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.
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.
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.
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 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.
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-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.
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.
We present EXOFAST, 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.
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.
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.
Exorings, written in Python, contains tools for displaying and fitting giant extrasolar planet ring systems; it uses FITS formatted data for input.
Exorings is suitable for surveying entire catalogs of transiting planet candidates for exoring candidates, providing a subset of objects worthy of more detailed light curve analysis. Moreover, it is highly suited for uncovering evidence of a population of ringed planets by comparing the radius anomaly and PR-effects in ensemble studies.
EXOSIMS generates and analyzes end-to-end simulations of space-based exoplanet imaging missions. The software is built up of interconnecting modules describing different aspects of the mission, including the observatory, optical system, and scheduler (encoding mission rules) as well as the physical universe, including the assumed distribution of exoplanets and their physical and orbital properties. Each module has a prototype implementation that is inherited by specific implementations for different missions concepts, allowing for the simulation of widely variable missions.
ExoSOFT provides orbital analysis of exoplanets and binary star systems. It fits any combination of astrometric and radial velocity data, and offers four parameter space exploration techniques, including MCMC. It is packaged with an automated set of post-processing and plotting routines to summarize results, and is suitable for performing orbital analysis during surveys with new radial velocity and direct imaging instruments.
The simple, straightforward Exotrending code detrends exoplanet transit light curves given a light curve (flux versus time) and good ephemeris (epoch of first transit and orbital period). The code has been tested with Kepler and K2 light curves and should work with any other light curve.
EXSdetect is a python implementation of an X-ray source detection algorithm which is optimally designed to detected faint extended sources and makes use of Voronoi tessellation and Friend-of-Friend technique. It is a flexible tool capable of detecting extended sources down to the lowest flux levels attainable within instrumental limitations while maintaining robust photometry, high completeness, and low contamination, regardless of source morphology. EXSdetect was developed mainly to exploit the ever-increasing wealth of archival X-ray data, but is also ideally suited to explore the scientific capabilities of future X-ray facilities, with a strong focus on investigations of distant groups and clusters of galaxies.
The program EXTINCT.FOR is a FORTRAN subroutine summarizing a three-dimensional visual Galactic extinction model, based on a number of published studies. INPUTS: Galactic latitude (degrees), Galactic longitude (degrees), and source distance (kpc). OUTPUTS (magnitudes): Extinction, extinction error, a statistical correction term, and an array containing extinction and extinction error from each subroutine. The model is useful for correcting visual magnitudes of Galactic sources (particularly in statistical models), and has been used to find Galactic extinction of extragalactic sources. The model's limited angular resolution (subroutine-dependent, but with a minimum resolution of roughly 2 degrees) is necessitated by its ability to describe three-dimensional structure.
Extinction-distances uses the number of foreground stars and a Galactic model of the stellar distribution to estimate the distance to dark clouds. It exploits the relatively narrow range of intrinsic near-infrared colors of stars to separate foreground from background stars. An advantage of this method is that the distribution of stellar colors in the Galactic model need not be precisely correct, only the number density as a function of distance from the Sun.
ExtLaw_H18 generates the extinction law between 0.8 - 2.2 microns. The law is derived using the Westerlund 1 (Wd1) main sequence (A_Ks ~ 0.6 mag) and Arches cluster field Red Clump at the Galactic Center (A_Ks ~ 2.7 mag). To derive the law a Wd1 cluster age of 5 Myr is assumed, though changing the cluster age between 4 Myr -- 7 Myr has no effect on the law. This extinction law can be applied to highly reddened stellar populations that have similar foreground material as Wd1 and the Arches RC, namely dust from the spiral arms of the Milky Way in the Galactic Plane.
Extreme-deconvolution is a general algorithm to infer a d-dimensional distribution function from a set of heterogeneous, noisy observations or samples. It is fast, flexible, and treats the data's individual uncertainties properly, to get the best description possible for the underlying distribution. It performs well over the full range of density estimation, from small data sets with only tens of samples per dimension, to large data sets with hundreds of thousands of data points.
In EyE (Enhance Your Extraction) an artificial neural network connected to pixels of a moving window (retina) is trained to associate these input stimuli to the corresponding response in one or several output image(s). The resulting filter can be loaded in SExtractor to operate complex, wildly non-linear filters on astronomical images. Typical applications of EyE include adaptive filtering, feature detection and cosmetic corrections.
