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[ascl:2307.021] FGBuster: Parametric component separation for Cosmic Microwave Background observations

FGBuster (ForeGroundBuster) separates frequency maps into component maps and forecasts component separation both when the model is correct and when it is incorrect. FGBuster can be used for SED evaluation, intermediate component separation, multi-resolution separation, and forecasting, among other tasks.

[ascl:2307.020] PolyBin: Binned polyspectrum estimation on the full sky

PolyBin estimates the binned power spectrum, bispectrum, and trispectrum for full-sky HEALPix maps such as the CMB. This can include both spin-0 and spin-2 fields, such as the CMB temperature and polarization, or galaxy positions and galaxy shear. Alternatively, one can use only scalar maps. For each statistic, two estimators are available: the standard (ideal) estimators, which do not take into account the mask, and window-deconvolved estimators. For the second case, a Fisher matrix must be computed; this depends on binning and the mask, but does not need to be recomputed for each new simulation. PolyBin can compute both the parity-even and parity-odd components, accounting for any leakage between the two, for the bispectrum and trispectrum.

[ascl:2307.019] IMRPhenomD: Phenomenological waveform model

The IMRPhenomD model generates gravitational wave signals for merging black hole binaries with non-precessing spins. The waveforms are produced in the frequency domain and include the inspiral, merger and ringdown parts for the dominant spherical harmonic mode of the signal. Part of LALSuite (ascl:2012.021) and also available as an independent code, IMRPhenomD is written in C and is calibrated against data from numerical relativity simulations. A re-implementation of IMRPhenomD in Python, PyIMRPhenomD (ascl:2307.023), is available.

[ascl:2307.018] IMRIpy: Intermediate Mass Ratio Inspirals simulator

IMRIpy simulates an Intermediate Mass Ratio Inspiral (IMRI) by gravitational wave emission with a Dark Matter(DM) halo or a (baryonic) Accretion Disk around the central Intermediate Mass Black Hole(IMBH). It can use different density profiles (such as DM spikes), and different interactions, such as dynamical friction with and without HaloFeedback models or accretion, to produce the simulation.

[ascl:2307.017] Veusz: Scientific plotting package

Veusz produces a wide variety of publication-ready 2D and 3D plots. Plots are created by building up plotting widgets with a consistent object-based interface, and the package provides many options for customizing plots. Veusz can import data from text, CSV, HDF5 and FITS files; datasets can also be entered within the program and new datasets created via the manipulation of existing datasets using mathematical expressions and more. The program can also be extended, by adding plugins supporting importing new data formats, different types of data manipulation or for automating tasks, and it supports vector and bitmap output, including PDF, Postscript, SVG and EMF.

[ascl:2307.016] DataComb: Combining data for better images

DataComb combines radio interferometric and single dish observations and obtains quantitative measures of how different techniques perform to obtain better fidelity images. The package relies on CASA (ascl:1107.013) for the combinations and on AstroPy (ascl:1304.002) for making quantitative
comparisons between different images produced by different methods. Model images and simulations are also used to assess the different combination methods.

[ascl:2307.015] BOWIE: Gravitational wave binary signal analysis

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.

[ascl:2307.014] Synthetic LISA: Simulator for LISA-like gravitational-wave observatories

Synthetic LISA simulates the LISA science process at the level of scientific and technical requirements. The code generates synthetic time series of the LISA fundamental noises, as filtered through all the TDI observables, and provides a streamlined module to compute the TDI responses to gravitational waves, according to a full model of TDI, including the motion of the LISA array, and the temporal and directional dependence of the armlengths.

[ascl:2307.013] SIRENA: Energy reconstruction of X-ray photons for Athena X-IFU

SIRENA (Software Ifca for Reconstruction of EveNts for Athena X-IFU) reconstructs the energy of incoming X-ray photons after their detection in the X-IFU TES detector. It is integrated in the SIXTE (ascl:1903.002) end-to-end simulations environment where it currently runs over SIXTE simulated data. This is done by means of a tool called tesreconstruction, which is mainly a wrapper to pass a data file to the SIRENA tasks.

[ascl:2307.012] mnms: Map-based Noise ModelS

mnms (Map-based Noise ModelS) creates map-based models of Simons Observatory Atacama Cosmology Telescope (ACT) data. Each model supports drawing map-based simulations from data splits with independent realizations of the noise or equivalent, similar to an independent set of time-domain sims. In addition to the ability to create on-the-fly simulations, mnms also includes ready-made scripts for writing a large batch of products to disk in a dedicated SLURM job.

