BayesicFitting fits models to data. Data in this context means a set of (measured) points x and y. The model provides some (mathematical) relation between the x and y. Fitting adapts the model such that certain criteria are optimized. The BayesicFitting toolbox also determines whether one model fits the data better than another, making the toolbox particularly powerful. The package consists of more than 100 Python classes, of which one third are model classes. Another third are fitters in one guise or another along with additional tools, and the remaining third is used for Nested Sampling.

BayeSN performs hierarchical Bayesian SED modeling of type Ia supernova light curves. This probabilistic optical-NIR SED model analyzes the population distribution of physical properties as well as cosmology-independent distance estimation for individual SNe. BayeSN is built with NumPyro and Jax (ascl:2111.002) and provides support for GPU acceleration.

BayesVP offers a Bayesian approach for modeling Voigt profiles in absorption spectroscopy. The code fits the absorption line profiles within specified wavelength ranges and generates posterior distributions for the column density, Doppler parameter, and redshifts of the corresponding absorbers. The code uses publicly available efficient parallel sampling packages to sample posterior and thus can be run on parallel platforms. BayesVP supports simultaneous fitting for multiple absorption components in high-dimensional parameter space. The package includes additional utilities such as explicit specification of priors of model parameters, continuum model, Bayesian model comparison criteria, and posterior sampling convergence check.

BAYGAUD (BAYesian GAUssian Decomposer) implements the decomposition of velocity profiles in a data cube and subsequent classification. It uses MultiNest (ascl:1109.006) for calculating the posterior distribution and the evidence for a given likelihood function. The code models a given line profile with an optimal number of Gaussians based on the Bayesian Markov Chain Monte Carlo (MCMC) techniques. BAYGAUD is parallelized using the Message-Passing Interface (MPI) standard, which reduces the time needed to calculate the evidence using MCMC techniques.

BCcodes computes bolometric corrections and synthetic colors in up to 5 filters for input values of the stellar parameters Teff, log(g), [Fe/H], E(B-V) and [alpha/Fe].

BCMemu provides emulators to model the suppression in the power spectrum due to baryonic feedback processes. These emulators are based on the baryonification model, where gravity-only N-body simulation results are manipulated to include the impact of baryonic feedback processes. The package also has a three parameter barynification model; the first assumes all the three parameters to be independent of redshift while the second assumes the parameters to be redshift dependent.

BCES performs robust linear regression on (X,Y) data points where both X and Y have measurement errors. The fitting method is the bivariate correlated errors and intrinsic scatter (BCES). Some of the advantages of BCES regression compared to ordinary least squares fitting are that it allows for measurement errors on both variables and permits the measurement errors for the two variables to be dependent. Further it permits the magnitudes of the measurement errors to depend on the measurements and other lines such as the bisector and the orthogonal regression can be constructed.

BE-HaPPY (Bias Emulator for Halo Power spectrum Python) facilitates future large scale surveys analysis by providing an accurate, easy to use and computationally inexpensive method to compute the halo bias in the presence of massive neutrinos. Provided with a linear power spectrum, the package will compute a new power spectrum according to the chosen configuration. BE-HaPPY handles linear, polynomial, and perturbation theory bias models. The code also handles Kaiser and Scoccimarro redshifts; other available options include real or redshift space, the total neutrino mass, and a choice of mass bin or scale array, among others.

beamconv simulates the scanning of the CMB sky while incorporating realistic beams and scan strategies. It uses (spin-)spherical harmonic representations of the (polarized) beam response and sky to generate simulated CMB detector signal timelines. Beams can be arbitrarily shaped. Pointing timelines can be read in or calculated on the fly; optionally, the results can be binned on the sphere.

beamModelTester enables evaluation of models of the variation in sensitivity and apparent polarization of fixed antenna phased array radio telescopes. The sensitivity of such instruments varies with respect to the orientation of the source to the antenna, resulting in variation in sensitivity over altitude and azimuth that is not consistent with respect to frequency due to other geometric effects. In addition, the different relative orientation of orthogonal pairs of linear antennae produces a difference in sensitivity between the antennae, leading to an artificial apparent polarization. Comparing the model with observations made using the given telescope makes it possible evaluate the model's performance; the results of this evaluation can provide a figure of merit for the model and guide improvements to it. This system also enables plotting of results from a single station observation on a variety of parameters.

The BEARCLAW package is a multidimensional, Eulerian AMR-capable computational code written in Fortran to solve hyperbolic systems for astrophysical applications. It is part of AstroBEAR (ascl:1104.002), a hydrodynamic & magnetohydrodynamic code environment designed for a variety of astrophysical applications which allows simulations in 2, 2.5 (i.e., cylindrical), and 3 dimensions, in either cartesian or curvilinear coordinates.

BEAST (Bayesian Extinction and Stellar Tool) fits the ultraviolet to near-infrared photometric SEDs of stars to extract stellar and dust extinction parameters. The stellar parameters are age (t), mass (M), metallicity (M), and distance (d). The dust extinction parameters are dust column (Av), average grain size (Rv), and mixing between type A and B extinction curves (fA).

BEHR is a standalone command-line C program designed to quickly estimate the hardness ratios and their uncertainties for astrophysical sources. It is especially useful in the Poisson regime of low counts, and computes the proper uncertainty regardless of whether the source is detected in both passbands or not.

