Results 451-500 of 2256 (2217 ASCL, 39 submitted)
VOSpec is a multi-wavelength spectral analysis tool with access to spectra, theoretical models and atomic and molecular line databases registered in the VO. The standard tools of VOSpec include line and continuum fitting, redshift and reddening correction, spectral arithmetic and convolution between spectra, equivalent width and flux calculations, and a best fitting algorithm for fitting selected SEDs to a TSAP service. VOSpec offers several display modes (tree vs table) and organising functionalities according to the available metadata for each service, including distance from the observation position.
RegiStax is software for alignment/stacking/processing of images; it was released over 10 years ago and continues to be developed and improved. The current version is RegiStax 6, which supports the following formats: AVI, SER, RFL (RegiStax Framelist), BMP, JPG, TIF, and FIT. This version has a shorter and simpler processing sequence than its predecessor, and optimizing isn't necessary anymore as a new image alignment method optimizes directly. The interface of RegiStax 6 has been simplified to look more uniform in appearance and functionality, and RegiStax 6 now uses Multi-core processing, allowing the user to have up to have multiple cores(recommended to use maximally 4) working simultaneous during alignment/stacking.
The ESA/ESO/NASA FITS Liberator makes it possible to process and edit astronomical science data in the FITS format to produce stunning images of the universe. Formerly a plugin for Adobe Photoshop, the current version of FITS Liberator is a stand-alone application and no longer requires Photoshop. This image processing software makes it possible to create color images using raw observations from a range of telescopes; the FITS Liberator continues to support the FITS and PDS formats, preferred by astronomers and planetary scientists respectively, which enables data to be processed from a wide range of telescopes and planetary probes, including ESO’s Very Large Telescope, the NASA/ESA Hubble Space Telescope, NASA’s Spitzer Space Telescope, ESA’s XMM–Newton Telescope and Cassini–Huygens or Mars Reconnaissance Orbiter.
The Space Telescope Science Data Analysis System (STSDAS) is a software package for reducing and analyzing astronomical data. It is layered on top of IRAF and provides general-purpose tools for astronomical data analysis as well as routines specifically designed for HST data. In particular, STSDAS contains all the programs used for the calibration and reduction of HST data in the STScI post-observation processing pipelines.
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.
bhint is a post-Newtonian, high-precision integrator for stellar systems surrounding a super-massive black hole. The algorithm makes use of the fact that the Keplerian orbits in such a potential can be calculated directly and are only weakly perturbed. For a given average number of steps per orbit, bhint is almost a factor of 100 more accurate than the standard Hermite method.
statpl estimates the parameter of power-law distributed data and calculates goodness-of-fit tests for them. Many objects studied in astronomy follow a power-law distribution function (DF), for example the masses of stars or star clusters. Such data is often analyzed by generating a histogram and fitting a straight line to it. The parameters obtained in this way can be severely biased, and the properties of the underlying DF, such as its shape or a possible upper limit, are difficult to extract. statpl is an (effectively) bias-free estimator for the exponent and the upper limit.
Plumix is a small package for generating mass segregated star clusters. Its output can be directly used as input initial conditions for NBODY4 or NBODY6 code. Mass segregation stands as one of the most robust features of the dynamical evolution of self-gravitating star clusters. We formulate parametrized models of mass segregated star clusters in virial equilibrium. To this purpose we introduce mean inter-particle potentials for statistically described unsegregated systems and suggest a single-parameter generalization of its form which gives a mass-segregated state. Plumix is a numerical C-code generating the cluster according the algorithm given for construction of appropriate star cluster models. Their stability over several crossing-times is verified by following the evolution by means of direct N-body integration.
Catena integrates the orbits of an ensemble of stars using the chain-regularization method (Mikkola & Aarseth) with an embedded Runge-Kutta integration method of 9(8)th order (Prince & Dormand).
Libimf provides a collection of programming functions based on the general IMF-algorithm by Pflamm-Altenburg & Kroupa (2006).
mkj_libs provides a set of helper routines (vector operations, astrometry, statistical analysis of spherical data) for the main plane-fitting and analysis tools.
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.