[ascl:2307.011] DiscVerSt: Vertical structure calculator for accretion discs around neutron stars and black holes

DiscVerSt calculates the vertical structure of accretion discs around neutron stars and black holes. Different classes represent the vertical structure for different types of EoS and opacity, temperature gradient and irradiation scheme; the code includes an interface for initializing the chosen structure type. DiscVerSt also contains functions to calculate S-curves and the vertical and radial profile of a stationary disc.

[submitted] Coniferest: Python package for active anomaly detection

Coniferest is a Python package designed for implementing anomaly detection algorithms and interactive active learning tools. The centerpiece of the package is an Isolation Forest algorithm, known for its superior scoring performance and multi-threading evaluation. This robust anomaly detection algorithm operates by constructing random decision trees.

In addition to the Isolation Forest algorithm, Coniferest also offers two modified versions for active learning: AAD Forest and Pineforest. The AAD Forest modifies the Isolation Forest by reweighting its leaves based on responses from human experts, providing a faster alternative to the ad_examples package.

On the other hand, Pineforest, developed by the SNAD team, employs a filtering algorithm that builds and dismantles trees with each new human-machine iteration step.

Coniferest provides a user-friendly interface for conducting interactive human-machine sessions, facilitating the use of these active anomaly detection algorithms. The SNAD team maintains and utilizes this package primarily for anomaly detection in the field of astronomy, with a particular focus on light-curve data from large time-domain surveys.

[ascl:2307.010] baccoemu: Cosmological emulators for large-scale structure statistics

baccoemu provides a collection of emulators for large-scale structure statistics over a wide range of cosmologies. The emulators provide fast predictions for the linear cold- and total-matter power spectrum, the nonlinear cold-matter power spectrum, and the modifications to the cold-matter power spectrum caused by baryonic physics in a wide cosmological parameter space, including dynamical dark energy and massive neutrinos.

[ascl:2307.009] pnautilus: Three-phase chemical code

The three-phase pnautilus chemical code finds the abundance of each species by solving rate equations for gas-phase and grain surface chemistries. It performs gas–grain simulations in which both the icy mantle and the surface are considered active, taking into account mantle photodissociation, diffusion, and reactions; the code also considers the competition among reaction, diffusion and evaporation.

[ascl:2307.008] 21cmvFAST: Adding dark matter-baryon relative velocities to 21cmFAST

21cmvFAST demonstrates that including dark matter (DM)-baryon relative velocities produces velocity-induced acoustic oscillations (VAOs) in the 21-cm power spectrum. Based on 21cmFAST (ascl:1102.023) and 21CMMC (ascl:1608.017), 21cmvFAST accounts for molecular-cooling haloes, which are expected to drive star formation during cosmic dawn, as both relative velocities and Lyman-Werner feedback suppress halo formation. This yields accurate 21-cm predictions all the way to reionization (z>~10).

[ascl:2307.007] AGNvar: Model spectral timing properties in active galactic nuclei

AGNvar calculates the expected reverberation signal in any given energy band, for a given spectral energy distribution (SED), assuming variable X-ray emission. The code predicts the shape of the re-processed continuum by modeling the time-averaged SED according to input parameters, which include geometry, mass, and mass accretion rate; generally the input parameters are based off typical XSPEC (ascl:9910.005) models. It evaluates the SED response to an input driving light-curve (assumed to originate in the X-ray corona) and creates a set of time-dependent SEDs. It then takes the results from the set of time-dependent SEDs and extracts the light-curve in a given band pass.

[ascl:2307.006] pyPplusS: Modeling exoplanets with rings

pyPplusS calculates the light curves for ringed, oblate or spherical exoplanets in both the uniform and limb darkened cases. It can constrain the oblateness of planets using photometric data only. This code can be used to model light curves of more complicated configurations, including multiple planets, oblate planets, moons, rings, and combinations of these, while properly and efficiently taking into account overlapping areas and limb darkening.

[ascl:2307.005] axionHMcode: Non-linear power spectrum calculator

axionHMcode computes the non-linear matter power spectrum in a mixed dark matter cosmology with ultra-light axion (ULA) component of the dark matter. This model uses some of the fitting parameters and is inspired by HMcode (ascl:1508.001). axionHMcode uses the full expanded power spectrum to calculate the non-linear power spectrum; it splits the axion overdensity into a clustered and linear component to take the non clustering of axions on small scales due to free-streaming into account.