EZ_Ages is an IDL code package that computes the mean, light-weighted stellar population age, [Fe/H], and abundance enhancements [Mg/Fe], [C/Fe], [N/Fe], and [Ca/Fe] for unresolved stellar populations. This is accomplished by comparing Lick index line strengths between the data and the stellar population models of Schiavon (2007), using a method described in Graves & Schiavon (2008). The algorithm uses the inversion of index-index model grids to determine ages and abundances, and exploits the sensitivities of the various Lick indices to measure Mg, C, N, and Ca enhancements over their solar abundances with respect to Fe.
EZ (Easy-Z) estimates redshifts for extragalactic objects. It compares the observed spectrum with a set of (user given) spectral templates to find out the best value for the redshift. To accomplish this task, it uses a highly configurable set of algorithms. EZ is easily extendible with new algorithms. It is implemented as a set of C programs and a number of python classes. It can be used as a standalone program, or the python classes can be directly imported by other applications.
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.
Light curves from the Kepler telescope rely on "postage stamp" cutouts of a few pixels near each of 200,000 target stars. These light curves are optimized for the detection of short-term signals like planet transits but induce systematics that overwhelm long-term variations in stellar flux. Longer-term effects can be recovered through analysis of the Full Frame Images, a set of calibration data obtained monthly during the Kepler mission. The Python package f3 analyzes the Full Frame Images to infer long-term astrophysical variations in the brightness of Kepler targets, such as magnetic activity or sunspots on slowly rotating stars.
FAC calculates various atomic radiative and collisional processes, including radiative transition rates, collisional excitation and ionization by electron impact, energy levels, photoionization, and autoionization, and their inverse processes radiative recombination and dielectronic capture. The package also includes a collisional radiative model to construct synthetic spectra for plasmas under different physical conditions.
FalconIC generates discrete particle positions, velocities, masses and pressures based on linear Boltzmann solutions that are computed by libraries such as CLASS and CAMB. FalconIC generates these initial conditions for any species included in the selection, including Baryons, Cold Dark Matter and Dark Energy fluids. Any species can be set in Eulerian (on a fixed grid) or Lagrangian (particle motion) representation, depending on the gauge and reality chosen. That is, for relativistic initial conditions in the synchronous comoving gauge, Dark Matter can only be described in an Eulerian representation. For all other choices (Relativistic in Longitudinal gauge, Newtonian with relativistic expansion rates, Newtonian without any notion of radiation), all species can be treated in all representations. The code also computes spectra. FalconIC is useful for comparative studies on initial conditions.
FAMA (Fast Automatic MOOG Analysis), written in Perl, computes the atmospheric parameters and abundances of a large number of stars using measurements of equivalent widths (EWs) automatically and independently of any subjective approach. Based on the widely-used MOOG code, it simultaneously searches for three equilibria, excitation equilibrium, ionization balance, and the relationship between logn(FeI) and the reduced EWs. FAMA also evaluates the statistical errors on individual element abundances and errors due to the uncertainties in the stellar parameters. Convergence criteria are not fixed "a priori" but instead are based on the quality of the spectra.
FAMIAS (Frequency Analysis and Mode Identification for Asteroseismology) is a package of software tools programmed in C++ for the analysis of photometric and spectroscopic time-series data. FAMIAS provides analysis tools that are required for the steps between the data reduction and the seismic modeling. Two main sets of tools are incorporated in FAMIAS. The first set permits to search for periodicities in the data using Fourier and non-linear least-squares fitting techniques. The other set permits to carry out a mode identification for the detected pulsation frequencies to determine their harmonic degree l, and azimuthal order m. FAMIAS is applicable to main-sequence pulsators hotter than the Sun. This includes Gamma Dor, Delta Sct stars, slowly pulsating B (SPB)-stars and Beta Cep stars - basically all stars for which empirical mode identification is required to successfully carry out asteroseismology.