BELLAMY is a cross-matching algorithm designed primarily for radio images, that aims to match all sources in the supplied target catalogue to sources in a reference catalogue by calculating the probability of a match. BELLAMY utilises not only the position of a source on the sky, but also the flux data to calculate this probability, determining the most probable match in the reference catalog to the target source. Additionally, BELLAMY attempts to undo any spatial distortion that may be affecting the target catalogue, by creating a model of the offsets of matched sources which is then applied to unmatched sources. This combines to produce an iterative cross-matching algorithm that provides the user with an obvious measure of how confident they should be with the results of a cross-match.

Bessel, written in the C programming language, uses an accurate scheme for evaluating Bessel functions of high order. It has been extensively tested against a number of other routines, demonstrating its accuracy and efficiency.

bettermoments measures precise line-of-sight velocities from Doppler shifted lines to determine small scale deviations indicative of, for example, embedded planets.

The "busy function" accurately describes the characteristic double-horn HI profile of many galaxies. Implemented in a C/C++ library and Python module called BF_dist, it is a continuous, differentiable function that consists of only two basic functions, the error function, erf(x), and a polynomial, |x|^n, of degree n >= 2. BF_dist offers great flexibility in fitting a wide range of HI profiles from the Gaussian profiles of dwarf galaxies to the broad, asymmetric double-horn profiles of spiral galaxies, and can be used to parametrize observed HI spectra of galaxies and the construction of spectral templates for simulations and matched filtering algorithms accurately and efficiently.

A fast GPU-based bispectrum estimator implemented using JAX.

BGLS calculates the Bayesian Generalized Lomb-Scargle periodogram. It takes as input arrays with a time series, a dataset and errors on those data, and returns arrays with sampled periods and the periodogram values at those periods.

BHDD (BlackHolesDarkDress) simulates primordial black hole (PBH) binaries that are clothed in dark matter (DM) halos. The software uses N-body simulations and analytical estimates to follow the evolution of PBH binaries formed in the early Universe.

bhint is a post-Newtonian, high-precision integrator for stellar systems surrounding a super-massive black hole. The algorithm makes use of the fact that the Keplerian orbits in such a potential can be calculated directly and are only weakly perturbed. For a given average number of steps per orbit, bhint is almost a factor of 100 more accurate than the standard Hermite method.

BHJet models steady-state SEDs of jets launched from accreting black holes. This semi-analytical, multi-zone jet model is applicable across the entire black hole mass scale, from black hole X-ray binaries (both low and high mass) to active galactic nuclei of any class (from low-luminosity AGN to flat spectrum radio quasars). It is designed to be more comparable than other codes to GRMHD simulations and/or RMHD semi-analytical solutions.

BHMcalc provides renditions of the instantaneous circumbinary habital zone (CHZ) and also calculates BHM properties of the system including those related to the rotational evolution of the stellar components and the combined XUV and SW fluxes as measured at different distances from the binary. Moreover, it provides numerical results that can be further manipulated and used to calculate other properties.

The Black Hole Perturbation Toolkit models gravitational radiation from small mass-ratio binaries as well as from the ringdown of black holes. The former are key sources for the future space-based gravitational wave detector LISA. BHPToolkit brings together core elements of multiple scattered black hole perturbation theory codes into a Toolkit that can be used by all; different tools can be installed individually by users depending on need and interest.

BHSKY (copyright 1999 by Robert J. Nemiroff) computes the visual distortion effects visible to an observer traveling around and descending near a non-rotating black hole. The codes are general relativistically accurate and incorporate concepts such as large-angle deflections, image magnifications, multiple imaging, blue-shifting, and the location of the photon sphere. Once star.dat is edited to define the position and orientation of the observer relative to the black hole, bhsky_table should be run to create a table of photon deflection angles. Next bhsky_image reads this table and recomputes the perceived positions of stars in star.num, the Yale Bright Star Catalog. Lastly, bhsky_camera plots these results. The code currently tracks only the two brightest images of each star, and hence becomes noticeably incomplete within 1.1 times the Schwarzschild radius.

BIANCHI provides functionality to support the simulation of Bianchi Type VIIh induced temperature fluctuations in CMB maps of a universe with shear and rotation. The implementation is based on the solutions to the Bianchi models derived by Barrow et al. (1985), which do not incorporate any dark energy component. Functionality is provided to compute the induced fluctuations on the sphere directly in either real or harmonic space.

BiaPy provides deep-learning workflows for a large variety of image analysis tasks, including 2D and 3D semantic segmentation, instance segmentation, object detection, image denoising, single image super-resolution, self-supervised learning and image classification. Though developed specifically for bioimages, it can be used for watershed-based instance segmentation for friends-of-friends proto-haloes.

bias_emulator models the clustering of halos on large scales. It incorporates the cosmological dependence of the bias beyond the mapping of halo mass to peak height. Precise measurements of the halo bias in the simulations are interpolated across cosmological parameter space to obtain the halo bias at any point in parameter space within the simulation cloud. A tool to produce realizations of correlated noise for propagating the modeling uncertainty into error budgets that use the emulator is also provided.

The Bayesian Inference Engine (BIE) is an object-oriented library of tools written in C++ designed explicitly to enable Bayesian update and model comparison for astronomical problems. To facilitate "what if" exploration, BIE provides a command line interface (written with Bison and Flex) to run input scripts. The output of the code is a simulation of the Bayesian posterior distribution from which summary statistics e.g. by taking moments, or determine confidence intervals and so forth, can be determined. All of these quantities are fundamentally integrals and the Markov Chain approach produces variates $ heta$ distributed according to $P( heta|D)$ so moments are trivially obtained by summing of the ensemble of variates.