[ascl:2307.004] ALF: Absorption line fitter

alf fits the absorption line optical—NIR spectrum. Initially written to constrain the stellar IMF in old massive galaxies, the code now also offers theoretical age and metallicity-dependent response functions covering 19 elements, nuisance parameters to capture uncertainties in stellar evolution, and parameters to capture uncertainties in the data, including modeling telluric absorption and sky line residuals. alf can fit stellar populations with metallicities from approximately -2.0 to +0.3 and performs well when fitting stellar populations ranging from metal-poor globular clusters to brightest cluster galaxies. The software works in continuum-normalized space and so does not make any use of the shape of the continuum (nor of corresponding photometry). Fitting is handled with emcee (ascl:1303.002); the code is MPI parallelized and runs efficiently on many processors, though fitting data with alf is time intensive.

[ascl:2307.003] RelicFast: Fast scale-dependent halo bias

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.

[ascl:2307.002] BE-HaPPY: Bias emulator for halo power spectrum

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.

[ascl:2307.001] Jdaviz: JWST astronomical data analysis tools in the Jupyter platform

Jdaviz provides data viewers and analysis plugins that can be flexibly combined as desired to create interactive applications. It offers Specviz (ascl:1902.011) for visualization and quick-look analysis of 1D astronomical spectra; Mosviz for visualization of astronomical spectra, including 1D and 2D spectra as well as contextual information, and Cubeviz for visualization of spectroscopic data cubes (such as those produced by JWST MIRI). Imviz, which provides visualization and quick-look analysis for 2D astronomical images, is also included. Jdaviz is designed with instrument modes from the James Webb Space Telescope (JWST) in mind, but the tool is flexible enough to read in data from many astronomical telescopes, and the documentation provides a complete table of all supported modes.

[ascl:2306.060] SCF-FDPS: Disk-halo systems simulator

The fast N-body code SCF-FDPS (Self-Consistent Field-Framework for Developing Particle Simulators) simulates disk-halo systems. It combines a self-consistent field (SCF) code, which provides scalability, and a tree code that is parallelized using the Framework for Developing Particle Simulators (FDPS) (ascl:1604.011). SCF-FDPS handles a wide variety of halo profiles and can be used to study extensive dynamical problems of disk-halo systems.

[ascl:2306.059] BOXFIT: Gamma-ray burst afterglow light curve generator

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.

[ascl:2306.058] GER: Global Extinction Reduction

The Global Extinction Reduction IDL codes compare optical photometry from the twin Gemini North and South Multi-Object Spectrographs (GMOS-N and GMOS-S) against the expected worsening of atmospheric transparency due to global climate change. Data from the Gemini instruments are first reduced by DRAGONS (ascl:1811.002). GER then calibrates them against the Sloan Digital Sky Survey (SDSS) and Gaia G-band catalogs; image rotation and alignment is accomplished via identification of sufficiently-bright stars in Gaia. A simple model of Gemini and their site characteristics is generated, including meteorology, cloudy-fractions, number of reflections, dates of re-coatings modulated by rate of efficiency decay, together with response of detectors and associated zeropoints, and can be compared with the decline of transparency due to rising temperature and associated humidity increase.

[ascl:2306.057] pybranch: Calculate experimental branching fractions and transition probabilities from atomic spectra

pybranch calculates experimental branching fractions and transition probabilities from measurements of atomic spectra. Though the program is usually used with spectral line lists from intensity-calibrated spectra from Fourier transform spectrometers, it can in principle be used with any calibrated spectra that meet the input requirements. pybranch takes a set of linelists, computes a weighted average branching fraction (Fki) for each line, combines these branching fractions with the level lifetime to obtain the transition probability, and then prints the calibrated intensities and S/N ratios for all the lines observed from a particular upper level in each spectrum. One line can be chosen to use as a reference to put all of the intensities on the same scale. pybranch can use calculated transition probabilities to calculate a residual from lines that have not been observed.

[ascl:2306.056] PSFMachine: Toolkit for doing PSF photometry

PSFMachine creates models of instrument effective Point Spread Functions (ePSFs), also called Pixel Response Functions (PRFs). These models are then used to fit a scene in a stack of astronomical images. PSFMachine is able to quickly derive photometry from stacks of Kepler and TESS images and separate crowded sources.