Time Utilities are software tools that, in principal, allow one to calculate BJD to a precision of 1 μs for any target from anywhere on Earth or from any spacecraft. As the quality and quantity of astrophysical data continue to improve, the precision with which certain astrophysical events can be timed becomes limited not by the data themselves, but by the manner, standard, and uniformity with which time itself is referenced. While some areas of astronomy (most notably pulsar studies) have required absolute time stamps with precisions of considerably better than 1 minute for many decades, recently new areas have crossed into this regime. In particular, in the exoplanet community, we have found that the (typically unspecified) time standards adopted by various groups can differ by as much as a minute. Left uncorrected, this ambiguity may be mistaken for transit timing variations and bias eccentricity measurements. We recommend using BJD_TDB, the Barycentric Julian Date in the Barycentric Dynamical Time standard for any astrophysical event. The BJD_TDB is the most practical absolute time stamp for extraterrestrial phenomena, and is ultimately limited by the properties of the target system. We compile a general summary of factors that must be considered in order to achieve timing precisions ranging from 15 minutes to 1 μs, and provide software for download and online webapps for use.
ImageJ is a public domain Java image processing program inspired by NIH Image. It can display, edit, analyze, process, save and print 8-bit, 16-bit and 32-bit images. It can read many image formats including TIFF, GIF, JPEG, BMP, DICOM, FITS and "raw". It supports "stacks", a series of images that share a single window. It is multithreaded, so time-consuming operations such as image file reading can be performed in parallel with other operations.
ImageHealth (IH) is a c program that makes use of standard CFITSIO routines to examine, in an automated fashion, .FITS images with any number of extensions, find objects within those images, and determine basic parameters of those images (stellar flux, background counts, FWHM, and ellipticity, along with sky background counts) in order to provide a snapshot of the quality of those images. A variety of python wrappers have also been written to test large numbers of such images and compare the results of ImageHealth to other image analysis programs, such as SourceExtractor. Additional IH-related tools will be made available in the future.
Efforts are now focused on an implementation of IH specifically for the Dark Energy Camera; we do not envision providing support for the instrument-independent version of the code offered here though comments, questions, and feedback are welcome.
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.
HiGPUs is an implementation of the numerical integration of the classical, gravitational, N-body problem, based on a 6th order Hermite’s integration scheme with block time steps, with a direct evaluation of the particle-particle forces. The main innovation of this code is its full parallelization, exploiting both OpenMP and MPI in the use of the multicore Central Processing Units as well as either Compute Unified Device Architecture (CUDA) or OpenCL for the hosted Graphic Processing Units. We tested both performance and accuracy of the code using up to 256 GPUs in the supercomputer IBM iDataPlex DX360M3 Linux Infiniband Cluster provided by the italian supercomputing consortium CINECA, for values of N ≤ 8 millions. We were able to follow the evolution of a system of 8 million bodies for few crossing times, task previously unreached by direct summation codes.
HiGPUs is also available as part of the AMUSE project.
The Versatile Advection Code (VAC) is a freely available general hydrodynamic and magnetohydrodynamic simulation software that works in 1, 2 or 3 dimensions on Cartesian and logically Cartesian grids. VAC runs on any Unix/Linux system with a Fortran 90 (or 77) compiler and Perl interpreter. VAC can run on parallel machines using either the Message Passing Interface (MPI) library or a High Performance Fortran (HPF) compiler.
Hyperion is a three-dimensional dust continuum Monte-Carlo radiative transfer code that is designed to be as generic as possible, allowing radiative transfer to be computed through a variety of three-dimensional grids. The main part of the code is problem-independent, and only requires an arbitrary three-dimensional density structure, dust properties, the position and properties of the illuminating sources, and parameters controlling the running and output of the code. Hyperion is parallelized, and is shown to scale well to thousands of processes. Two common benchmark models for protoplanetary disks were computed, and the results are found to be in excellent agreement with those from other codes. Finally, to demonstrate the capabilities of the code, dust temperatures, SEDs, and synthetic multi-wavelength images were computed for a dynamical simulation of a low-mass star formation region.