FARGO is an efficient and simple modification of the standard transport algorithm used in explicit eulerian fixed polar grid codes, aimed at getting rid of the average azimuthal velocity when applying the Courant condition. This results in a much larger timestep than the usual procedure, and it is particularly well-suited to the description of a Keplerian disk where one is traditionally limited by the very demanding Courant condition on the fast orbital motion at the inner boundary. In this modified algorithm, the timestep is limited by the perturbed velocity and by the shear arising from the differential rotation. The speed-up resulting from the use of the FARGO algorithm is problem dependent. In the example presented in the code paper below, which shows the evolution of a Jupiter sized protoplanet embedded in a minimum mass protoplanetary nebula, the FARGO algorithm is about an order of magnitude faster than a traditional transport scheme, with a much smaller numerical diffusivity.
A successor of FARGO (ascl:1102.017), FARGO3D is a versatile HD/MHD code that runs on clusters of CPUs or GPUs, with special emphasis on protoplanetary disks. FARGO3D offers Cartesian, cylindrical or spherical geometry; 1-, 2- or 3-dimensional calculations; and orbital advection (aka FARGO) for HD and MHD calculations. As in FARGO, a simple Runge-Kutta N-body solver may be used to describe the orbital evolution of embedded point-like objects. There is no need to know CUDA; users can develop new functions in C and have them translated to CUDA automatically to run on GPUs.
The Fast Template Periodogram extends the Generalised Lomb Scargle periodogram (Zechmeister and Kurster 2009) for arbitrary (periodic) signal shapes. A template is first approximated by a truncated Fourier series of length H. The Nonequispaced Fast Fourier Transform NFFT is used to efficiently compute frequency-dependent sums. Template fitting can now be done in NlogN time, improving existing algorithms by an order of magnitude for even small datasets. The FTP can be used in conjunction with gradient descent to accelerate a non-linear model fit, or be used in place of the multi-harmonic periodogram for non-sinusoidal signals with a priori known shapes.
We place functional constraints on the shape of the inflaton potential from the cosmic microwave background through a variant of the generalized slow roll approximation that allows large amplitude, rapidly changing deviations from scale-free conditions. Employing a principal component decomposition of the source function G'~3(V'/V)^2 - 2V''/V and keeping only those measured to better than 10% results in 5 nearly independent Gaussian constraints that maybe used to test any single-field inflationary model where such deviations are expected. The first component implies < 3% variations at the 100 Mpc scale. One component shows a 95% CL preference for deviations around the 300 Mpc scale at the ~10% level but the global significance is reduced considering the 5 components examined. This deviation also requires a change in the cold dark matter density which in a flat LCDM model is disfavored by current supernova and Hubble constant data and can be tested with future polarization or high multipole temperature data. Its impact resembles a local running of the tilt from multipoles 30-800 but is only marginally consistent with a constant running beyond this range. For this analysis, we have implemented a ~40x faster WMAP7 likelihood method which we have made publicly available.
FAST-PT calculates 1-loop corrections to the matter power spectrum in cosmology. The code utilizes Fourier methods combined with analytic expressions to reduce the computation time down to scale as N log N, where N is the number of grid point in the input linear power spectrum. FAST-PT is extremely fast, enabling mode-coupling integral computations fast enough to embed in Monte Carlo Markov Chain parameter estimation.
FAST (Fitting and Assessment of Synthetic Templates) fits stellar population synthesis templates to broadband photometry and/or spectra. FAST is compatible with the photometric redshift code EAzY (ascl:1010.052) when fitting broadband photometry; it uses the photometric redshifts derived by EAzY, and the input files (for examply, photometric catalog and master filter file) are the same. FAST fits spectra in combination with broadband photometric data points or simultaneously fits two components, allowing for an AGN contribution in addition to the host galaxy light. Depending on the input parameters, FAST outputs the best-fit redshift, age, dust content, star formation timescale, metallicity, stellar mass, star formation rate (SFR), and their confidence intervals. Though some of FAST's functions overlap with those of HYPERZ (ascl:1108.010), it differs by fitting fluxes instead of magnitudes, allows the user to completely define the grid of input stellar population parameters and easily input photometric redshifts and their confidence intervals, and calculates calibrated confidence intervals for all parameters. Note that FAST is not a photometric redshift code, though it can be used as one.