[ascl:2306.055] ESSENCE: Evaluate spatially correlated noise in interferometric images

ESSENCE (Evaluating Statistical Significance undEr Noise CorrElation) evaluates the statistical significance of image analysis and signal detection under correlated noise in interferometric images (e.g., ALMA, NOEMA). It measures the noise autocorrelation function (ACF) to fully characterize the statistical properties of spatially correlated noise in the interferometric image, computes the noise in the spatially integrated quantities (e.g., flux, spectrum) with a given aperture, and simulates noise maps with the same correlation property. ESSENSE can also construct a covariance matrix from noise ACF, which can be used for a 2d image or 3d cube model fitting.

[ascl:2306.054] threepoint: Covariance of third-order aperture statistics

threepoint models the third-order aperture statistics, the natural components of the shear three-point correlation function and the covariance of third-order aperture statistics. Third-order weak lensing statistics extract cosmological information in the non-Gaussianity of the cosmic large-scale structure, making them a promising tool for cosmological analyses.

[ascl:2306.053] TiDE: Light curves and spectra of tidal disruption events

TiDE (TIdal Disruption Event) computes the light curves or spectrum of tidal disruption events. Written in C++, it can compute the monochromatic light curve without diffusion, including the total luminosity, wind luminosity and disk luminosity, and the monochromatic light curve with diffusion. TiDE can also model the bolometric luminosity and calculate the spectrum at a given time, including the wind luminosity and disk luminosity. This code can be used to explore the possible parameter space and reveal potential biases caused by the model assumptions, and can be extended with new models, allowing one to compare and test different prescriptions and model assumptions under the same circumstances.

[ascl:2306.052] kilopop: Binary neutron star population of optical kilonovae

kilopop produces binary neutron star kilonovae in the grey-body approximation. It can also create populations of these objects useful for forecasting detection and testing observing scenarios. Additionally, it uses an emulator for the grey-opacity of the material calibrated against a suite of numerical radiation transport simulations with the code SuperNu (ascl:2103.019).

[ascl:2306.051] Hitomi: Cosmological analysis of anisotropic galaxy distributions

Hitomi provides a comprehensive set of codes for cosmological analysis of anisotropic galaxy distributions using two- and three-point statistics: two-point correlation function (2PCF), power spectrum, three-point correlation function (3PCF), and bispectrum. The code can measure the Legendre-expanded 2PCF and power spectrum from an observed sample of galaxies, and can measure the 3PCF and bispectrum expanded using the Tripolar spherical harmonic (TripoSH) function. Hitomi is basically a serial code, but can also implement MPI parallelization. Hitomi uses MPI to read multiple different input parameters simultaneously.

[ascl:2306.050] SubgridClumping: Clumping factor for large low-resolution N-body simulations

SubgridClumping derives the parameters for the global, in-homogeneous and stochastic clumping model and then computes the clumping factor for large low-resolution N-body simulations smoothed on a regular grid. Written for the CUBEP3M simulation, the package contains two main modules. The first derives the three clumping model parameters for a given small high-resolution simulation; the second computes a clumping factor cube (same mesh-size as input) for the three models for the given density field of a large low-resolution simulation.

[ascl:2306.049] ARPACK-NG: Large scale eigenvalue problem solver

ARPACK-NG provides a common repository with maintained versions and a test suite for the ARPACK (ascl:1311.010) code, which is no longer updated; it is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems. ARPACK-NG offers routines for banded matrices, singular value decomposition, single and double precision real arithmetic versions for symmetric, non-symmetric standard or generalized problems, and a reverse communication interface (RCI). It also provides example driver routines that may be used as templates to implement numerous shift-invert strategies for all problem types, data types and precision, in addition to other tools. The ARPACK-NG project, started by Debian, Octave, and Scilab, is now a community project maintained by volunteers.

[ascl:2306.048] MG-PICOLA: Simulating cosmological structure formation

MG-PICOLA is a modified version of L-PICOLA (ascl:1507.004) that extends the COLA approach for simulating cosmological structure formation to theories that exhibit scale-dependent growth. It can compute matter power-spectra (CDM and total), redshift-space multipole power-spectra P0,P2,P4 and do halofinding on the fly.

