Results 2501-2600 of 3361 (3279 ASCL, 82 submitted)
RandomQuintessence integrates the Klein-Gordon and Friedmann equations for quintessence models with random initial conditions and functional forms for the potential. Quintessence models generically impose non-trivial structure on observables like the equation of state of dark energy. There are three main modules; montecarlo_nompi.py sets initial conditions, loops over a bunch of randomly-initialised models, integrates the equations, and then analyses and saves the resulting solutions for each model. Models are defined in potentials.py; each model corresponds to an object that defines the functional form of the potential, various model parameters, and functions to randomly draw those parameters. All of the equation-solving code and methods to analyze the solution are kept in solve.py under the base class DEModel(). Other files available analyze and plot the data in a variety of ways.
RAPID (Real-time Automated Photometric IDentification) classifies multiband photometric light curves into several different transient classes. It uses a deep recurrent neural network to produce time-varying classifications, and because it does not rely on deriving computationally expensive features from the data, it is well suited for processing alerts that wide-field surveys such as the Zwicky Transient Facility (ZTF) and the Large Synoptic Survey Telescope (LSST) will produce.
RAPOC (Rosseland and Planck Opacity Converter) uses molecular absorption measurements (i.e., wavelength-dependent opacities) for a given temperature, pressure, and wavelength range to calculate Rosseland and Planck mean opacities for use in atmospheric modeling. The code interpolates between discrete data points and can use ExoMol and DACE data, or any user-defined data provided in a readable format. RAPOC is simple, straightforward, and easily incorporated into other codes.
RAPP is a robust automated photometry pipeline for blurred images. RAPP requires that the observed images contain at least three stars and applies bias, dark, and flat field correction on blurred observational raw data; it also uses the median of adjacent pixels to eliminate outliers. It also uses star enhancement and robust image matching, extracts stars, and performs aperture photometry to extract information from blurred images.
Rapster (RAPid cluSTER evolution) models binary black hole population synthesis and the evolution of star clusters based on simple, yet realistic prescriptions. The code can generate large populations of dynamically formed binary black holes. Rapster uses SEVN (ascl:2206.019) to model the initial black hole mass spectrum and PRECESSION (ascl:1611.004) to model the mass, spin, and gravitational recoil of merger remnants.
RAPTOR produces accurate images, animations, and spectra of relativistic plasmas in strong gravity by numerically integrating the equations of motion of light rays and performing time-dependent radiative transfer calculations along the rays. The code is compatible with any analytical or numerical spacetime, is hardware-agnostic and may be compiled and run on both GPUs and CPUs. RAPTOR is useful for studying accretion models of supermassive black holes, performing time-dependent radiative transfer through general relativistic magneto-hydrodynamical (GRMHD) simulations and investigating the expected observational differences between the so-called fastlight and slow-light paradigms.
RascalC quickly estimates covariance matrices from two- or three-point galaxy correlation functions. Given an input set of random particle locations and a two-point correlation function (or input set of galaxy positions), RascalC produces an estimate of the associated covariance for a given binning strategy, with non-Gaussianities approximated by a ‘shot-noise-rescaling’ parameter. For the 2PCF, the rescaling parameter can be calibrated by dividing the particles into jackknife regions and comparing sample to theoretical jackknife covariance. RascalC can also be used to compute Legendre-binned covariances and cross-covariances between different two-point correlation functions.
The massively parallel code RASCAS (RAdiative SCattering in Astrophysical Simulations) performs radiative transfer on an adaptive mesh with an octree structure using the Monte Carlo technique. The code features full MPI parallelization, domain decomposition, adaptive load-balancing, and a standard peeling algorithm to construct mock observations. The radiative transport of resonant line photons through different mixes of species (e.g. HI, SiII, MgII, FeII), including their interaction with dust, is implemented in a modular fashion to allow new transitions to be easily added to the code. RASCAS may also be used to propagate photons at any wavelength (e.g. stellar continuum or fluorescent lines), and has been designed to be easily customizable and to process simulations of arbitrarily large sizes on large supercomputers.
RASSINE normalizes merged 1D spectra using the concept of convex hulls. The code uses six parameters that can be fine-tuned, and provides an interactive interface, including graphical feedback, for easily choosing the parameters. RASSINE can also provide a first guess for the parameters that are derived directly from the merged 1D spectrum based on previously performed calibrations.
rate computes thermochemical-equilibrium abundances for a H-C-N-O system with known pressure, temperature, and elemental abundances. The output abundances are H2O, CH4, CO, CO2, NH3, C2H2, C2H4, HCN, and N2, H2, H, and He.
RATRAN is a numerical method and computer code to calculate the radiative transfer and excitation of molecular lines. The approach is based on the Monte Carlo method, and incorporates elements from Accelerated Lambda Iteration. It combines the flexibility of the former with the speed and accuracy of the latter. Convergence problems known to plague Monte Carlo methods at large optical depth (>100) are avoided by separating local contributions to the radiation field from the overall transfer problem. The random nature of the Monte Carlo method serves to verify the independence of the solution to the angular, spatial, and frequency sampling of the radiation field. This allows the method to be used in a wide variety of astrophysical problems without specific adaptations. Moreover, the code can be applied to all atoms or molecules for which collisional rate coefficients are available and any axially symmetric source model. Continuum emission and absorption by dust is explicitly taken into account but scattering is neglected. We expect this program to be an important tool in analyzing data from present and future infrared and (sub-)millimeter telescopes.
Time-distance helioseismology aims to measure and interpret the travel times of waves propagating between two points located on the solar surface. The travel times are then inverted to infer sub-surface properties that are encoded in the measurements. The trajectory of the waves generally follows that of the infinite-frequency ray path, although they are sensitive to perturbations off of this path. Finite-frequency sensitivity kernels are thus needed to give more accurate inversion results.