Conventional algorithms for rejecting cosmic rays in single CCD exposures rely on the contrast between cosmic rays and their surroundings and may produce erroneous results if the point-spread function is smaller than the largest cosmic rays. This code uses a robust algorithm for cosmic-ray rejection, based on a variation of Laplacian edge detection. The algorithm identifies cosmic rays of arbitrary shapes and sizes by the sharpness of their edges and reliably discriminates between poorly sampled point sources and cosmic rays. Examples of its performance are given for spectroscopic and imaging data, including Hubble Space Telescope Wide Field Planetary Camera 2 images, in the code paper.
This code provides a method for detecting cosmic rays in single images. The algorithm is based on a simple analysis of the histogram of the image data and does not use any modeling of the picture of the object. It does not require a good signal-to-noise ratio in the image data. Identification of multiple-pixel cosmic-ray hits is realized by running the procedure for detection and replacement iteratively. The method is very effective when applied to the images with spectroscopic data, and is also very fast in comparison with other single-image algorithms found in astronomical data-processing packages. Practical implementation and examples of application are presented in the code paper.
Astropysics is a library containing a variety of utilities and algorithms for reducing, analyzing, and visualizing astronomical data. Best of all, it encourages the user to leverage the existing capabilities of Python to make this quick, easy, and as painless as cutting-edge science can even actually be. There do exist other Python packages with some of the capabilities of this project, but the goal of this project is to integrate all these tools together and make them interact in the most straightforward ways possible.
xSonify maps scientific data to acoustic sequences. Listening to data can help discover patterns in huge amounts of data. Written in Java, xSonify allows visually impaired people to examine numerical data for patterns. The data can be imported from local files or from remote databases via the Internet. Single results of measurements from spacecraft instruments can be selected by their corresponding variables in a specific time frame. The results are transformed into MIDI sequences which can be played with a selection of different instruments from a soundbank. Another software module enables xSonify to convert the sonified data into other sound formats to make it easier to archive and exchange the Sonification results with other scientists.
PyFITS provides an interface to FITS formatted files in the Python scripting language and PyRAF, the Python-based interface to IRAF. It is useful both for interactive data analysis and for writing analysis scripts in Python using FITS files as either input or output. PyFITS is a development project of the Science Software Branch at the Space Telescope Science Institute.
PyFITS has been deprecated. Please see Astropy.
The PySALT user package contains the primary reduction and analysis software tools for the SALT telescope. Currently, these tools include basic data reductions for RSS and SALTICAM in both imaging, spectroscopic, and slot modes. Basic analysis software for slot mode data is also provided. These tools are primarily written in python/PyRAF with some additional IRAF code.
PyRAF is a command language for running IRAF tasks that is based on the Python scripting language. It gives users the ability to run IRAF tasks in an environment that has all the power and flexibility of Python. PyRAF can be installed along with an existing IRAF installation; users can then choose to run either PyRAF or the IRAF CL.
The mid-infrared spectra of ultraluminous infrared galaxies (ULIRGs) contain a variety of spectral features that can be used as diagnostics to characterize the spectra. However, such diagnostics are biased by our prior prejudices on the origin of the features. Moreover, by using only part of the spectrum they do not utilize the full information content of the spectra. Blind statistical techniques such as principal component analysis (PCA) consider the whole spectrum, find correlated features and separate them out into distinct components.
This code, written in IDL, classifies principal components of IRS spectra to define a new classification scheme using 5D Gaussian mixtures modelling. The five PCs and average spectra for the four classifications to classify objects are made available with the code.
The JKTEBOP code is used to fit a model to the light curves of detached eclipsing binary stars in order to derive the radii of the stars as well as various other quantities. It is very stable and includes extensive Monte Carlo or bootstrapping error analysis algorithms. It is also excellent for transiting extrasolar planetary systems. All input and output is done by text files; JKTEBOP is written in almost-standard FORTRAN 77 using first the g77 compiler and now the ifort compiler.
wvrgcal is a command line front end to LibAIR, the atmospheric inference library for phase correction of ALMA data using water vapour radiometers, and is the user-facing application for calculating atmospheric phase correction from WVR data. wvrgcal outputs a CASA gain calibration table which can then be applied to the observed data in the usual way.
