HERACLES is a 3D hydrodynamical code used to simulate astrophysical fluid flows. It uses a finite volume method on fixed grids to solve the equations of hydrodynamics, MHD, radiative transfer and gravity. This software is developed at the Service d'Astrophysique, CEA/Saclay as part of the COAST project and is registered under the CeCILL license. HERACLES simulates astrophysical fluid flows using a grid based Eulerian finite volume Godunov method. It is capable of simulating pure hydrodynamical flows, magneto-hydrodynamic flows, radiation hydrodynamic flows (using either flux limited diffusion or the M1 moment method), self-gravitating flows using a Poisson solver or all of the above. HERACLES uses cartesian, spherical and cylindrical grids.

The hera_opm package provides a convenient and flexible framework for developing data analysis pipelines for operating on a sequence of input files. Though developed for application to the Hydrogen Epoch of Reionization Array (HERA), it is a general package that can be applied to any workflow designed to apply a series of analysis steps to any type of files. It is also portable, operating both on a diversity of computer clusters with batch submission systems and local machines.

HENDRICS, a rewrite and update to MaLTPyNT (ascl:1502.021), contains command-line scripts based on Stingray (ascl:1608.001) to perform a quick-look (spectral-)timing analysis of X-ray data, treating the gaps in the data due, e.g., to occultation from the Earth or passages through the SAA, properly. Despite its original main focus on NuSTAR, HENDRICS can perform standard aperiodic timing analysis on X-ray data from, in principle, any other satellite, and its features include power density and cross spectra, time lags, pulsar searches with the Epoch folding and the Z_n^2 statistics, color-color and color-intensity diagrams. The periodograms produced by HENDRICS (such as a power density spectrum or a cospectrum) can be saved in a format compatible with XSPEC (ascl:9910.005) or ISIS (ascl:1302.002).

HELIOS, a radiative transfer code, is constructed for studying exoplanetary atmospheres. The model atmospheres of HELIOS are one-dimensional and plane-parallel, and the equation of radiative transfer is solved in the two-stream approximation with non-isotropic scattering. Though HELIOS can be used alone, the opacity calculator HELIOS-K (ascl:1503.004) can be used with it to provide the molecular opacities.

Helios-r2 performs atmospheric retrieval of brown dwarf and exoplanet spectra. It uses a Bayesian statistics approach by employing a nested sampling method to generate posterior distributions and calculate the Bayesian evidence. The nested sampling itself is done by Multinest (ascl:1109.006). The computationally most demanding parts of the model have been written in NVIDIA's CUDA language for an increase in computational speed. Successful applications include retrieval of brown dwarf emission spectra and secondary eclipse measurements of exoplanets.

HELIOS-K is an opacity calculator for exoplanetary atmospheres. It takes a line list as an input and computes the line shapes of an arbitrary number of spectral lines (~millions to billions). HELIOS-K is capable of computing 100,000 spectral lines in 1 second; it is written in CUDA, is optimized for graphics processing units (GPUs), and can be used with the HELIOS radiative transfer code (ascl:1807.009).

HelioPy provides a set of tools to download and read in data, and carry out other common data processing tasks for heliospheric and planetary physics. It handles a wide variety of solar and satellite data and builds upon the SpiceyPy package (ascl:1903.016) to provide an accessible interface for performing orbital calculations. It has also implemented a framework to perform transformations between some common coordinate systems.

HELA performs atmospheric retrieval on exoplanet atmospheres using a Random Forest algorithm. The code has two stages: training (which includes testing), and predicting. It requires a training set that matches the format of the data to be analyzed, with the same number of points and a sample spectrum for each parameter. The number of trees used and the number of jobs are editable. The HELA package includes a training set and data as examples.

Heimdall uses direct, tree, and sub-band dedispersion algorithms on massively parallel computing architectures (GPUs) to speed up real-time detection of radio pulsar and other transient events.