Ray tracing codes calculate travel time kernels for a ray. There are three main codes which calculate the group time as a function of distance, the ray paths as well as the phase and group times along the path, and the ray kernels for the sound speed squared.
The RC3 mosaicking pipeline creates color composite images and scientifically-calibrated FITS mosaics in all SDSS imaging bands for all the RC3 galaxies that lie within the survey’s footprint and on photographic plates taken by the Digitized Palomar Observatory Sky Survey (DPOSS) for the B, R, IR bands. The pipeline uses SExtractor (ascl:1010.064) for extraction and STIFF (ascl:1110.006) to generating color images. The mosaicking program uses a recursive algorithm for positional update first to correct the positional inaccuracy inherent in the RC3 catalog, then conducts the mosaicking procedure using the Astropy (ascl:1304.002) wrapper to IPAC's Montage (ascl:1010.036) software. The program is generalized into a pipeline that can be easily extended to future survey data or other source catalogs; an online interface is available at
The Roman Coronagraph Exposure Time Calculator (Roman_Coronagraph_ETC for short) is the public version of the exposure time calculator of the Coronagraph Instrument aboard the Nancy Grace Roman Space Telescope funded by NASA. The methods used to estimate the integration times are based upon peer reviewed research articles (see Bibliography) and a collection of instrumental and modeling parameters of both the Coronagraph Instrument and the Nancy Grace Roman Space Telescope. The code is written in python. Visit https://github.com/hsergi/Roman_Coronagraph_ETC for more information.
rcosmo provides information processing, visualization, manipulation and spatial statistical analysis of Cosmic Microwave Background (CMB) radiation and other spherical data stored in or converted to HEALPix coordinates. The package has more than 100 different functions, and can perform spherical geometry, manipulate CMB and other spherical data, and visualize HEALPix data. rcosmo can also perform statistical analysis of CMB and spherical data, and transforme spherical data in cartesian and geographic coordinates into HEALPix format.
RCR provides advanced outlier rejection that is easy to use. Both sigma clipping, the simplest form of outlier rejection, and traditional Chauvenet rejection make use of non-robust quantities, the mean and standard deviation, which are sensitive to the outliers that they are being used to reject. This limits such techniques to samples with small contaminants or small contamination fractions. RCR instead first makes use of robust replacements for the mean, such as the median and the half-sample mode, and similar robust replacements for the standard deviation. RCR has been carefully calibrated and can be applied to samples with both large contaminants and large contaminant fractions (sometimes in excess of 90% contaminated).
RDGEN is a collection of routines for data handling, display, and adjusting, with a facility which helps to set up files for using with VPFIT (ascl:1408.015); it is included in the VPFIT distribution file. It is useful for setting region boundaries and initial guesses for VPFIT, for displaying the accumulated results, for examining by eye particular redshift systems and fits to them, testing that the error array is a true reflection of the rms scatter in the data, comparing spectra and generally examining and even modifying the data.
ReACT extends the Copter (ascl:1304.022) and MG-Copter packages, which calculate redshift and real space large scale structure observables for a wide class of gravity and dark energy models. Additions to Copter include spherical collapse in modified gravity, halo model power spectrum for general theories, and real and redshift space LSS 2 point statistics for modified gravity and dark energy. ReACT also includes numerical perturbation theory kernel solvers, real space bispectra in modified gravity, and a numerical perturbation theory kernel solver up to 4th order for 1-loop bispectrum.
ReadPDS reads in and visualizes data from the Planetary Data System in PDS4 format. Tools are available in Python as PDS4Viewer and in IDL as PDS4-IDL. These tools support PDS4 data, including images, spectra, and arrays and provide multiple views of the data, including summary, image, plot, and table views in addition to easy access to metadata such as structure labels and spectral characteristics.
REALMAF is a maximum-a-posteriori code to measure magnetic power spectra from Faraday rotation data. It uses a sophisticated model for the magnetic autocorrelation in real space, thus alleviating the need for simplifying assumptions in the processing. REALMAF treats the divergence relation of the magnetic field with a multiplicative factor in Fourier space, which allows modeling the magnetic autocorrelation as a spherically symmetric function.
RealSim-IFS generates survey-realistic integral-field spectroscopy (IFS) observations of galaxies from numerical simulations of galaxy formation. The tool is designed primarily to emulate current and experimental observing strategies for IFS galaxy surveys in astronomy, and can reproduce both the flux and variance propagation of real galaxy spectra to cubes. RealSim-IFS has built-in functions supporting SAMI and MaNGA IFU footprints, but supports any fiber-based IFU design, in general.
The freely available Monte Carlo code REAS for modelling radio emission from cosmic ray air showers has evolved to include the full complexity of air shower physics. REAS3 improves the calculation of the emission contributions, which was not fully consistent in earlier versions of REAS, by incorporating the missing radio emission due to the variation of the number of charged particles during the air shower evolution using an "end-point formalism". With the inclusion of these emission contributions, the structure of the simulated radio pulses changes from unipolar to bipolar, and the azimuthal emission pattern becomes nearly symmetric. Remaining asymmetries can be explained by radio emission due to the variation of the net charge excess in air showers, which is automatically taken into account in the new implementation. REAS3 constitutes the first self-consistent time-domain implementation based on single particle emission taking the full complexity of air shower physics into account, and is freely available for all interested users. REAS3 has been superseded by CoREAS (ascl:1406.003).
REBOUND is a multi-purpose N-body code which is freely available under an open-source license. It was designed for collisional dynamics such as planetary rings but can also solve the classical N-body problem. It is highly modular and can be customized easily to work on a wide variety of different problems in astrophysics and beyond.