Astrometry.net is a reliable and robust system that takes as input an astronomical image and returns as output the pointing, scale, and orientation of that image (the astrometric calibration or World Coordinate System information). The system requires no first guess, and works with the information in the image pixels alone; that is, the problem is a generalization of the "lost in space" problem in which nothing—not even the image scale—is known. After robust source detection is performed in the input image, asterisms (sets of four or five stars) are geometrically hashed and compared to pre-indexed hashes to generate hypotheses about the astrometric calibration. A hypothesis is only accepted as true if it passes a Bayesian decision theory test against a null hypothesis. With indices built from the USNO-B catalog and designed for uniformity of coverage and redundancy, the success rate is >99.9% for contemporary near-ultraviolet and visual imaging survey data, with no false positives. The failure rate is consistent with the incompleteness of the USNO-B catalog; augmentation with indices built from the Two Micron All Sky Survey catalog brings the completeness to 100% with no false positives. We are using this system to generate consistent and standards-compliant meta-data for digital and digitized imaging from plate repositories, automated observatories, individual scientific investigators, and hobbyists.
The BINSYN program suite is a collection of programs for analysis of binary star systems with or without an optically thick accretion disk. BINSYN produces synthetic spectra of individual binary star components plus a synthetic spectrum of the system. If the system includes an accretion disk, BINSYN also produces a separate synthetic spectrum of the disk face and rim. A system routine convolves the synthetic spectra with filter profiles of several photometric standards to produce absolute synthetic photometry output. The package generates synthetic light curves and determines an optimized solution for system parameters.
Aperture Photometry Tool (APT) is software for astronomers and students interested in manually exploring the photometric qualities of astronomical images. It has a graphical user interface (GUI) which allows the image data associated with aperture photometry calculations for point and extended sources to be visualized and, therefore, more effectively analyzed. Mouse-clicking on a source in the displayed image draws a circular or elliptical aperture and sky annulus around the source and computes the source intensity and its uncertainty, along with several commonly used measures of the local sky background and its variability. The results are displayed and can be optionally saved to an aperture-photometry-table file and plotted on graphs in various ways using functions available in the software. APT is geared toward processing sources in a small number of images and is not suitable for bulk processing a large number of images, unlike other aperture photometry packages (e.g., SExtractor). However, APT does have a convenient source-list tool that enables calculations for a large number of detections in a given image. The source-list tool can be run either in automatic mode to generate an aperture photometry table quickly or in manual mode to permit inspection and adjustment of the calculation for each individual detection. APT displays a variety of useful graphs, including image histogram, and aperture slices, source scatter plot, sky scatter plot, sky histogram, radial profile, curve of growth, and aperture-photometry-table scatter plots and histograms. APT has functions for customizing calculations, including outlier rejection, pixel “picking” and “zapping,” and a selection of source and sky models. The radial-profile-interpolation source model, accessed via the radial-profile-plot panel, allows recovery of source intensity from pixels with missing data and can be especially beneficial in crowded fields.
PyKE is a python-based PyRAF package that can also be run as a stand-alone program within a unix-based shell without compiling against PyRAF. It is a group of tasks developed for the reduction and analysis of Kepler Simple Aperture Photometry (SAP) data of individual targets with individual characteristics. The main purposes of these tasks are to i) re-extract light curves from manually-chosen pixel apertures and ii) cotrend and/or detrend the data in order to reduce or remove systematic noise structure using methods tunable to user and target-specific requirements. PyKE is an open source project and contributions of new tasks or enhanced functionality of existing tasks by the community are welcome.
The Planck Sky Model (PSM) is a global representation of the multi-component sky at frequencies ranging from a few GHz to a few THz. It summarizes in a synthetic way as much of our present knowledge as possible of the GHz sky. PSM is a complete and versatile set of programs and data that can be used for the simulation or the prediction of sky emission in the frequency range of typical CMB experiments, and in particular of the Planck sky mission. It was originally developed as part of the activities of Planck component separation Working Group (or "Working Group 2" - WG2), and of the ADAMIS team at APC.