The Fast Chi-Squared Algorithm is a fast, powerful technique for detecting periodicity. It was developed for analyzing variable stars, but is applicable to many of the other applications where the Fast Fourier Transforms (FFTs) or other periodograms (such as Lomb-Scargle) are currently used. The Fast Chi-squared technique takes a data set (e.g. the brightness of a star measured at many different times during a series of observations) and finds the periodic function that has the best frequency and shape (to an arbitrary number of harmonics) to fit the data. Among its advantages are:
Because of their simplicity, axisymmetric mass distributions are often used to model gravitational lenses. Since galaxies are usually observed to have elliptical light distributions, mass distributions with elliptical density contours offer more general and realistic lens models. They are difficult to use, however, since previous studies have shown that the deflection angle (and magnification) in this case can only be obtained by rather expensive numerical integrations. We present a family of lens models for which the deflection can be calculated to high relative accuracy (10-5) with a greatly reduced numerical effort, for small and large ellipticity alike. This makes it easier to use these distributions for modeling individual lenses as well as for applications requiring larger computing times, such as statistical lensing studies. FASTELL is a code to calculate quickly and accurately the lensing deflection and magnification matrix for the softened power-law elliptical mass distribution (SPEMD) lens galaxy model. The SPEMD consists of a softened power-law radial distribution with elliptical isodensity contours.
The analysis of weak lensing data requires to account for missing data such as masking out of bright stars. To date, the majority of lensing analyses uses the two point-statistics of the cosmic shear field. These can either be studied directly using the two-point correlation function, or in Fourier space, using the power spectrum. The two-point correlation function is unbiased by missing data but its direct calculation will soon become a burden with the exponential growth of astronomical data sets. The power spectrum is fast to estimate but a mask correction should be estimated. Other statistics can be used but these are strongly sensitive to missing data. The solution that is proposed by FASTLens is to properly fill-in the gaps with only NlogN operations, leading to a complete weak lensing mass map from which one can compute straight forwardly and with a very good accuracy any kind of statistics like power spectrum or bispectrum.
PSF fitting photometry allows a simultaneously fit of a PSF profile on the sources. Many routines use PSF fitting photometry, including IRAF/allstar, Strarfinder, and Convphot. These routines are in general complex to use and slow. FASTPHOT is optimized for prior extraction (the position of the sources is known) and is very fast and simple.
FAT (Fully Automated TiRiFiC) is an automated procedure that fits tilted-ring models to Hi data cubes of individual, well-resolved galaxies. The method builds on the 3D Tilted Ring Fitting Code (TiRiFiC, ascl:1208.008). FAT accurately models the kinematics and the morphologies of galaxies with an extent of eight beams across the major axis in the inclination range 20°-90° without the need for priors such as disc inclination. FAT's performance allows us to model the gas kinematics of many thousands of well-resolved galaxies, which is essential for future HI surveys, with the Square Kilometre Array and its pathfinders.
FATS facilitates and standardizes feature extraction for time series data; it quickly and efficiently calculates a compilation of many existing light curve features. Users can characterize or analyze an astronomical photometric database, though this library is not necessarily restricted to the astronomical domain and can also be applied to any kind of time series data.
FBEYE, the "Flares By-Eye" detection suite, is written in IDL and analyzes Kepler light curves and validates flares. It works on any 3-column light curve that contains time, flux, and error. The success of flare identification is highly dependent on the smoothing routine, which may not be suitable for all sources.
FCLC (Featureless Classification of Light Curves) software describes the static behavior of a light curve in a probabilistic way. Individual data points are converted to densities and consequently probability density are compared instead of features. This gives rise to an independent classification which can corroborate the usefulness of the selected features.
The spectral disentangling technique can be applied on a time series of observed spectra of a spectroscopic double-lined binary star (SB2) to determine the parameters of orbit and reconstruct the spectra of component stars, without the use of template spectra. fd3 disentangles the spectra of SB2 stars, capable also of resolving the possible third companion. It performs the separation of spectra in the Fourier space which is faster, but in several respects less versatile than the wavelength-space separation. (Wavelength-space separation is implemented in the twin code CRES.) fd3 is written in C and is designed as a command-line utility for a Unix-like operating system. fd3 is a new version of FDBinary (ascl:1705.011), which is now deprecated.