REBOUND comes with symplectic integrators WHFast, WHFastHelio, SEI, and LEAPFROG. It supports open, periodic and shearing-sheet boundary conditions. REBOUND can use a Barnes-Hut tree to calculate both self-gravity and collisions. These modules are fully parallelized with MPI as well as OpenMP. The former makes use of a static domain decomposition and a distributed essential tree. Two new collision detection modules based on a plane-sweep algorithm are also implemented. The performance of the plane-sweep algorithm is superior to a tree code for simulations in which one dimension is much longer than the other two and in simulations which are quasi-two dimensional with less than one million particles.
REBOUNDx incorporates additional physics into REBOUND (ascl:1110.016) simulations. Users can add effects from a list of pre-implemented astrophysical forces or contribute new ones. The main code is written in C, and a Python wrapper is provided for interfacing with other libraries. The REBOUNDx source code is machine independent and a binary format to save REBOUNDx configurations interfaces with the SimulationArchive class in REBOUND, making it possible to share and reproduce results bit by bit.
RECFAST calculates the recombination of H, HeI, and HeII in the early Universe; this involves a line-by-line treatment of each atomic level. It differs in comparison to previous calculations in two major ways: firstly, the ionization fraction x_e is approximately 10% smaller for redshifts <~800, due to non-equilibrium processes in the excited states of H, and secondly, HeI recombination is much slower than previously thought, and is delayed until just before H recombines. RECFAST enables fast computation of the ionization history (and quantities such as the power spectrum of CMB anisotropies which depend on it) for arbitrary cosmologies.
Time series are commonly unevenly spaced in time make it difficult to obtain an accurate estimate of their typical red-noise spectrum. REDFIT overcomes this problem by fitting a first-order autoregressive (AR1) process directly to unevenly spaced time series. Hence, interpolation in the time domain and its inevitable bias can be avoided. The program can be used to test if peaks in the spectrum of a time series are significant against the red-noise background from an AR1 process.
The RedPipe collection of Python scripts performs optical photometric and spectroscopic data reduction. There are scripts on preprocessing, photometry, calibration, spectroscopy, analysis and plotting. The photometry and spectroscopy codes use pyraf (ascl:1207.011) and hence require an already existing installation of Image Reduction and Analysis Facility (IRAF, ascl:9911.002).
redshifts collects all unique spectroscopic redshifts from online databases such as VizieR and NED. It can perform a flexible search within a radius of a given set of (RA, DEC) coordinates and uses column names and descriptions (including UCD keywords) to identify columns containing spectroscopic redshifts or velocities. It weeds out photometric redshifts and duplicates and returns a unique list of best spectroscopic redshift measurements. redshifts can be used standalone from the terminal, and can take a number of optional command line arguments, or from Python.
REDSPEC is an IDL based reduction package designed with NIRSPEC in mind though can be used to reduce data from other spectrographs as well. REDSPEC accomplishes spatial rectification by summing an A+B pair of a calibration star to produce an image with two spectra; the image is remapped on the basis of polynomial fits to the spectral traces and calculation of gaussian centroids to define their separation, producing straight spectral traces with respect to the detector rows. The raw images are remapped onto a coordinate system with uniform intervals in spatial extent along the slit and in wavelength along the dispersion axis.
The astronomical data reduction package REDUCEME reduces and analyzes long-slit spectroscopic data. The package uses the unformatted FORTRAN raw data format, so requires FITS files be transformed to REDUCEME format; the reverse operation (from REDUCEME to FITS format) is also available. The package is a set of programs written in FORTRAN 77 and includes shell scripts (using the C shell syntax) to perform routine tasks; it can be extended by the inclusion of external programs. REDUCEME uses PGPLOT (ascl:1103.002) for line plots and images, and a subset of subroutines, called BUTTON, enables the user to communicate interactively with the image display employing graphic buttons. One advantage of using REDUCEME is that for each image an associated error image can also be processed throughout the reduction process, allowing for a careful control of the error propagation.
redvsblue measures a precise redshift given a broad redshift prior. For each emission line or the full spectrum, the software runs a coarse chi2 scan as a function of redshift, using the input PCA+broadband Legendre polynomials, and finds three local minima, and does a finer chi2 scan in each minima. It then defines the global PCA redshift (ZPCA) from the best minimum of the three; ZPCA is a redshift estimator biased toward the computation of the PCA. The redshift of the line (ZLINE) is defined from the maximum of the best-fit model of the line. ZLINE is a redshift estimator un-biased toward the velocity of the line, but can be biased with respect to the cosmological redshift. The output is a FITS file, with one HDU per redshift type.
Reflex provides an easy and flexible way to reduce VLT/VLTI science data using the ESO pipelines. It allows graphically specifying the sequence in which the data reduction steps are executed, including conditional stops, loops and conditional branches. It eases inspection of the intermediate and final data products and allows repetition of selected processing steps to optimize the data reduction. The data organization necessary to reduce the data is built into the system and is fully automatic; advanced users can plug their own modules and steps into the data reduction sequence. Reflex supports the development of data reduction workflows based on the ESO Common Pipeline Library. Reflex is based on the concept of a scientific workflow, whereby the data reduction cascade is rendered graphically and data seamlessly flow from one processing step to the next. It is distributed with a number of complete test datasets so users can immediately start experimenting and familiarize themselves with the system.
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.
RegPT computes the power spectrum in flat wCDM class models based on the RegPT treatment when provided with either of transfer function or matter power spectrum. It then gives the multiple-redshift outputs for power spectrum, and optionally provides correlation function data. The Fortran code has two major options for power spectrum calculations; -fast, which quickly computes the power spectrum at two-loop level (typically a few seconds) using the pre-computed data set of PT kernels for fiducial cosmological models, and -direct, in which the code first applies the fast method, and then follows the regularized expression for power spectrum to directly evaluate the multi-dimensional integrals. The output results are the power spectrum of direct calculation and difference of the results between fast and direct method. The code also gives the data set of PT diagrams necessary for power spectrum calculations from which the power spectrum can be constructed.