BiFFT uses Fourier transforms to implement the Dirac-Delta function that enforces a closed triangle of three k-vectors; this allows very fast calculations of the bispectrum. Once the C code associated with the package is compiled and the source folder directed to the location of the C code, the user can run the code using the python wrapper.The binning in each function has been tested over the course of many years and the user can use it out of the box without ever touching the underlying C code. However, the cylindrical bispectrum calculation is much more sensitive to sample variance; its default binning is quite coarse and might need adjusting (and testing) for some datasets.

Bifrost is a stream processing framework that eases the development of high-throughput processing CPU/GPU pipelines. It is designed for digital signal processing (DSP) applications within radio astronomy. Bifrost uses a flexible ring buffer implementation that allows different signal processing blocks to be connected to form a pipeline. Each block may be assigned to a CPU core, and the ring buffers are used to transport data to and from blocks. Processing blocks may be run on either the CPU or GPU, and the ring buffer will take care of memory copies between the CPU and GPU spaces.

Big MACS is a Python program that estimates an accurate photometric calibration from only an input catalog of stellar magnitudes and filter transmission functions. The user does not have to measure color terms which can be difficult to characterize. Supplied with filter transmission functions, Big MACS synthesizes an expected stellar locus for your data and then simultaneously solves for all unknown zeropoints when fitting to the instrumental locus. The code uses a spectroscopic model for the SDSS stellar locus in color-color space and filter functions to compute expected locus. The stellar locus model is corrected for Milky Way reddening. If SDSS or 2MASS photometry is available for stars in field, Big MACS can yield a highly accurate absolute calibration.

bigfile stores data from cosmology simulations from HPC systems and beyond. It provides a hierarchical structure of data columns via File, Dataset and Column. A Column stores a two dimensional table. Numerical typed columns are supported; attributes can be attached to a Column and both numerical attributes and string attributes are supported. Type casting is performed on-the-fly if read/write operations request a different data type than the file has stored.

BiGONLight (Bi-local geodesic operators framework for numerical light propagation) encodes the Bi-local Geodesic Operators formalism (BGO) to study light propagation in the geometric optics regime in General Relativity. The parallel transport equations, the optical tidal matrix, and the geodesic deviation equations for the bilocal operators are expressed in 3+1 form and encoded in BiGONLight as Mathematica functions. The bilocal operators are used to obtain all possible optical observables by combining them with the observer and emitter four-velocities and four-accelerations. The user can choose the position of the source and the observer anywhere along the null geodesic with any four-velocities and four-accelerations.

BiHalofit fits the matter bispectrum in the nonlinear regime calibrated by high-resolution cosmological N-body simulations of 41 cold dark matter models around the Planck 2015 best-fit parameters. The parameterization is similar to that in Halofit (ascl:1402.032). The simulation volume is sufficiently large to cover almost all measurable triangle bispectrum configurations in the universe, and the function is calibrated using one-loop perturbation theory at large scales. BiHaloFit predicts the weak-lensing bispectrum and will assist current and future weak-lensing surveys and cosmic microwave background lensing experiments.

Bilby provides a user-friendly interface to perform parameter estimation. It is primarily designed and built for inference of compact binary coalescence events in interferometric data, such as analysis of compact binary mergers and other types of signal model including supernovae and the remnants of binary neutron star mergers, but it can also be used for more general problems. The software is flexible, allowing the user to change the signal model, implement new likelihood functions, and add new detectors. Bilby can also be used to do population studies using hierarchical Bayesian modelling.

binary_c-python provides a manager for and interface to the binary_c framework (ascl:2307.035), and rapidly evolves individual systems and populations of stars. It provides functions such as data processing tools and initial distribution functions for stellar properties. binary_c-python also includes tools to run large grids of (binary) stellar systems on servers or distributed systems.

The binary_c software framework models the evolution of single, binary and multiple stars, including stellar evolution and nucleosynthesis. Stellar evolution includes wind mass loss, rotation, thermal pulses, magnetic braking, pre-main sequence evolution, supernovae and kicks, and neutron stars; binary-star evolution includes mass transfer, gravitational-wave losses, tides, novae, circumbinary discs, and merging stars. binary_c natively includes nucleosynthesis, and, as it is designed for stellar population calculations, it is lightweight and versatile. binary_c works in standalone, virtual and HPC environments, and its support software contains tools for development and data analysis. A version in Python, binary_c-python (ascl:2307.036), is also available.

binary_precursor models light curves of supernova (SN) precursors powered by a pre-SN outburst accompanying accretion onto a compact object companion. Though it is only one of the possible models, it is useful for interpretations of (bright) SN precursors highly exceeding the Eddington limit of massive stars, which are observed in a fraction of SNe with dense circumstellar matter (CSM) around the progenitor. It offers a number of editable parameters, including compact object mass, progenitor mass, progenitor radii, and opacity. Initial CSM velocity can be normalized by the progenitor escape velocity (xi parameter), and the CSM mass, ionization temperature, and binary separation can also be specified.

Binary-Speckle reduces Speckle or AO data from the raw data to deconvolved images (in Fourier space), to determine the parameters of a binary or triple, and to find limits for undetected companion stars.

Binary computes the evolution of an accretion disc interacting with a binary system. It has been developed and used to study the coupled evolution of supermassive BH binaries and gaseous accretion discs.

binaryBHexp (binary black hole explorer) uses surrogate models of numerical simulations to generate on-the-fly interactive visualizations of precessing binary black holes. These visualizations can be generated in a few seconds and at any point in the 7-dimensional parameter space of the underlying surrogate models. These visualizations provide a valuable means to understand and gain insights about binary black hole systems and gravitational physics such as those detected by the LIGO gravitational wave detector.

binaryoffset identifies the binary offset effect in images from any detector. The easiest input to work with is a dark or bias image that is spatially flat. The code can also be run on images that are not spatially flat, assuming that there is some model of the signal on the CCD that can be used to produce a residual image.