HeatingRate calculates the nuclear heating rates [erg/s/g] of beta-decay, alpha-decay, and spontaneous fission of r-process nuclei, taking into account for thermalization of gamma-rays and charged decay products in r-process ejecta. It uses the half-lives and injection energy spectra from an evaluated nuclear data library (ENDF/B-VII.1). Each heating rate is computed for given abundances, ejecta mass, velocity, and density profile. HeatingRate also computes the bolometric light curve and the evolution of the effective temperature for given abundances, ejecta mass, velocity, and density profile assuming opacities independent of the wavelength.

HEATCVB is a stand-alone Fortran 77 subroutine that estimates the local volumetric coronal heating rate with four required inputs: the radial distance r, the wind speed u, the mass density ρ, and the magnetic field strength |B0|. The primary output is the heating rate Qturb at the location defined by the input parameters. HEATCVB also computes the local turbulent dissipation rate of the waves, γ = Qturb/(2UA).

HEASOFT combines XANADU, high-level, multi-mission software for X-ray astronomical spectral, timing, and imaging data analysis tasks, and FTOOLS (ascl:9912.002), general and mission-specific software to manipulate FITS files, into one package. It also contains contains the NuSTAR subpackage of tasks, NuSTAR Data Analysis Software (NuSTARDAS). The source code for the software can be downloaded; precompiled executables for the most widely used computer platforms are also available for download. As an additional service, HEAsoft tasks can be directly from a web browser via WebHera.

HEARSAY computes simulations of the causal contacts between emitters in the Galaxy. It implements the Stochastic Constrained Causal Contact Network (SC3Net) model and explores the parameter space of the model for the emergence of communicating nodes through Monte Carlo simulations and analyzes their causal connections. This model for the abundance and duration of civilizations is based on minimal assumptions and three free parameters, with focus on the statistical properties of empirical models instead of an interpretable model with variables to be determined by observation.

Healvis simulates radio interferometric visibility off of HEALPix shells. It generates a flat-spectrum and a GSM model and computes visibilities, and can simulates visibilities given an Observation Parameter YAML file. Healvis can perform partial frequency simulations in serial to minimize instantaneous memory loads.

healpy handles pixelated data on the sphere. It is based on the Hierarchical Equal Area isoLatitude Pixelization (HEALPix) scheme and bundles the HEALPix (ascl:1107.018) C++ library. healpy provides utilities to convert between sky coordinates and pixel indices in HEALPix nested and ring schemes and find pixels within a disk, a polygon or a strip in the sky. It can apply coordinate transformations between Galactic, Ecliptic and Equatorial reference frames, apply custom rotations either to vectors or full maps, and read and write HEALPix maps to disk in FITS format. healpy also includes utilities to upgrade and downgrade the resolution of existing HEALPix maps and transform maps to Spherical Harmonics space and back using multi-threaded C++ routines, among other utilities.

Healpix.jl is a Julia-only port of the C/C++/Fortran/Python HEALPix library (ascl:1107.018), which implements a hierarchical pixelization of the sphere in equal-area pixels. Much like the original library, Healpix.jl supports two enumeration schemes for the pixels (RING and NESTED) and implements an optimized computation of the generalized Fourier transform using spherical harmonics, binding libsharp2 (ascl:1402.033). In addition, Healpix.jl provides four additional features: 1.) it fully supports Windows systems, alongside the usual Linux and MAC OS X machines; 2.) it uses Julia's strong typesystem to prevent several bugs related to mismatches in map ordering (e.g., combining a RING map with a NESTED map); 3.) it uses a versatile memory layout so that map bytes can be stored in shared memory objects or on GPUs; and 4.) it implements an elegant and general way to signal missing values in maps.

HEALPix is an acronym for Hierarchical Equal Area isoLatitude Pixelization of a sphere. As suggested in the name, this pixelization produces a subdivision of a spherical surface in which each pixel covers the same surface area as every other pixel. Another property of the HEALPix grid is that the pixel centers occur on a discrete number of rings of constant latitude, the number of constant-latitude rings is dependent on the resolution of the HEALPix grid.