[ascl:2306.047] COLASolver: Particle-Mesh N-body code

COLASolver creates Particle-Mesh (PM) N-body simulations; the code is fast and very flexible, and can compute a wide range of models. For models with complex dynamics (screened models), it provides several options from doing it exactly to approximate but fast to just simulating linear theory equations. Every time-consuming operation is parallelized over MPI and OpenMP. It uses a slab-based parallelization that works well for fast approximate (COLA) simulations but does not perform as well for high resolution simulations. COLASolver can also be used as an analysis code for results from other simulations.

[ascl:2306.046] CHIPS: Circumstellar matter and light curves of interaction-powered transients simulator

CHIPS (Complete History of Interaction-Powered Supernovae) simulates the circumstellar matter and light curves of interaction-powered transients. Coupled with MESA (ascl:1010.083), the combined codes can obtain the circumstellar matter profile and light curves of the interaction-powered supernovae. CHIPS generates a realistic CSM from a model-agnostic mass eruption calculation, which can serve as a reference for observers to compare with various observations of the CSM. The code can also generate bolometric light curves from CSM interaction, which can be compared with observed light curves. The calculation of mass eruption and light curve typically takes respectively half a day and half an hour on modern CPUs.

[ascl:2306.045] nuPyProp: Propagate neutrinos through the earth

nuPyProp simulates tau neutrino and muon neutrino interactions in the Earth and predicts the spectrum of the τ-leptons and muons that emerge. The code produces tables of charged lepton exit probabilities and energies that can be used directly or as inputs to nuSpaceSim (ascl:2306.043), which is designed to simulate optical and radio signals from extensive air showers induced by the emerging charged leptons.

[ascl:2306.044] nuSpaceSim: Cosmic neutrino simulation

nuSpaceSim simulates upward-going extensive air showers caused by neutrino interactions with the atmosphere. It is an end-to-end, neutrino flux to space-based signal detection, modeling tool for the design of sub-orbital and space-based neutrino detection experiments. This comprehensive suite of modeling packages accepts an experimental design input and then models the experiment's sensitivity to both the diffuse, cosmogenic neutrino flux as well as astrophysical neutrino transient events, such as that postulated from binary neutron star (BNS) mergers. nuSpaceSim calculates the tau neutrino acceptance for the Optical Cherenkov technique; tau propagation is interpolated using included data tables from nupyprop (ascl:2306.044). The simulation is parameterized by an input XML configuration file, with settings for detector characteristics and global parameters; nuSpaceSim also provides a python API for programmatic access.

[ascl:2306.043] SHERLOCK: Explore Kepler, K2, and TESS data

The end-to-end SHERLOCK (Searching for Hints of Exoplanets fRom Lightcurves Of spaCe-based seeKers) pipeline allows users to explore data from space-based missions to search for planetary candidates. It can recover alerted candidates by the automatic pipelines such as SPOC and the QLP, Kepler objects of interest (KOIs) and TESS objects of interest (TOIs), and can search for candidates that remain unnoticed due to detection thresholds, lack of data exploration, or poor photometric quality. SHERLOCK has six different modules to perform its tasks; these modules can be executed by filling in an initial YAML file with some basic information and using a few lines of code sequentially to pass from one step to the next. Alternatively, the user may provide with the light curve in a csv file, where the time, normalized flux, and flux error are provided in columns in comma-separated format.

[ascl:2306.042] CONDUCT: Electron transport coefficients of magnetized stellar plasmas

CONDUCT calculates all components of kinetic tensors in fully ionized electron-ion plasmas at arbitrary magnetic field. It employs a thermal averaging with the Fermi distribution function and can be used when electrons are partially degenerate; it provides, along with the electrical and thermal conductivities, also thermopower (thermoelectric coefficient). CONDUCT takes into account collisions of the electrons with ions and (in solid phase) charged impurities as well as quantum effects on ionic motion in the solid phase. The code's outputs are the longitudinal, transverse, and off-diagonal (Hall) components of electrical and thermal conductivity tensors as well as the components of thermoelectric tensor.

[ascl:2306.041] COFFE: COrrelation Function Full-sky Estimator

COFFE (COrrelation Function Full-sky Estimator) computes quantities in linear perturbation theory. It computes the full-sky and flat-sky 2-point correlation function (2PCF) of galaxy number counts, taking into account all of the effects, including density, RSD, and lensing. It also determines the full-sky, flat-sky, and redshift-averaged multipoles of the 2PCF, and the flat-sky Gaussian covariance matrix of the multipoles of the 2PCF.