Given a series of radial velocities as a function of time for a star in a binary system, BinaryStarSolver solves for various orbital parameters. Namely, it solves for eccentricity (e), argument of periastron (ω), velocity amplitude (K), long term average radial velocity (γ), and orbital period (P). If the orbital parameters of a primary star are already known, it can also find the orbital parameters of a companion star, with only a few radial velocity data points.

The BI-spectra and Non-Gaussianity Operator (BINGO) code, written in Fortran, computes the scalar bi-spectrum and the non-Gaussianity parameter fNL in single field inflationary models involving the canonical scalar field. BINGO can calculate all the different contributions to the bi-spectrum and the parameter fNL for an arbitrary triangular configuration of the wavevectors.

BinMag examines theoretical stellar spectra computed with Synth/SynthMag/Synmast/Synth3/SME spectrum synthesis codes and compare them to observations. An IDL widget program, BinMag applies radial velocity shift and broadening to the theoretical spectra to account for the effects of stellar rotation, radial-tangential macroturbulence, and instrumental smearing. The code can also simulate spectra of spectroscopic binary stars by appropriate coaddition of two synthetic spectra. Additionally, BinMag can be used to measure equivalent width, fit line profile shapes with analytical functions, and to automatically determine radial velocity and broadening parameters. BinMag interfaces with the Synth3 (ascl:1212.010) and SME (ascl:1202.013) codes, allowing the user to determine chemical abundances and stellar atmospheric parameters from the observed spectra.

Binospec reduces data for the Binospec imaging spectrograph. The software is also used for observation planning and instrument control, and is automated to decrease the number of tasks the user has to perform. Binospec uses a database-driven approach for instrument configuration and sequencing of observations to maximize efficiency, and a web-based interface is available for defining observations, monitoring status, and retrieving data products.

Binsim produces images of interacting binaries for any system parameters. Though not suitable for modeling light curves or spectra, the resulting images are helpful in visualizing the geometry of a given system and are also helpful in talks and educational work. The code uses the OpenGL API to do the 3D rendering. The software can produce images of cataclysmic variables and X-ray binaries, and can render the mass donor star, an axisymmetric disc (without superhumps, warps or spirals), the accretion stream and hotspot, and a "corona."

The BINSYN program suite is a collection of programs for analysis of binary star systems with or without an optically thick accretion disk. BINSYN produces synthetic spectra of individual binary star components plus a synthetic spectrum of the system. If the system includes an accretion disk, BINSYN also produces a separate synthetic spectrum of the disk face and rim. A system routine convolves the synthetic spectra with filter profiles of several photometric standards to produce absolute synthetic photometry output. The package generates synthetic light curves and determines an optimized solution for system parameters.

BiPoS1 (Binary Population Synthesizer) efficiently calculates binary distribution functions after the dynamical processing of a realistic population of binary stars during the first few Myr in the hosting embedded star cluster. It is particularly useful for generating a realistic birth binary population as an input for N-body simulations of globular clusters. Instead of time-consuming N-body simulations, BiPoS1 uses the stellar dynamical operator, which determines the fraction of surviving binaries depending on the binding energy of the binaries. The stellar dynamical operator depends on the initial star cluster density, as well as the time until the residual gas of the star cluster is expelled. At the time of gas expulsion, the dynamical processing of the binary population is assumed to effectively end due to the expansion of the star cluster related to that event. BiPoS1 has also a galactic-field mode, in order to synthesize the stellar population of a whole galaxy.

The Bisous model is a marked point process that models multi-dimensional patterns. The Bisous filament finder works directly with galaxy distribution data and the model intrinsically takes into account the connectivity of the filamentary network. The Bisous model generates the visit map (the probability to find a filament at a given point) together with the filament orientation field; these two fields are used to extract filament spines from the data.

Bitshuffle rearranges typed, binary data for improving compression; the algorithm is implemented in a python/C package within the Numpy framework. The library can be used alongside HDF5 to compress and decompress datasets and is integrated through the dynamically loaded filters framework. Algorithmically, Bitshuffle is closely related to HDF5's Shuffle filter except it operates at the bit level instead of the byte level. Arranging a typed data array in to a matrix with the elements as the rows and the bits within the elements as the columns, Bitshuffle "transposes" the matrix, such that all the least-significant-bits are in a row, etc. This transposition is performed within blocks of data roughly 8kB long; this does not in itself compress data, but rearranges it for more efficient compression. A compression library is necessary to perform the actual compression. This scheme has been used for compression of radio data in high performance computing.

The Fermi-LAT Background Estimator (BKGE) is a publicly available open-source tool that can estimate the expected background of the Fermi-LAT for any observational conguration and duration. It produces results in the form of text files, ROOT files, gtlike source-model files (for LAT maximum likelihood analyses), and PHA I/II FITS files (for RMFit/XSpec spectral fitting analyses). Its core is written in C++ and its user interface in Python.

BlackBOX performs standard CCD image reduction tasks on multiple images from the BlackGEM and MeerLICHT telescopes. It uses the satdet module of ASCtools (ascl:2011.024) and Astro-SCRAPPY (ascl:1907.032). BlackBOX simultaneously uses multi-processing and multi-threading and feeds the reduced images to ZOGY (ascl:2105.010) to ultimately perform optimal image subtraction and detect transient sources.

BlackHawk calculates the Hawking evaporation spectra of any black hole distribution. Written in C, the program enables users to compute the primary and secondary spectra of stable or long-lived particles generated by Hawking radiation of the distribution of black holes, and to study their evolution in time.