HEADSS (HiErArchical Data Splitting and Stitching) facilitates clustering at scale, unlike clustering algorithms that scale poorly with increased data volume or that are intrinsically non-distributed. HEADSS automates data splitting and stitching, allowing repeatable handling, and removal, of edge effects. Implemented in conjunction with scikit's HDBSCAN, the code achieves orders of magnitude reduction in single node memory requirements for both non-distributed and distributed implementations, with the latter offering similar order of magnitude reductions in total run times while recovering analogous accuracy. HEADSS also establishes a hierarchy of features by using a subset of clustering features to split the data.

The Hierarchical Data System (HDS) is a file-based hierarchical data system designed for the storage of a wide variety of information. It is particularly suited to the storage of large multi-dimensional arrays (with their ancillary data) where efficient access is needed. It is a key component of the Starlink software collection (ascl:1110.012) and is used by the Starlink N-Dimensional Data Format (NDF) library (ascl:1411.023).

HDS organizes data into hierarchies, broadly similar to the directory structure of a hierarchical filing system, but contained within a single HDS container file. The structures stored in these files are self-describing and flexible; HDS supports modification and extension of structures previously created, as well as functions such as deletion, copying, and renaming. All information stored in HDS files is portable between the machines on which HDS is implemented. Thus, there are no format conversion problems when moving between machines. HDS can write files in a private binary format (version 4), or be layered on top of HDF5 (version 5).

HDMSpectra computes the decay spectrum for dark matter with masses above the scale of electroweak symmetry breaking, down to Planck scale and including all relevant electroweak interactions. The code determines the distribution of stable states for photons, neutrinos, positrons, and antiprotons.

HCGrid maps non-uniform radio astronomy data onto a uniformly distributed grid using a convolution-based algorithm on CPU-GPU heterogeneous platforms. The package has three modules; the initialization module initializes parameters needed for the calculation process, such as setting the size of the sampling space and output resolution. The gridding module uses a parallel ordering algorithm to pre-order the sampling points based on HEALPix on the CPU platform and uses an efficient two-level lookup table to speed up the acquisition of sampling points; it then accelerates convolution by using the high parallelism of GPU and through related performance optimization strategies based on CUDA architecture to further improve the gridding performance. The third module processes the results; it visualizes the gridding and exports the final products as FITS files.

HBT+ is a hybrid subhalo finder and merger tree builder for cosmological simulations. It comes as an MPI edition that can be run on distributed clusters or shared memory machines and is MPI/OpenMP parallelized, and also as an OpenMP edition that can be run on shared memory machines and is only OpenMP parallelized. This version is more memory efficient than the MPI branch on shared memory machines, and is more suitable for analyzing zoomed-in simulations that are difficult to balance on distributed clusters. Both editions support hydro simulations with gas/stars.

HBT is a Hierarchical Bound-Tracing subhalo finder and merger tree builder, for numerical simulations in cosmology. It tracks haloes from birth and continues to track them after mergers, finding self-bound structures as subhaloes and recording their merger histories as merger trees.

HBSGSep (Hierarchical Bayesian Star-Galaxy Separations) classifies stars and galaxies photometrically by fitting templates and hierarchically learning their prior weights. The hierarchical Bayesian algorithms are unsupervised and do not use a training set nor are priors set in advance of running the algorithms; the priors for the templates are inferred from the data themselves.

Hazma enables indirect detection of sub-GeV dark matter. It computes gamma-ray and electron/positron spectra from dark matter annihilations, sets limits on sub-GeV dark matter using existing gamma-ray data, and determines the discovery reach of future gamma-ray detectors. The code also derives accurate CMB constraints. Hazma comes with several sub-GeV dark matter models, for which it provides functions to compute dark matter annihilation cross sections and mediator decay widths. A variety of low-level tools are provided to make it straightforward to define new models.