The C code ReionYuga generates the Epoch of Reionization (EoR) neutral Hydrogen (HI) field (successively the redshifted 21-cm signal) within a cosmological simulation box using semi-numerical techniques. The code is based on excursion set formalism and uses a three parameter model. It is designed to work with PMN-body (ascl:2107.003) and FoF-Halo-finder (ascl:2107.004).
RELAGN creates spectral models for the calculation of AGN SEDs, ranging from the Optical/UV (outer accretion disc) to the Hard X-ray (Innermost X-ray Corona). The code is available in two languages, Python and Fortran. The Fortran version is written to be used with the spectral fitting software XSPEC (ascl:9910.005), and is the preferred version for analyzing X-ray spectral data. The Python version provides more flexibility for modeling. Whereas the Fortran version produces only a spectrum, the Python implementation can extract the physical properties of the system (such as the physical mass accretion rate, disc size, and efficiency parameters) since these are all stored as attributes within the model. Both versions require a working installation of HEASOFT (ascl:1408.004).
RelicFast computes the scale-dependent bias induced by relics of different masses, spins, and temperatures, through spherical collapse and the peak-background split. The code determines halo bias in under a second, making it possible to include this effect for different cosmologies, and light relics, at little computational cost.
relxill self-consistently connects an angle-dependent reflection model constructed with XILLVER (http://www.srl.caltech.edu/personnel/javier/xillver/index.html) with the relativistic blurring code RELLINE (ascl:1505.021). It calculates the proper emission angle of the radiation at each point on the accretion disk and then takes the corresponding reflection spectrum into account.
reMASTERed reconstructs ensemble-averaged pseudo-$C_\ell$ to effectively exact precision, with significant improvements over traditional estimators for cases where the map and mask are correlated. The code can compute the results given an arbitrary map and mask; it can also compute the results in the ensemble average for certain types of threshold masks.
repack re-packs and compresses line-transition data for radiative-transfer calculations. It identifies the strong lines that dominate the spectrum from the large-majority of weaker lines, returning a binary line-by-line (LBL) file with the strong lines info (wavenumber, Elow, gf, and isotope ID), and an ASCII file with the combined contribution of the weaker lines compressed into a continuum extinction coefficient (in cm-1 amagat-1) as function of wavenumber and temperature.
The RePrimAnd library supports numerical simulations of general relativistic magnetohydrodynamics. It provides methods for recovering primitive variables such as pressure and velocity from the variables evolved in quasi-conservative formulations. Further, it provides a general framework for handling matter equations of state (EOS). Python bindings are automatically built together with the library, provided a Python3 installation containing the pybind11 package is detected. RePrimAnd also provides an (experimental) thorn that builds the library within an Einstein Toolkit (ascl:1102.014) environment using the ExternalLibraries mechanism.
reproject implements image reprojection (resampling) methods for astronomical images using various techniques via a uniform interface. Reprojection re-grids images from one world coordinate system to another (for example changing the pixel resolution, orientation, coordinate system). reproject works on celestial images by interpolation, as well as by finding the exact overlap between pixels on the celestial sphere. It can also reproject to/from HEALPIX projections by relying on the astropy-healpix package.
REPS (REscaled Power Spectra) provides accurate, one-percent level, numerical simulations of the initial conditions for massive neutrino cosmologies, rescaling the late-time linear power spectra to the simulation initial redshift.
RequiSim computes the Variance Weighted Overlap, which is a measure of the bias on the lensing signal from power spectrum modelling bias for any non-linear model. It assumes that the bias on the power spectrum is Gaussian with a covariance described by a user-provided knowledge matrix that describes the covariance in the bias on the power spectrum. The data from the Euclid wide-field survey are included.
RESOLVE is a Bayesian inference algorithm for image reconstruction in radio interferometry. It is optimized for extended and diffuse sources. Features include parameter-free Bayesian reconstruction of radio continuum data with a focus on extended and weak diffuse sources, reconstruction with uncertainty propagation dependent on measurement noise, and estimation of the spatial correlation structure of the radio astronomical source. RESOLVE provides full support for measurement sets and includes a simulation tool (if uv-coverage is provided).
REVOLVER reconstructs real space positions from redshift-space tracer data by subtracting RSD through FFT-based reconstruction (optional) and applies void-finding algorithms to create a catalogue of voids in these tracers. The tracers are normally galaxies from a redshift survey but could also be halos or dark matter particles from a simulation box. Two void-finding routines are provided. The first is based on ZOBOV (ascl:1304.005) and uses Voronoi tessellation of the tracer field to estimate the local density, followed by a watershed void-finding step. The second is a voxel-based method, which uses a particle-mesh interpolation to estimate the tracer density, and then uses a similar watershed algorithm. Input data files can be in FITS format, or ASCII- or NPY-formatted data arrays.
rfast ingests tables of opacities and generates synthetic spectra of worlds and retrieves real or simulated spectral observations. It can add noise, perform inverse modeling, and plot results. The tool can be applied to simulated and real observations spanning reflected-light, thermal emission, and transit transmission. Retrieval parameters can be toggled and parameters can be retrieved in log or linear space and adopt a Gaussian or flat prior.
RFCDE provides an implementation of random forests designed for conditional density estimation. It computes a kernel density estimate of y with nearest neighbor weightings defined by the location of the evaluation point x relative to the leaves in the random forest.