BlackJAX is a sampling library designed for ease of use, speed, and modularity and works on CPU as well as GPU. It is not a probabilistic programming library (PLL), though it integrates well with PPLs as long as they can provide a (potentially unnormalized) log-probability density function compatible with JAX. BlackJAX is written in pure Python and depends on XLA via JAX (ascl:2111.002). It can be used by those who have a logpdf and need a sampler or need more than a general-purpose sampler. It is also useful for building a sample on GPU and for users who want to learn how sampling algorithms work.

Blacklight postprocesses general-relativistic magnetohydrodynamic simulation data and produces outputs for analyzing data sets, including maps of auxiliary quantities and false-color renderings. The code can use Athena++ (ascl:1912.005) outputs directly, and also supports files in HARM (ascl:1209.005) and iHARM3d (ascl:2210.013) format. Written in C++, Blacklight offers support for adaptive mesh refinement input, slow-light calculations, and adaptive ray tracing.

blackthorn generates spectra of dark matter annihilations into right-handed (RH) neutrinos or into particles that result from their decay. These spectra include photons, positrons, and neutrinos. The code provides support for varied RH-neutrino masses ranging from MeV to TeV by incorporating hazma, PPPC4DMID, and HDMSpectra models to compute dark matter annihilation cross sections and mediator decay widths. blackthorn also computes decay branching fractions and partial decay widths.

BlaST (Blazar Synchrotron Tool) estimates the synchrotron peak of blazars given their spectral energy distribution. It uses a machine-learning algorithm that simplifies the estimation and also provides a reliable uncertainty estimation. The package naturally accounts for additional SED components from the host galaxy and the disk emission. BlaST also supports bulk estimation, e.g. estimating a whole catalog, by providing a directory or zip file containing the seds as well as an output file in which to write the results.

Blimpy (Breakthrough Listen I/O Methods for Python) provides utilities for viewing and interacting with the data formats used within the Breakthrough Listen program, including Sigproc filterbank (.fil) and HDF5 (.h5) files that contain dynamic spectra (aka 'waterfalls'), and guppi raw (.raw) files that contain voltage-level data. Blimpy can also extract, calibrate, and visualize data and a suite of command-line utilities are also available.

Blobby3D performs Bayesian inference for gas kinematics on emission line observations of galaxies using Integral Field Spectroscopy. The code robustly infers gas kinematics for regularly rotating galaxies even if the gas profiles have significant substructure. Blobby3D also infers gas kinematic properties free from the effects of beam smearing (where beam smearing is the effect of the observational seeing spatially blurring the gas profiles), which has significant effects on the observed gas kinematic properties, particularly the observed velocity dispersion.

BLOBCAT is a source extraction software that utilizes the flood fill algorithm to detect and catalog blobs, or islands of pixels representing sources, in 2D astronomical images. The software is designed to process radio-wavelength images of both Stokes I intensity and linear polarization, the latter formed through the quadrature sum of Stokes Q and U intensities or as a by-product of rotation measure synthesis. BLOBCAT corrects for two systematic biases to enable the flood fill algorithm to accurately measure flux densities for Gaussian sources. BLOBCAT exhibits accurate measurement performance in total intensity and, in particular, linear polarization, and is particularly suited to the analysis of large survey data.

Bayesian Blocks is a time-domain algorithm for detecting localized structures (bursts), revealing pulse shapes, and generally characterizing intensity variations. The input is raw counting data, in any of three forms: time-tagged photon events, binned counts, or time-to-spill data. The output is the most probable segmentation of the observation into time intervals during which the photon arrival rate is perceptibly constant, i.e. has no statistically significant variations. The idea is not that the source is deemed to have this discontinuous, piecewise constant form, rather that such an approximate and generic model is often useful. The analysis is based on Bayesian statistics.

This code is obsolete and yields approximate results; see Bayesian Blocks (ascl:1209.001) instead for an algorithm guaranteeing exact global optimization.

BLOSMapping determines the line-of-sight component of magnetic fields associated with molecular clouds. The code uses Faraday rotation measure catalogs along with an on-off approach based on relative measurements to estimate the rotation measure caused by molecular clouds. It then uses the outputs from a chemical evolution code along with extinction maps to determine the line-of-sight magnetic field strength and direction.

BLS (Box-fitting Least Squares) is a box-fitting algorithm that analyzes stellar photometric time series to search for periodic transits of extrasolar planets. It searches for signals characterized by a periodic alternation between two discrete levels, with much less time spent at the lower level.

BMarXiv scans new (i.e., since the last time checked) submissions from arXiv, ranks submissions based on keyword matches, and produces an HTML page as an output.

The keywords are looked for (with regex capabilities) in the title, abstract, but also the author list, so it is possible to look for people too. The score is calculated for each specific entry but additional (and optional) scoring is performed using the first author recent submissions and/or the other authors' recent submissions.

It is possible to include/exclude any arXiv categories (within astro-ph or not). New astronomical conferences (from CADC by default) and new codes (from ASCL.net) are also checked and can also be scanned for keywords.

A local bibliography file can be scanned to find frequent words/groups of words that could become scanned keywords.

bmcmc is a general purpose Markov Chain Monte Carlo package for Bayesian data analysis. It uses an adaptive scheme for automatic tuning of proposal distributions. It can also handle Bayesian hierarchical models by making use of the Metropolis-Within-Gibbs scheme.