[ascl:2306.040] PEPITA: Prediction of Exoplanet Precisions using Information in Transit Analysis

PEPITA (Prediction of Exoplanet Precisions using Information in Transit Analysis) makes predictions for the precision of exoplanet parameters using transit light-curves. The code uses information analysis techniques to predict the best precision that can be obtained by fitting a light-curve without actually needing to perform the fit, thus allowing more efficient planning of observations or re-observations.

[ascl:2306.039] GRChombo: Numerical relativity simulator

GRChombo performs numerical relativity simulations. It uses Chombo (ascl:1202.008) for adaptive mesh refinement and can evolve standard spacetimes such as binary black hole mergers and scalar collapses into black holes. The code supports non-trivial many-boxes-in-many-boxes mesh hierarchies and massive parallelism and evolves the Einstein equation using the standard BSSN formalism. GRChombo is written in C++14 and uses hybrid MPI/OpenMP parallelism and vector intrinsics to achieve good performance.

[ascl:2306.038] FacetClumps: Molecular clump detection algorithm based on Facet model

FacetClumps extracts and analyses clumpy structure in molecular clouds. Written in Python and based on the Gaussian Facet model, FacetClumps extracts signal regions using morphology, and segments the signal regions into local regions with a gradient-based method. It then applies a connectivity-based minimum distance clustering method to cluster the local regions to the clump centers. FacetClumps automatically adjusts its parameters to local situations to improve adaptability, and is optimized to detect faint and overlapping clumps.

[ascl:2306.037] CADET: X-ray cavity detection tool

The machine learning pipeline CADET (CAvity DEtection Tool) finds and size-estimates arbitrary surface brightness depressions (X-ray cavities) on noisy Chandra images of galaxies. The pipeline is a self-standing Python script and inputs either raw Chandra images in units of counts (numbers of captured photons) or normalized background-subtracted and/or exposure-corrected images. CADET saves corresponding pixel-wise as well as decomposed cavity predictions in FITS format and also preserves the WCS coordinates; it also outputs a PNG file showing decomposed predictions for individual scales.

[ascl:2306.036] IDEFIX: Astrophysical fluid dynamics

Idefix solves non-relativistic HD and MHD equations on various grid geometries. Based on a Godunov finite-volume method, this astrophysical flows code includes a wide choice of solvers and several modules, including constrained transport, orbital advection, and non-ideal MHD, to address complex astrophysical and fluid dynamics applications. Written in C++, Idefix relies on the Kokkos meta-programming library to guarantee performance portability on a wide variety of architectures.

[ascl:2306.035] CONCEPT: COsmological N-body CodE in PyThon

CONCEPT (COsmological N-body CodE in PyThon) simulates cosmological structure formation. It can simulate matter particles evolving under self-gravity in an expanding background. The code offers multiple gravitational solvers and has adaptive time integration built in. In addition to particles, CONCEPT also evolves fluids at various levels of non-linearity, providing the means for the inclusion of more exotic species such as massive neutrinos, as well as for simulations consistent with general relativistic perturbation theory. Various non-standard species, such as decaying cold dark matter, are fully supported. CONCEPT includes a sophisticated initial condition generator and can output snapshots, power spectra, bispectra ,and several kinds of renders.

[ascl:2306.034] COLT: Monte Carlo radiative transfer and simulation analysis toolkit

COLT (Cosmic Lyman-alpha Transfer) is a Monte Carlo radiative transfer (MCRT) solver for post-processing hydrodynamical simulations on arbitrary grids. These include a plane parallel slabs, spherical geometry, 3D Cartesian grids, adaptive resolution octrees, unstructured Voronoi tessellations, and secondary outputs. COLT also includes several visualization and analysis tools that exploit the underlying ray-tracing algorithms or otherwise benefit from an efficient hybrid MPI + OpenMP parallelization strategy within a flexible C++ framework.

[ascl:2306.033] lasso_spectra: Predict properties from galaxy spectra using Lasso regression

lasso_spectra fits Lasso regression models to data, specifically galaxy spectra. It contains two classes for performing the actual model fitting. GeneralizedLasso is a tensorflow implementation of Lasso regression, which includes the ability to use link functions. SKLasso is a wrapper around the scikit-learn Lasso implementation intended to give the same syntax as GeneralizedLasso. It is much faster and more reliable, but does not support generalized linear models.

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