PSM gives users the opportunity to investigate the model in some depth: look at its parameters, visualize its predictions for all individual components in various formats, simulate sky emission compatible with a given parameter set, and observe the modeled sky with a synthetic instrument. In particular, it makes possible the simulation of sky emission maps as could be plausibly observed by Planck or other CMB experiments that can be used as inputs for the development and testing of data processing and analysis techniques.
This suite contains two packages for computing cosmological quantities on the GPU: aperture_mass, which calculates the aperture mass map for a given dataset using the filter proposed by Schirmer et al (2007) (an NFW profile with exponential cut-offs at zero and large radii), and angular_correlation, which calculates the 2-pt angular correlation function using data and a flat distribution of randomly generated galaxies. A particular estimator is chosen, but the user has the flexibility to explore other estimators.
Big MACS is a Python program that estimates an accurate photometric calibration from only an input catalog of stellar magnitudes and filter transmission functions. The user does not have to measure color terms which can be difficult to characterize. Supplied with filter transmission functions, Big MACS synthesizes an expected stellar locus for your data and then simultaneously solves for all unknown zeropoints when fitting to the instrumental locus. The code uses a spectroscopic model for the SDSS stellar locus in color-color space and filter functions to compute expected locus. The stellar locus model is corrected for Milky Way reddening. If SDSS or 2MASS photometry is available for stars in field, Big MACS can yield a highly accurate absolute calibration.
Tilted Ring Fitting Code (TiRiFiC) is a prototype computer program to construct simulated (high-resolution) astronomical spectroscopic 3d-observations (data cubes) of simple kinematical and morphological models of rotating (galactic) disks. It is possible to automatically optimize the parameterizations of constructed model disks to fit spectroscopic (3d-) observations via a χ2 minimization. TiRiFiC is currently implemented as an add-on to the Groningen Image Processing System (GIPSY) software package and attempts to provide a method to automatically fit an extended tilted-ring model directly to a data cube.
BLOBCAT is a source extraction software that utilizes the flood fill algorithm to detect and catalog blobs, or islands of pixels representing sources, in 2D astronomical images. The software is designed to process radio-wavelength images of both Stokes I intensity and linear polarization, the latter formed through the quadrature sum of Stokes Q and U intensities or as a by-product of rotation measure synthesis. BLOBCAT corrects for two systematic biases to enable the flood fill algorithm to accurately measure flux densities for Gaussian sources. BLOBCAT exhibits accurate measurement performance in total intensity and, in particular, linear polarization, and is particularly suited to the analysis of large survey data.
BASE is a novel program for the combined or separate Bayesian analysis of astrometric and radial-velocity measurements of potential exoplanet hosts and binary stars. The tool fulfills two major tasks of exoplanet science, namely the detection of exoplanets and the characterization of their orbits. BASE was developed to provide the possibility of an integrated Bayesian analysis of stellar astrometric and Doppler-spectroscopic measurements with respect to their binary or planetary companions’ signals, correctly treating the astrometric measurement uncertainties and allowing to explore the whole parameter space without the need for informative prior constraints. The tool automatically diagnoses convergence of its Markov chain Monte Carlo (MCMC) sampler to the posterior and regularly outputs status information. For orbit characterization, BASE delivers important results such as the probability densities and correlations of model parameters and derived quantities. BASE is a highly configurable command-line tool developed in Fortran 2008 and compiled with GFortran. Options can be used to control the program’s behaviour and supply information such as the stellar mass or prior information. Any option can be supplied in a configuration file and/or on the command line.
Fewbody is a numerical toolkit for simulating small-N gravitational dynamics. It is a general N-body dynamics code, although it was written for the purpose of performing scattering experiments, and therefore has several features that make it well-suited for this purpose. Fewbody uses the 8th-order Runge-Kutta Prince-Dormand integration method with 9th-order error estimate and adaptive timestep to advance the N-body system forward in time. It integrates the usual formulation of the N-body equations in configuration space, but allows for the option of global pairwise Kustaanheimo-Stiefel (K-S) regularization (Heggie 1974; Mikkola 1985). The code uses a binary tree algorithm to classify the N-body system into a set of independently bound hierarchies, and performs collisions between stars in the “sticky star” approximation. Fewbody contains a collection of command line utilities that can be used to perform individual scattering and N-body interactions, but is more generally a library of functions that can be used from within other codes.