Residual Feature Extraction Pipeline carries out feature extraction of residual substructure within the residual images produced by popular galaxy structural-fitting routines such as GALFIT (ascl:1104.010) and GIM2D (ascl:1004.001). It extracts faint low surface brightness features by isolating flux-wise and area-wise significant contiguous pixels regions by rigorous masking routine. The code accepts the image cubes (original image, model image, residual image) and generates several data products, such as an image with extracted features, a source extraction based segmentation map, and the background sky mask and the residual extraction mask. It uses a Monte Carlo approach-based area threshold above which the extracted features are identified. The pipeline also creates a catalog entry indicating the surface brightness and its error.
rfpipe supports Python-based analysis of radio interferometric data (especially from the Very Large Array) and searches for fast radio transients. This extends on the rtpipe library (ascl:1706.002) with new approaches to parallelization, acceleration, and more portable data products. rfpipe can run in standalone mode or be in a cluster environment.
RGW is a lightweight R-language implementation of the affine-invariant Markov Chain Monte Carlo sampling method of Goodman & Weare (2010). The implementation is based on the description of the python package emcee (ascl:1303.002).
RH 1.5D performs Zeeman multi-level non-local thermodynamical equilibrium calculations with partial frequency redistribution for an arbitrary amount of chemical species. Derived from the RH code and written in C, it calculates spectra from 3D, 2D or 1D atmospheric models on a column-by-column basis (or 1.5D). It includes optimization features to speed up or improve convergence, which are particularly useful in dynamic models of chromospheres. While one should be aware of its limitations, the calculation of spectra using the 1.5D or column-by-column is a good approximation in many cases, and generally allows for faster convergence and more flexible methods of improving convergence. RH 1.5D scales well to at least tens of thousands of CPU cores.
RHOCUBE models 3D density distributions on a discrete Cartesian grid and their integrated 2D maps. It can be used for a range of applications, including modeling the electron number density in LBV shells and computing the emission measure. The RHOCUBE Python package provides several 3D density distributions, including a powerlaw shell, truncated Gaussian shell, constant-density torus, dual cones, and spiralling helical tubes, and can accept additional distributions. RHOCUBE provides convenient methods for shifts and rotations in 3D, and if necessary, an arbitrary number of density distributions can be combined into the same model cube and the integration ∫ dz performed through the joint density field.
The RHT (Rolling Hough Transform) measures linear intensity as a function of orientation in images. This machine vision algorithm works on any image-space (2D) data, and quantifies the presence of linear structure as a function of orientation. The RHT can be used to identify linear features in images, to quantify the orientation of structure in images, and to map image intensity from 2D x-y space to 3D x-y-orientation space. An option in the code allows the user to quantify intensity as a function of direction (modulo 2pi) rather than orientation (modulo pi). The RHT was first used to discover that filamentary structures in neutral hydrogen emission are aligned with the ambient magnetic field.
RICH (Racah Institute Computational Hydrodynamics) is a 2D hydrodynamic code based on Godunov's method. The code, largely based on AREPO (ascl:1909.010), acts on an unstructured moving mesh. It differs from AREPO in the interpolation and time advancement scheme as well as a novel parallelization scheme based on Voronoi tessellation. Though not universally true, in many cases a moving mesh gives better results than a static mesh: where matter moves one way and a sound wave is traveling in the other way (such that relative to the grid the wave is not moving), a static mesh gives better results than a moving mesh. RICH is designed in an object oriented, user friendly way that facilitates incorporation of new algorithms and physical processes.
RichValues transforms numeric values with uncertainties and upper/lower limits to create "rich values" that can be written in plain text documents in an easily readable format and used to propagate uncertainties automatically. Rich values can also be exported in the same formatting style as the import. The RichValues library uses a specific formatting style to represent the different kinds of rich values with plain text; it can also be used to create rich values within a script. Individual rich values can be used in, for example, tuples, lists, and dictionaries, and also in arrays and tables.
RID (Relativistic Image Doubling in water Cherenkov detectors) uses Monte Carlo simulations to find the relative fraction of charged, relativistic particles entering a HAWC-like Water Cherenkov Detector that can cause a Relativistic Image Doubling (RID) effect visible to at least one of the internal detectors. The technique is available in C++ and Fortran; RID also includes python code for the horizontal incidence of the muon inside the tank.
riptide implements the Fast Folding Algorithm (FFA) to identify periodic signals from time series data. In order to identify faint pulsars, the code provides access to a library of functions and classes for processing dedispersed radio signals. The FFA approaches the theoretical optimum for sensitivity to periodic signals regardless of pulse period and duty cycle.
RJ-plots uses a moments of inertia method to disentangle a 2D structure's elongation from its centrally over/under-density, thus providing a means for the automated and objective classification of such structures. It may be applied to any 2D pixelated image such as column density maps or moment zero maps of molecular lines. This method is a further development of J-plots (ascl:2009.007).
RJObject provides a general approach to trans-dimensional Bayesian inference problems, using trans-dimensional MCMC embedded within a Nested Sampling algorithm. This allows exploration of the posterior distribution and calculattion of the marginal likelihood (summed over N) even if the problem contains a phase transition or other difficult features such as multimodality.
RLOS (Relativistic Line Of Sight) uses hydrocode output data, such as that from PLUTO (ascl:1010.045), to create synthetic images depicting what a model relativistic astrophysical jet looks like to a stationary observer. The approximate time-delayed imaging algorithm used is implemented within existing line-of-sight code. The software has the potential to study a variety of dynamical astrophysical phenomena in collaboration with other imaging and simulation tools.
RM-CLEAN reads in dirty Q and U cubes, generates rmtf based on the frequencies given in an ASCII file, and cleans the RM spectra following the algorithm given by Brentjens (2007). The output cubes contain the clean model components and the CLEANed RM spectra. The input cubes must be reordered with mode=312, and the output cubes will have the same ordering and thus must be reordered after being written to disk. RM-CLEAN runs as a MIRIAD (ascl:1106.007) task and a Python wrapper is included with the code.