BOND determines oxygen and nitrogen abundances in giant H II regions by comparison with a large grid of photoionization models. The grid spans a wide range in O/H, N/O and ionization parameter U, and covers different starburst ages and nebular geometries. Unlike other statistical methods, BOND relies on the [Ar III]/[Ne III] emission line ratio to break the oxygen abundance bimodality. By doing so, it can measure oxygen and nitrogen abundances without assuming any a priori relation between N/O and O/H. BOND takes into account changes in the hardness of the ionizing radiation field, which can come about due to the ageing of H II regions or the stochastically sampling of the IMF. The emission line ratio He I/Hβ, in addition to commonly used strong lines, constrains the hardness of the ionizing radiation field. BOND relies on the emission line ratios [O III]/Hβ, [O II]/Hβ and [N II]/Hβ, [Ar III]/Hβ, [Ne III]/Hβ, He I/Hβ as its input parameters, while its output values are the measurements and uncertainties for O/H and N/O.

Bonsai is a gravitational N-body tree-code that runs completely on the GPU. This reduces the amount of time spent on communication with the CPU. The code runs on NVIDIA GPUs and on a GTX480 it is able to integrate ~2.8M particles per second. The tree construction and traverse algorithms are portable to many-core devices which have support for CUDA or OpenCL programming languages.

The Bootsik software generates and visualizes potential magnetic fields. bootsik.f90 generates a potential magnetic field on a 3D mesh, staggered relative to the magnetic potential, by extrapolating the magnetic field normal to the photospheric surface. The code first calculates a magnetic potential using a modified Green’s function method and then uses a finite differencing scheme to calculate the magnetic field from the potential. The IDL script boobox.pro can then be used to visualize the magnetic field.

BOOTTRAN calculates error bars for Keplerian orbital parameters for both single- and multiple-planet systems. It takes the best-fit parameters and radial velocity data (BJD, velocity, errors) and calculates the error bars from sampling distribution estimated via bootstrapping. It is recommended to be used together with the RVLIN (ascl:1210.031) package, which find best-fit Keplerian orbital parameters. Both RVLIN and BOOTTRAN are compatible with multiple-telescope data. BOOTTRAN also calculates the transit time and secondary eclipse time and their associated error bars. The algorithm is described in the appendix of the associated article.

The basic mechanisms responsible for producing winds from cool, late-type stars are still largely unknown. We take inspiration from recent progress in understanding solar wind acceleration to develop a physically motivated model of the time-steady mass loss rates of cool main-sequence stars and evolved giants. This model follows the energy flux of magnetohydrodynamic turbulence from a subsurface convection zone to its eventual dissipation and escape through open magnetic flux tubes. We show how Alfven waves and turbulence can produce winds in either a hot corona or a cool extended chromosphere, and we specify the conditions that determine whether or not coronal heating occurs. These models do not utilize arbitrary normalization factors, but instead predict the mass loss rate directly from a star's fundamental properties. We take account of stellar magnetic activity by extending standard age-activity-rotation indicators to include the evolution of the filling factor of strong photospheric magnetic fields. We compared the predicted mass loss rates with observed values for 47 stars and found significantly better agreement than was obtained from the popular scaling laws of Reimers, Schroeder, and Cuntz. The algorithm used to compute cool-star mass loss rates is provided as a self-contained and efficient IDL computer code. We anticipate that the results from this kind of model can be incorporated straightforwardly into stellar evolution calculations and population synthesis techniques.

BornRaytrace uses neural data compression of weak lensing map summary statistics to simulate weak gravitational lensing effects. It can raytrace through overdensity Healpix maps to return a convergence map, include shear-kappa transformation on the full sphere, and also include intrinsic alignments (NLA model).

BOWIE (Binary Observability With Illustrative Exploration) performs graphical analysis of binary signals from gravitational waves. It takes gridded data sets and produces different types of plots in customized arrangements for detailed analysis of gravitational wave sensitivity curves and/or binary signals. BOWIE offers three main tools: a gridded data generator, a plotting tool, and a waveform generator for general use. The waveform generator creates PhenomD waveforms for binary black hole inspiral, merger, and ringdown. Gridded data sets are created using the PhenomD generator for signal-to-noise (SNR) analysis. Using the gridded data sets, customized configurations of plots are created with the plotting package.

BOXFIT calculates light curves and spectra for arbitrary observer times and frequencies and of performing (broadband) data fits using the downhill simplex method combined with simulated annealing. The flux value for a given observer time and frequency is a function of various variables that set the explosion physics (energy of the explosion, circumburst number density and jet collimation angle), the radiative process (magnetic field generation efficiency, electron shock-acceleration efficiency and synchrotron power slope for the electron energy distribution) and observer position (distance, redshift and angle). The code can be run both in parallel and on a single core. Because a data fit takes many iterations, this is best done in parallel. Single light curves and spectra can readily be done on a single core.

BoxRemap remaps the cubical domain of a cosmological simulation into simple non-cubical shapes. It can be used for on-the-fly remappings of the simulation geometry and is volume-preserving; remapped geometry has the same volume V = L3 as the original simulation box. The remappings are structure-preserving (local neighboring structures are mapped to neighboring places) and one-to-one, with every particle/halo/galaxy/etc. appearing once and only once in the remapped volume.