A big challenge in solar and stellar physics in the coming years will be to decipher the magnetism of the solar outer atmosphere (chromosphere and corona) along with its dynamic coupling with the magnetic fields of the underlying photosphere. To this end, it is important to develop rigorous diagnostic tools for the physical interpretation of spectropolarimetric observations in suitably chosen spectral lines. HAZEL is a computer program for the synthesis and inversion of Stokes profiles caused by the joint action of atomic level polarization and the Hanle and Zeeman effects in some spectral lines of diagnostic interest, such as those of the He I 1083.0 nm and 587.6 nm (or D3) multiplets. It is based on the quantum theory of spectral line polarization, which takes into account in a rigorous way all the relevant physical mechanisms and ingredients (optical pumping, atomic level polarization, level crossings and repulsions, Zeeman, Paschen-Back and Hanle effects). The influence of radiative transfer on the emergent spectral line radiation is taken into account through a suitable slab model. The user can either calculate the emergent intensity and polarization for any given magnetic field vector or infer the dynamical and magnetic properties from the observed Stokes profiles via an efficient inversion algorithm based on global optimization methods.

HAYASHI (Halo-level AnalYsis of the Absorption Signal in HI) computes the number of absorption features of the 21cm forest using a semianalytic formalism. It includes the enhancement of the signal due to the presence of substructures within minihalos and supports non-standard cosmologies with impact in the large scale structure, such as warm dark matter and primordial black holes. HAYASHI is written in Python3 and uses the cosmological computations package Colossus (ascl:1501.016).

HawkingNet searches for Hawking points in large Cosmic Microwave Background (CMB) data sets. It is based on the deep residual network ResNet18 and consists of eighteen neural layers. Written in Paython, HawkingNet inputs the CMB data, processes the data through its internal network trained for data classification, and outputs the result in a form of a classification score that indicates how confident it is that a Hawking point is contained in the image patch.

HARMPI is a parallel, 3D version of HARM (ascl:1209.005), which solves hyperbolic partial differential equations in conservative form using high-resolution shock-capturing techniques. The code is parallelized using MPI and is fully operational in 3D. HARMPI, like HARM, is capable of using non-uniform grids and solves the relativistic magnetohydrodynamic equations of motion on a stationary black hole spacetime in Kerr-Schild coordinates to evolve an accretion disk model.

Harmony is a general numerical scheme for evaluating MBS emission and absorption coefficients for both polarized and unpolarized light in a plasma with a general distribution function.

harmonic learns an approximate harmonic mean estimator (referred to as a "learnt harmonic mean estimator") from posterior distribution samples to compute the marginal likelihood required for Bayesian model selection. Using a large number of independent Markov chain Monte Carlo (MCMC) chains from another package such as emcee (ascl:1303.002), harmonic uses importance sampling to learn a new target distribution in order to optimize an approximate harmonic estimator while minimizing its variance.

Harmonia combines clustering statistics decomposed in spherical and Cartesian Fourier bases for large-scale galaxy clustering likelihood analysis. Optimal weighting schemes for spherical Fourier analysis can also be readily implemented using the code.

HARM uses a conservative, shock-capturing scheme for evolving the equations of general relativistic magnetohydrodynamics. The fluxes are calculated using the Harten, Lax, & van Leer scheme. A variant of constrained transport, proposed earlier by Tóth, is used to maintain a divergence-free magnetic field. Only the covariant form of the metric in a coordinate basis is required to specify the geometry. On smooth flows HARM converges at second order.

hardCORE calculates the minimum, maximum, and marginal core radius fractions (CRFmin, CRFmax, CRFmarg) for a solid exoplanet using only its mass and radius. Written in Python, the code is an efficient tool that is extremely fast to execute and perform inversions.