FDBinary disentangles spectra of SB2 stars. The spectral disentangling technique can be applied on a time series of observed spectra of an SB2 to determine the parameters of orbit and reconstruct the spectra of component stars, without the use of template spectra. The code is written in C and is designed as a command-line utility for a Unix-like operating system. FDBinary uses the Fourier-space approach in separation of composite spectra. This code has been replaced with the newer fd3 (ascl:1705.012).
FDIPS is a finite difference iterative potential-field solver that can generate the 3D potential magnetic field solution based on a magnetogram. It is offered as an alternative to the spherical harmonics approach, as when the number of spherical harmonics is increased, using the raw magnetogram data given on a grid that is uniform in the sine of the latitude coordinate can result in inaccurate and unreliable results, especially in the polar regions close to the Sun. FDIPS is written in Fortran 90 and uses the MPI library for parallel execution.
FDPS provides the necessary functions for efficient parallel execution of particle-based simulations as templates independent of the data structure of particles and the functional form of the interaction. It is used to develop particle-based simulation programs for large-scale distributed-memory parallel supercomputers. FDPS includes templates for domain decomposition, redistribution of particles, and gathering of particle information for interaction calculation. It uses algorithms such as Barnes-Hut tree method for long-range interactions; methods to limit the calculation to neighbor particles are used for short-range interactions. FDPS reduces the time and effort necessary to write a simple, sequential and unoptimized program of O(N^2) calculation cost, and produces compiled programs that will run efficiently on large-scale parallel supercomputers.
Bandpass shifting and the (1+z)5 surface brightness dimming (for a fixed width filter) make standard tools for the extraction of structural parameters of galaxies wavelength dependent. If only few (or one) observed high-res bands exist, this dependence has to be corrected to make unbiased statements on the evolution of structural parameters or on galaxy subsamples defined by morphology. FERENGI artificially redshifts low-redshift galaxy images to different redshifts by applying the correct cosmological corrections for size, surface brightness and bandpass shifting. A set of artificially redshifted galaxies in the range 0.1<z<1.1 using a set of ~100 SDSS low-redshift (v<7000 km s-1) images as input has been created to use as a training set of realistic images of galaxies of diverse morphologies and a large range of redshifts for the GEMS and COSMOS galaxy evolution projects. This training set allows other studies to investigate and quantify the effects of cosmological redshift on the determination of galaxy morphologies, distortions, and other galaxy properties that are potentially sensitive to resolution, surface brightness, and bandpass issues. The data sets are also available for download from the FERENGI website.
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.
FFTLog is a set of Fortran subroutines that compute the fast Fourier or Hankel (= Fourier-Bessel) transform of a periodic sequence of logarithmically spaced points. FFTLog can be regarded as a natural analogue to the standard Fast Fourier Transform (FFT), in the sense that, just as the normal FFT gives the exact (to machine precision) Fourier transform of a linearly spaced periodic sequence, so also FFTLog gives the exact Fourier or Hankel transform, of arbitrary order m, of a logarithmically spaced periodic sequence.
FFTW is a C subroutine library for computing the discrete Fourier transform (DFT) in one or more dimensions, of arbitrary input size, and of both real and complex data (as well as of even/odd data, i.e. the discrete cosine/sine transforms or DCT/DST).
Benchmarks performed on a variety of platforms show that FFTW's performance is typically superior to that of other publicly available FFT software, and is even competitive with vendor-tuned codes. In contrast to vendor-tuned codes, however, FFTW's performance is portable: the same program will perform well on most architectures without modification.
fibmeasure finds the precise locations of the centers of back-illuminated optical fibers in images. It was developed for astronomical fiber positioning feedback via machine vision cameras and is optimized for high-magnification images where fibers appear as resolvable circles. It was originally written during the design of the WEAVE pick-and-place fiber positioner for the William Herschel Telescope.
The FIBRE-pac (FMOS image-based reduction package) is an IRAF-based reduction tool for the fiber multiple-object spectrograph (FMOS) of the Subaru telescope. To reduce FMOS images, a number of special techniques are necessary because each image contains about 200 separate spectra with airglow emission lines variable in spatial and time domains, and with complicated throughput patterns for the airglow masks. In spite of these features, almost all of the reduction processes except for a few steps are carried out automatically by scripts in text format making it easy to check the commands step by step. Wavelength- and flux-calibrated images together with their noise maps are obtained using this reduction package.
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