Photometric redshift estimation is becoming an increasingly important technique, although the currently existing methods present several shortcomings which hinder their application. Most of those drawbacks are efficiently eliminated when Bayesian probability is consistently applied to this problem. The use of prior probabilities and Bayesian marginalization allows the inclusion of valuable information, e.g. the redshift distributions or the galaxy type mix, which is often ignored by other methods. In those cases when the a priori information is insufficient, it is shown how to `calibrate' the prior distributions, using even the data under consideration. There is an excellent agreement between the 108 HDF spectroscopic redshifts and the predictions of the method, with a rms error Delta z/(1+z_spec) = 0.08 up to z<6 and no systematic biases nor outliers. The results obtained are more reliable than those of standard techniques even when the latter include near-IR colors. The Bayesian formalism developed here can be generalized to deal with a wide range of problems which make use of photometric redshifts, e.g. the estimation of individual galaxy characteristics as the metallicity, dust content, etc., or the study of galaxy evolution and the cosmological parameters from large multicolor surveys. Finally, using Bayesian probability it is possible to develop an integrated statistical method for cluster mass reconstruction which simultaneously considers the information provided by gravitational lensing and photometric redshifts.

BRATS (Broadband Radio Astronomy ToolS) provides tools for the spectral analysis of broad-bandwidth radio data and legacy support for narrowband telescopes. It can fit models of spectral ageing on small spatial scales, offers automatic selection of regions based on user parameters (e.g. signal to noise), and automatic determination of the best-fitting injection index. It includes statistical testing, including Chi-squared, error maps, confidence levels and binning of model fits, and can map spectral index as a function of position. It also provides the ability to reconstruct sources at any frequency for a given model and parameter set, subtract any two FITS images and output residual maps, easily combine and scale FITS images in the image plane, and resize radio maps.

Given a FITS image, breizorro creates a binary mask. The software allows the user control various parameters and functions, such as setting a sigma threshold for masking, merging in or subtracting one or more masks or region files, filling holes, applying dilation within a defined radius of pixels, and inverting the mask.

BRUCE and KYLIE, written in Fortran 77, synthesize the spectra of pulsating stars. BRUCE constructs a point-sampled model for the surface of a rotating, gravity-darkened star, and then subjects this model to perturbations arising from one or more non-radial pulsation modes. Departures from adiabaticity can be taken into account, as can the Coriolis force through adoption of the so-called traditional approximation. BRUCE writes out a time-sequence of perturbed surface models. This sequence is read in by KYLIE, which synthesizes disk-integrated spectra for the models by co-adding the specific intensity emanating from each visible point toward the observer. The specific intensity is calculated by interpolation in a large temperature-gravity-wavelength-angle grid of pre-calculated intensity spectra.

Brut, written in Python, identifies bubbles in infrared images of the Galactic midplane; it uses a database of known bubbles from the Milky Way Project and Spitzer images to build an automatic bubble classifier. The classifier is based on the Random Forest algorithm, and uses the WiseRF implementation of this algorithm.

brutifus aids in post-processing datacubes from integral field spectrographs. The set of Python routines in the package handle generic tasks, such as the registration of a datacube WCS solution with the Gaia catalogue, the correction of Galactic reddening, or the subtraction of the nebular/stellar continuum on a spaxel-per-spaxel basis, with as little user interactions as possible. brutifus is modular, in that the order in which the post-processing routines are run is entirely customizable.

BSAVI (Bayesian Sample Visualizer) is a tool to aid likelihood analysis of model parameters where samples from a distribution in the parameter space are used as inputs to calculate a given observable. For example, selecting a range of samples will allow you to easily see how the observables change as you traverse the sample distribution. At the core of BSAVI is the Observable object, which contains the data for a given observable and instructions for plotting it. It is modular, so you can write your own function that takes the parameter values as inputs, and BSAVI will use it to compute observables on the fly. It also accepts tabular data, so if you have pre-computed observables, simply import them alongside the dataset containing the sample distribution to start visualizing.

BSE is a rapid binary star evolution code. It can model circularization of eccentric orbits and synchronization of stellar rotation with the orbital motion owing to tidal interaction in detail. Angular momentum loss mechanisms, such as gravitational radiation and magnetic braking, are also modelled. Wind accretion, where the secondary may accrete some of the material lost from the primary in a wind, is allowed with the necessary adjustments made to the orbital parameters in the event of any mass variations. Mass transfer occurs if either star fills its Roche lobe and may proceed on a nuclear, thermal or dynamical time-scale. In the latter regime, the radius of the primary increases in response to mass-loss at a faster rate than the Roche-lobe of the star. Prescriptions to determine the type and rate of mass transfer, the response of the secondary to accretion and the outcome of any merger events are in place in BSE.

BSGMODEL is used to construct the disk and spheroid components of the Galaxy from which the distribution of visible stars and mass in the Galaxy is calculated. The computer files accessible here are available for export use. The modifications are described in comment lines in the software. The Galaxy model software has been installed and used by different people for a large variety of purposes (see, e. g., the the review "Star Counts and Galactic Structure'', Ann. Rev. Astron. Ap. 24, 577, 1986 ).

bskit, built upon the nbodykit (ascl:1904.027) simulation analysis package, measures density bispectra from snapshots of cosmological N-body or hydrodynamical simulations. It can measure auto or cross bispectra in a user-specified set of triangle bins (that is, triplets of 3-vector wavenumbers). Several common sets of bins are also implemented, including all triangle bins for specified k_min and k_max, equilateral triangles between specified k_min and k_max, isosceles triangles, and squeezed isosceles triangles.

Behind The Spectrum (BTS) is a fully-automated multiple-component fitter for optically-thin spectra. Written as a python module, the routine uses the first, second and third derivatives to determine thenumber of components in the spectrum. A least-squared fitting routine then determines the best fit with that number of components, checking for over-fitting and over-lapping velocity centroids.

BTSbot automates real-time identification of bright extragalactic transients in Zwicky Transient Facility (ZTF) data. A multi-modal convolutional neural network, BTSbot provides a bright transient score to individual ZTF detections using their image data and 25 extracted features. The package eliminates the need for daily visual inspection of new transients by automatically identifying and requesting spectroscopic follow-up observations of new bright transient candidates. BTSbot recovers all bright transients in our test split and performs on par with human experts in terms of identification speed (on average, ∼1 hour quicker than scanners).