Swarm-NG is a C++ library for the efficient direct integration of many n-body systems using highly-parallel Graphics Processing Units (GPU). Swarm-NG focuses on many few-body systems, e.g., thousands of systems with 3...15 bodies each, as is typical for the study of planetary systems; the code parallelizes the simulation, including both the numerical integration of the equations of motion and the evaluation of forces using NVIDIA's "Compute Unified Device Architecture" (CUDA) on the GPU. Swarm-NG includes optimized implementations of 4th order time-symmetrized Hermite integration and mixed variable symplectic integration as well as several sample codes for other algorithms to illustrate how non-CUDA-savvy users may themselves introduce customized integrators into the Swarm-NG framework. Applications of Swarm-NG include studying the late stages of planet formation, testing the stability of planetary systems and evaluating the goodness-of-fit between many planetary system models and observations of extrasolar planet host stars (e.g., radial velocity, astrometry, transit timing). While Swarm-NG focuses on the parallel integration of many planetary systems,the underlying integrators could be applied to a wide variety of problems that require repeatedly integrating a set of ordinary differential equations many times using different initial conditions and/or parameter values.
SolarSoft is a set of integrated software libraries, data bases, and system utilities which provide a common programming and data analysis environment for Solar Physics. The SolarSoftWare (SSW) system is built from Yohkoh, SOHO, SDAC and Astronomy libraries and draws upon contributions from many members of those projects. It is primarily an IDL based system, although some instrument teams integrate executables written in other languages. The SSW environment provides a consistent look and feel at widely distributed co-investigator institutions to facilitate data exchange and to stimulate coordinated analysis. Commonalities and overlap in solar data and analysis goals are exploited to permit application of fundamental utilities to the data from many different solar instruments. The use of common libraries, utilities, techniques and interfaces minimizes the learning curve for investigators who are analyzing new solar data sets, correlating results from multiple experiments or performing research away from their home institution.
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.
Lare3d is a Lagrangian-remap code for solving the non-linear MHD equations in three spatial dimensions.
The VARTOOLS program is a command line utility that provides tools for analyzing time series astronomical data. It implements a number of routines for calculating variability/periodicity statistics of light curves, as well as tools for modifying and filtering light curves.
APLpy (the Astronomical Plotting Library in Python) is a Python module for producing publication-quality plots of astronomical imaging data in FITS format. The module uses Matplotlib, a powerful and interactive plotting package. It is capable of creating output files in several graphical formats, including EPS, PDF, PS, PNG, and SVG. Plots can be made interactively or by using scripts, and can generate co-aligned FITS cubes to make three-color RGB images. It also offers different overlay capabilities, including contour sets, markers with customizable symbols, and coordinate grids, and a range of other useful features.
CUBEP3M is a high performance cosmological N-body code which has many utilities and extensions, including a runtime halo finder, a non-Gaussian initial conditions generator, a tuneable accuracy, and a system of unique particle identification. CUBEP3M is fast, has a memory imprint up to three times lower than other widely used N-body codes, and has been run on up to 20,000 cores, achieving close to ideal weak scaling even at this problem size. It is well suited and has already been used for a broad number of science applications that require either large samples of non-linear realizations or very large dark matter N-body simulations, including cosmological reionization, baryonic acoustic oscillations, weak lensing or non-Gaussian statistics.
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.
ParselTongue is a Python interface to classic AIPS, Obit and possibly other task-based data reduction packages. It serves as the software infrastructure for some of the ALBUS implementation. It allows you to run AIPS tasks, and access AIPS headers and extension tables from Python. There is also support for running Obit tasks and accessing data in FITS files. Full access to the visibilities in AIPS UV data is also available.
EzGal is a flexible Python program which generates observable parameters (magnitudes, colors, and mass-to-light ratios) for arbitrary input stellar population synthesis (SPS) models; it enables simple, direct comparison of different model sets so that the uncertainty introduced by choice of model set can be quantified. EzGal is also capable of generating composite stellar population models (CSPs) for arbitrary input star-formation histories and reddening laws, and can be used to interpolate between metallicities for a given model set.
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