RM-Tools analyzes radio polarization data, specifically the use of Faraday rotation measure synthesis and Stokes QU model fitting. It contains routines for both single-pixel 1D polarized spectra as well as 3D polarization cubes. RM-Tools is intended to serve as a toolkit for studies of polarized radio sources and measurements of their Faraday rotation. RM-Tools is the core package for the pipelines used for the POlarized Sky Survey of the Universe's Magnetism (POSSUM) and the polarization component of the Very Large Array Sky Survey (VLASS). The package is maintained by the Canadian Initiative for Radio Astronomy Data Analysis (CIRADA; cirada.org).
RMextract calculates Ionospheric Faraday Rotation for a given epoch, location and line of sight. This Python code extracts TEC, vTEC, Earthmagnetic field and Rotation Measures from GPS and WMM data for radio interferometry observations.
Rmfit uses a forward-folding technique to obtain the best-fit parameters for a chosen model given user-selected source and background time intervals from data files containing observed count rates and a corresponding detector response matrix. rmfit displays lightcurves and spectra using a graphical interface that enables user-defined integrated or time-resolved spectral fits and binning in either time or energy. Originally developed for the analysis of BATSE Gamma-Ray Burst (GRB) spectroscopy, rmfit is a tool for the spectroscopy of transient sources; it accommodates the Fermi GBM and LAT data and Swift BAT.
RMHB is a hierarchical Bayesian code for reverberation mapping (RM) that combines results of a sparsely sampled broad line region (BLR) light curve and a large sample of active galactic nuclei (AGN) to infer properties of the sample of the AGN. The key idea of RM is to measure the time lag τ between variations in the continuum emission from the accretion disc and subsequent response of the broad line region (BLR). The measurement of τ is typically used to estimate the physical size of the BLR and is combined with other measurements to estimate the black hole mass MBH. A major difficulty with RM campaigns is the large amount of data needed to measure τ. RMHB allows a clear interpretation of a posterior distribution for hyperparameters describing the sample of AGN.
RMNest directly fits the Stokes Q and U (and V) spectra of a radio signal to measure the effects of Faraday rotation (or conversion) induced by propagation through a magnetized plasma along the line of sight. The software makes use of the Bayesian Inference Library (Bilby; ascl:1901.011) as an interface to the dynesty (ascl:1809.013) nested sampling algorithm.
This program determines stellar population parameters (e.g. age, metallicity, IMF slope,...), using as input a pair of line-strength indices, through the interpolation in SSP model predictions. Both linear and bivariate fits are computed to perform the interpolation.
ROA (Running Optimal Average) describes time series data. This model uses a Gaussian window function that moves through the data giving stronger weights to points close to the center of the Gaussian. Therefore, the width of the window function, delta, controls the flexibility of the model, with a small delta providing a very flexible model. The function also calculates the effective number of parameters, as a very flexible model will correspond to large number of parameters while a rigid model (low delta) has a low effective number of parameters. Knowing the effective number of parameters can be used to optimize the window width, e.g., using the Bayesian information criterion (BIC). An error envelope, which expands appropriately where there are gaps in the data, is also calculated for the model.
ROBAST (ROOT-based simulator for ray tracing) is a non-sequential ray-tracing simulation library developed for wide use in optical simulations of gamma-ray and cosmic-ray telescopes. The library is written in C++ and fully utilizes the geometry library of the ROOT analysis framework, and can build the complex optics geometries typically used in cosmic ray experiments and ground-based gamma-ray telescopes.
Robbie automates cataloging sources, finding variables, and identifying transients in the image domain. It works in a batch processing paradigm with a modular design so components can be swapped out or upgraded to adapt to different input data while retaining a consistent and coherent methodological approach. Robbie is based on commonly used and open software, including AegeanTools (ascl:1212.009) and STILS/TOPCAT (ascl:1101.010).
ROBOSPECT, written in C, automatically measures and deblends line equivalent widths for absorption and emission spectra. ROBOSPECT should not be used for stars with spectra in which there is no discernible continuum over large wavelength regions, nor for the most carbon-enhanced stars for which spectral synthesis would be favored. Although ROBOSPECT was designed for metal-poor stars, it is capable of fitting absorption and emission features in a variety of astronomical sources.
The DR25 Kepler Robovetter is a robotic decision-making code that dispositions each Threshold Crossing Event (TCE) from the final processing (DR 25) of the Kepler data into Planet Candidates (PCs) and False Positives (FPs). The Robovetter provides four major flags to designate each FP TCE as Not Transit-Like (NTL), a Stellar Eclipse (SS), a Centroid Offset (CO), and/or an Ephemeris Match (EM). It produces a score ranging from 0.0 to 1.0 that indicates the Robovetter's disposition confidence, where 1.0 indicates strong confidence in PC, and 0.0 indicates strong confidence in FP. Finally, the Robovetter provides comments in a text string that indicate the specific tests each FP TCE fails and provides supplemental information on all TCEs as necessary.
Roche is a visualization and analysis tool for drawing the Roche-lobe geometry of evolving binaries. Roche can be used as a standalone program reading data from the command line or from a file generated by SeBa (ascl:1201.003). Eventually Roche will be able to read data from any other binary evolution program. Roche requires Starlab (ascl:1010.076) version 4.1.1 or later and the pgplot (ascl:1103.002) libraries. Roche creates a series of images, based on the SeBa output file SeBa.data, displaying the evolutionary state of a binary.
Rockstar (Robust Overdensity Calculation using K-Space Topologically Adaptive Refinement) identifies dark matter halos, substructure, and tidal features. The approach is based on adaptive hierarchical refinement of friends-of-friends groups in six phase-space dimensions and one time dimension, which allows for robust (grid-independent, shape-independent, and noise-resilient) tracking of substructure. Our method is massively parallel (up to 10^5 CPUs) and runs on the largest current simulations (>10^10 particles) with high efficiency (10 CPU hours and 60 gigabytes of memory required per billion particles analyzed). Rockstar offers significant improvement in substructure recovery as compared to several other halo finders.