Budda is a Fortran code developed to perform a detailed structural analysis on galaxy images. It is simple to use and gives reliable estimates of the galaxy structural parameters, which can be used, for instance, in Fundamental Plane studies. Moreover, it has a powerful ability to reveal hidden sub-structures, like inner disks, secondary bars and nuclear rings.

BUQO solves large-scale imaging inverse problems. It leverages probability concentration phenomena and the underlying convex geometry to formulate the Bayesian hypothesis test as a convex problem that is then efficiently solved by using scalable optimization algorithms. This allows scaling to high-resolution and high-sensitivity imaging problems that are computationally unaffordable for other Bayesian computation approaches.

Burning Arrow determines the destabilization of massive particle circular orbits due to thermal radiation, emitted in X-ray, from the hot accretion disk material. This code requires the radiation forces exerted on the material at the point of interest found by running the code Infinity (ascl:2212.021). Burning Arrow begins by assuming a target particle in the disk that moves in a circular orbit. It then introduces the recorded radiation forces from Infinity code for the target region. The forces are subsequently introduced into the target particle equations of motion and the trajectory is recalculated. Burning Arrow then produces images of the black hole - accretion disk system that includes the degenerated particle trajectories that obey the assorted velocity profiles.

BurnMan determines seismic velocities for the lower mantle. Written in Python, BurnMan calculates the isotropic thermoelastic moduli by solving the equations-of-state for a mixture of minerals defined by the user. The user may select from a list of minerals applicable to the lower mantle included or can define one. BurnMan provides choices in methodology, both for the EoS and for the multiphase averaging scheme and the results can be visually or quantitatively compared to observed seismic models.

Butterpy simulates star spot emergence, evolution, decay, and stellar rotational light curves. It tests the recovery of stellar rotation periods using different frequency analysis techniques. Butterpy can simulate light curves of stars with variable activity level, rotation period, spot lifetime, magnetic cycle duration and overlap, spot emergence latitudes, and latitudinal differential rotation shear.

Braneworld-extra-dimensions places constraints on the size of the AdS5 radius of curvature within the Randall-Sundrum brane-world model in light of the near-simultaneous detection of the gravitational wave event GW170817 and its optical counterpart, the short γ-ray burst event GRB170817A. The code requires a (supplied) patch to the Montepython cosmological MCMC sampler (ascl:1805.027) to sample the posterior distribution of the 4-dimensional parameter space in VBV17 and obtain constraints on the parameters.

BXA connects the nested sampling algorithm MultiNest (ascl:1109.006) to the X-ray spectral analysis environments Xspec (ascl:9910.005) and Sherpa (ascl:1107.005) for Bayesian parameter estimation and model comparison. It provides parameter estimation in arbitrary dimensions and plotting of spectral model vs. the data for best fit, posterior samples, or each component. BXA allows for model selection; it computes the evidence for the considered model, ready for use in computing Bayes factors and is not limited to nested models. It also visualizes deviations between model and data with Quantile-Quantile (QQ) plots, which do not require binning and are more comprehensive than residuals.

The concentration-mass relation for dark matter-dominated halos is one of the essential results expected from a theory of structure formation. C-m Emu is a simple numerical code for the c-M relation as a function of cosmological parameters for wCDM models generates the best-fit power-law model for each redshift separately and then interpolate between the redshifts. This produces a more accurate answer at each redshift at the minimal cost of running a fast code for every c -M prediction instead of using one fitting formula. The emulator is constructed from 37 individual models, with three nested N-body gravity-only simulations carried out for each model. The mass range covered by the emulator is 2 x 10^{12} M_sun < M <10^{15} M_sun with a corresponding redshift range of z=0 -1. Over this range of mass and redshift, as well as the variation of cosmological parameters studied, the mean halo concentration varies from c ~ 2 to c ~ 8. The distribution of the concentration at fixed mass is Gaussian with a standard deviation of one-third of the mean value, almost independent of cosmology, mass, and redshift over the ranges probed by the simulations.

C²-Ray calculates spherical symmetric time-dependent photo-ionization in 1D with the source at the origin for hydrogen only. The code is explicitly photon-conserving and uses an analytical relaxation solution for the ionization rate equations for each time step, thus enabling integration of the equation of transfer along a ray with fewer cells and time steps than previous methods. It is suitable for coupling radiative transfer to gas and N-body dynamics methods on fixed or adaptive grids. C²-Ray is not parallelized but contains an MPI module for compatibility with the 3D version (C²-Ray3Dm).

C²-Ray3Dm performs time-dependent photo-ionization calculations for 3D multiple sources, and for hydrogen only. Based on C²-Ray (ascl:2312.022), it runs under both MPI and OpenMP. The length of subroutines has been reduced to make the code more manageable and easier to read.

C2-Ray3Dm1D_Helium is the hydrogen + helium version of the radiative transfer photo-ionization code C²-Ray. It combines the 1D and 3D versions of the code.

The Command-line Catalogue Cross-matching (C³) software efficiently performs the positional cross-match between massive catalogues from modern astronomical surveys, whose size have rapidly increased in the current data-driven science era. Based on a multi-core parallel processing paradigm, it is executed as a stand-alone command-line process or integrated within any generic data reduction/analysis pipeline. C³ provides its users with flexibility in portability, parameter configuration, catalogue formats, angular resolution, region shapes, coordinate units and cross-matching types.