive analysis. With the back-end built using the numpy and scikit-learn libraries, ExoPlanet couples fast and well tested algorithms, a UI designed over the PyQt framework, and graphs rendered using Matplotlib. This serves to provide the user with a rich interface, rapid analytics and interactive visuals.
ExoPlanet is designed to have a minimal learning curve to allow researchers to focus more on the applicative aspect of machine learning algorithms rather than their implementation details and supports both methods of learning, providing algorithms for unsupervised and supervised training, which may be done with continuous or discrete labels. The parameters of each algorithms can be adjusted to ensure the best fit for the data. Training data is read from a CSV file, and after training is complete, ExoPlanet automates the building of the visual representations for the trained model. Once training and evaluation yield satisfactory results, the model may be used to make data based predictions on a new data set.
Exoplanet determines the posterior distribution of exoplanets by use of a trans-dimensional Markov Chain Monte Carlo method within Nested Sampling. This method finds the posterior distribution in a single run rather than requiring multiple runs with trial values.
Exopop is a general hierarchical probabilistic framework for making justified inferences about the population of exoplanets. Written in python, it requires that the occurrence rate density be a smooth function of period and radius (employing a Gaussian process) and takes survey completeness and observational uncertainties into account. Exopop produces more accurate estimates of the whole population than standard procedures based on weighting by inverse detection efficiency.
ExoPriors calculates a log-likelihood penalty for an input set of transit parameters to account for observational bias (geometric and signal-to-noise ratio detection bias) of transiting exoplanets. Written in Python, the code calculates this log-likelihood penalty in one of seven user-specified cases specified with Boolean input parameters for geometric and/or SNR bias, grazing or non-grazing events, and occultation events.
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