RODRIGUES (RATT Online Deconvolved Radio Image Generation Using Esoteric Software) is a web-based radio telescope simulation and reduction tool. From a technical perspective it is a web based parameterized docker container scheduler with a result set viewer.
ROGER (Reconstructing Orbits of Galaxies in Extreme Regions) predicts the dynamical properties of galaxies using the projected phase-space information. Written in R, it offers a choice of machine learning methods to classify the dynamical properties of galaxies. An interface for online use of the software is available at https://mdelosrios.shinyapps.io/roger_shiny/.
ROHSA (Regularized Optimization for Hyper-Spectral Analysis) reveals the statistical properties of interstellar gas through atomic and molecular lines. It uses a Gaussian decomposition algorithm based on a multi-resolution process from coarse to fine grid to decompose any kind of hyper-spectral observations into a sum of coherent Gaussian. Optimization is performed on the whole data cube at once to obtain a solution with spatially smooth parameters.
RoLo (Roche Lobe) calculates the radius and potential of the Roche Lobe for any specified direction, and also gives some other commonly used quantities (such as the Lagrange points). The calculator is valid for any mass ratio q between 0.01 and 100. The coordinates are spherical-polar (R, theta, phi) centered on one star (M1), with the x-axis (theta=pi/2, phi=0) pointing towards the other star (M2). The mass ratio is defined as q=M2/M1. Distances are given in units of the binary separation, a. A circular orbit is assumed.
Rosetta runs tasks for resource-intensive, interactive data analysis as software containers. The code's architecture frames user tasks as microservices – independent and self-contained units – which fully support custom and user-defined software packages, libraries and environments. These include complete remote desktop and GUI applications, common analysis environments such as the Jupyter Notebooks. Rosetta relies on Open Container Initiative containers, allowing for safe, effective and reproducible code execution. It can use a number of container engines and runtimes and seamlessly supports several workload management systems, thus enabling containerized workloads on a wide range of computing resources.
The numerical code RoSSBi3D (Rotating Systems Simulation Code for Bi-fluids) is designed for protoplanetary discs study at 2D and 3D. It is a finite volume code which is second order in time, features self-gravity (2D), and uses an exact Riemann solver to account for discontinuities. This FORTRAN 90 code solves the fully compressible inviscid Euler, continuity and energy conservation equations in polar coordinates for an ideal gas orbiting a central object. Solid particles are treated as a pressureless fluid and interact with the gas through aerodynamic forces. The code works on high performance computers thanks to the MPI standard (CPU).
The RPFITS data file format records synthesis visibility data obtained from the Australia Telescope Compact Array (ATCA) at Narrabri, NSW. It is also used for single-dish spectral line data obtained from Parkes and Mopra, including Parkes multibeam data. RPFITS superficially resembles random group FITS, but differs in important respects, making it incompatible with standard FITS software such as FITSIO (ascl:1010.001) and FTOOLS (ascl:9912.002) and, in particular, it precludes the use of fv (ascl:1205.005). The RPFITS Fortran library contains routines for reading and writing RPFITS files. A header file, RPFITS.h, is provided to facilitate usage by C and C++ applications. Also included is rpfhdr, a utility for viewing RPFITS headers (it also works for standard FITS), and rpfex for extracting selected scans from an RPFITS file.
rPICARD (Radboud PIpeline for the Calibration of high Angular Resolution Data) reduces data from different VLBI arrays, including high-frequency and low-sensitivity arrays, and supports continuum, polarization, and phase-referencing observations. Built on the CASA (ascl:1107.013) framework, it uses CASA for CLEAN imaging and self-calibration, and can be run non-interactively after only a few non-default input parameters are set. rPICARD delivers high-quality calibrated data and large bandwidth data can be processed within reasonable computing times.
RPPPS (Re-analysing Pipeline for Parkes Pulsar Survey) uses Linux shell scripts, C language, and python code and two parallel strategies to reorganize the PRESTO (ascl:1107.017) pulsar search pipeline to run multiple processes in parallel, thus accelerating the search for pulsars. Though originally designed for reprocessing PMPS data, the code has also been successfully used with FAST (Five-hundred-meter Aperture Spherical radio Telescope) drift scan data. The pipeline is only CPU-based and can be easily and quickly deployed in computing nodes for testing purposes or data processes.
RRATtrap is a single-pulse sifting algorithm to identify Rotating Radio Transients (RRATs) and transients using output from the PRESTO (ascl:1107.017) routine single_pulse_search.py. It can be integrated into pulsar survey data analysis pipelines and, in addition to finding RRATs, it can also identify Fast Radio Bursts.
Redshift Search Graphs provides a fast and reliable way to test redshifts found from sub-mm redshift searches. The scripts can graphically test the robustness of a spectroscopic redshift of a galaxy, test the efficiency of an instrument towards spectroscopic redshift searches, and optimize observations of tunable institutes (such as ALMA) for upcoming redshift searches.
rsigma calculates the resonant disturbing function, R(sigma), for a massless particle in an arbitrary orbit perturbed by a planet in circular orbit. This function defines the strength of the resonance (its semi-amplitude) and the location of the stable equilibrium points (the minima). It depends on the variable sigma called critical angle and on the particle's orbital elements a, e, i and the argument of the perihelion. R(sigma) is numerically calculated and the code is valid for arbitrary eccentricities and inclinations, including retrograde orbits.
The parallel one-dimensional moving-mesh hydrodynamics code RT1D reproduces the multidimensional dynamics from Rayleigh-Taylor instability in supernova remnants.
rtpipe (real-time pipeline) analyzes radio interferometric data with an emphasis on searching for transient or variable astrophysical sources. The package combines single-dish concepts such as dedispersion and filters with interferometric concepts, including images and the uv-plane. In contrast to time-domain data recorded with large single-dish telescopes, visibilities from interferometers can precisely localize sources anywhere in the entire field of view. rtpipe opens interferometers to the study of fast transient sky, including sources like pulsars, stellar flares, rotating radio transients, and fast radio bursts. Key portions of the search pipeline, such as image generation and dedispersion, have been accelerated. That, in combination with its multi-threaded, multi-node design, makes rtpipe capable of searching millisecond timescale data in real time on small compute clusters.
Radio Transient Simulations uses Monte-Carlo simulations to accurately determine transient rates in radio surveys. The user inputs either a real or simulated observational setup, and the simulations code calculates transient rate as a function of transient duration and peak flux. These simulations allow for simulating a wide variety of scenarios including observations with varying sensitivities and durations, multiple overlapping telescope pointings, and a wide variety of light curve shapes with the user having the ability to easily add more. Though the current scientific focus is on the radio regime, the simulations code can be easily adapted to other wavelength regimes.
Rubble implicitly models the local evolution of dust distributions in size, mass, and surface density by solving the Smoluchowski equation (also known as the coagulation-fragmentation equation) under given disk conditions. The Python package's robustness has been validated by a suite of numerical benchmarks against known analytical and empirical results. Rubble can model prescribed physical processes such as bouncing, modulated mass transfer, regulated dust loss/supply, probabilistic collisional outcomes based on velocity distributions, and more. The package also includes a toolkit for analyzing and visualizing results produced by Rubble.
The centrifugal deformation program RUBIS (Rotation code Using Barotropy conservation over Isopotential Surfaces) takes an input 1D model (with spherical symmetry) and returns its deformed version by applying a conservative rotation profile specified by the user. The code needs only the density as a function of radial distance from the reference model in addition to the surface pressure to be imposed to perform the deformation; preserving the relation between density and pressure when going from the 1D to the 2D structure makes this lightness possible. By solving Poisson's equation in spheroidal rather than spherical coordinates whenever a discontinuity is present, RUBIS can deform both stellar and planetary models, thereby dealing with potential discontinuities in the density profile.
runDM calculates the running of the couplings of Dark Matter (DM) to the Standard Model (SM) in simplified models with vector mediators. By specifying the mass of the mediator and the couplings of the mediator to SM fields at high energy, the code can calculate the couplings at low energy, taking into account the mixing of all dimension-6 operators. runDM can also extract the operator coefficients relevant for direct detection, namely low energy couplings to up, down and strange quarks and to protons and neutrons.
The RV program produces a report listing the components, in a given direction, of the observer's velocity on a given date. This allows an observed radial velocity to be referred to an appropriate standard of rest -- typically either the Sun or an LSR.
As a secondary function, RV computes light time components to the Sun, thus allowing the times of phenomena observed from a terrestrial observatory to be referred to a heliocentric frame of reference. n.b. It will of course, in addition, be necessary to express the observations in the appropriate timescale as well as applying light time corrections. In particular, it is likely that an observed UTC will need to be converted to TDB as well as being corrected to the Sun.)
rvfit, developed in IDL 7.0, fits non-precessing keplerian radial velocity (RV) curves for double-line and single-line binary stars or exoplanets. It fits a simple keplerian model to the observed RV and computes the seven parameters (six for a single-line system) from the model. Some parameters can be fixed beforehand if they are known, for instance, if photometric observations are available. The fit is done using an Adaptive Simulated Annealing algorithm optimized for this specific task. Simulated Annealing methods are powerful heuristic algorithms to minimize functions in multiparametric spaces.
The RVLIN package for IDL is a set of routines that quickly fits an arbitrary number of Keplerian curves to radial velocity data. It can handle data from multiple telescopes (i.e. it solves for the offset), constraints on P, e, and time of peri passage, and can incorporate transit timing data. The code handles fixed periods and circular orbits in combination and transit time constraints, including for multiple transiting planets.
RVSAO is a set of programs to obtain redshifts and radial velocities from digital spectra. RVSAO operates in the IRAF (Tody 1986, 1993) environment. The heart of the system is xcsao, which implements the cross-correlation method, and is a direct descendant of the system built by Tonry and Davis (1979). emsao uses intelligent heuristics to search for emission lines in spectra, then fits them to obtain a redshift. sumspec shifts and sums spectra to build templates for cross-correlation. linespec builds synthetic spectra given a list of spectral lines. bcvcorr corrects velocities for the motion of the earth. We discuss in detail the parameters necessary to run xcsao and emsao properly. We discuss the reliability and error associated with xcsao derived redshifts. We develop an internal error estimator, and we show how large, stable surveys can be used to develop more accurate error estimators. We develop a new methodology for building spectral templates for galaxy redshifts. We show how to obtain correlation velocities using emission line templates. Emission line correlations are substantially more efficient than the previous standard technique, automated emission line fitting. We compare the use of RVSAO with new methods, which use Singular Value Decomposition and $chi^2$ fitting techniques.
RVSpecFit determines radial velocities and stellar atmospheric parameters from spectra by direct pixel fitting by interpolated stellar templates. The code doesn't require spectrum normalization and can deal with non-flux calibrated spectra. RVSpecFit is able to fit multiple spectra simultaneously.
The s2 package can represent any arbitrary function defined on the sphere. Both real space map and harmonic space spherical harmonic representations are supported. Basic sky representations have been extended to simulate full sky noise distributions and Gaussian cosmic microwave background realisations. Support for the representation and convolution of beams is also provided. The code requires HEALPix (ascl:1107.018) and CFITSIO (ascl:1010.001).
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