HAOS-DIPER works with and manipulates data for neutral atoms and atomic ions to understand radiation emitted by some space plasmas, notably the solar atmosphere and stellar atmospheres. HAOS-DIPER works with quantum numbers for atomic levels, enabling it to perform tasks otherwise difficult or very tedious, including a variety of data checks, calculations based upon the atomic numbers, and searching and manipulating data based upon these quantum numbers. HAOS-DIPER handles conditions from LTE to coronal-like conditions, in a manner controlled by one system variable !REGIME, and has some capability for estimating data for which no accurate parameters are available and for accounting for the effects of missing atomic levels.

hankl implements the FFTLog algorithm in lightweight Python code. The FFTLog algorithm can be thought of as the Fast Fourier Transform (FFT) of a logarithmically spaced periodic sequence (= Hankel Transform). hankl consists of two modules, the General FFTLog module and the Cosmology one. The latter is suited for modern cosmological application and relies heavily on the former to perform the Hankel transforms. The accuracy of the method usually improves as the range of integration is enlarged; FFTlog prefers an interval that spans many orders of magnitude. Resolution is important, as low resolution introduces sharp features which in turn causes ringing.

The Hammurabi code is a publicly available C++ code for generating mock polarized observations of Galactic synchrotron emission with telescopes such as LOFAR, SKA, Planck, and WMAP, based on model inputs for the Galactic magnetic field (GMF), the cosmic-ray density distribution, and the thermal electron density. The Hammurabi code allows one to perform simulations of several different data sets simultaneously, providing a more reliable constraint of the magnetized ISM.

HAM solves non-relativistic hyperbolic partial differential equations in conservative form using high-resolution shock-capturing techniques. This version of HAM has been configured to solve the magnetohydrodynamic equations of motion in axisymmetry to evolve a shearing box model.

Halotools builds and tests models of the galaxy-halo connection and analyzes catalogs of dark matter halos. The core functions of the package include fast generation of synthetic galaxy populations using HODs, abundance matching, and related methods; efficient algorithms for calculating galaxy clustering, lensing, z-space distortions, and other astronomical statistics; a modular, object-oriented framework for designing galaxy evolution models; and end-to-end support for reducing halo catalogs and caching them as hdf5 files.

halomod calculates cosmological halo model and HOD quantities. It is built on HMF (ascl:1412.006); it retains that code's features and provides extended components for the halo model, including numerous halo bias models, including scale-dependent bias, basic concentration-mass-redshift relations, and several plug-and-play halo-exclusion models. halomod includes built-in HOD parameterizations and halo profiles, support for WDM models, and all basic quantities such as 3D correlations and power spectra, and also several derived quantities such as effective bias and satellite fraction. In addition, it offers a simple routine for populating a halo catalog with galaxies via a HOD. halomod is flexible and modular, making it easily extendable.

HaloGraphNet predicts halo masses from simulations using Graph Neural Networks. Given a dark matter halo and its galaxies, this software creates a graph with information about the 3D position, stellar mass and other properties. It then trains a Graph Neural Network to predict the mass of the host halo. Data are taken from the CAMELS hydrodynamic simulations.

Halogen, written in C, generates multimass spherically symmetric initial conditions for N-body simulations. A large family of radial density profiles is supported. The initial conditions are sampled from the full distribution function.

HaloGen computes all auto and cross spectra and halo model trispectrum in simple configurations. This modular halo model code computes 3d power spectra, and the corresponding projected 2d power spectra in the Limber and flat sky approximations. The observables include matter density, galaxy lensing, CMB lensing, thermal Sunyaev-Zel'dovich, cosmic infrared background, tracers with any dn/dz, b(z) and HOD.

HALOGEN generates approximate synthetic halo catalogs. Written in C, it decomposes the problem of generating cosmological tracer distributions (eg. halos) into four steps: generating an approximate density field, generating the required number of tracers from a CDF over mass, placing the tracers on field particles according to a bias scheme dependent on local density, and assigning velocities to the tracers based on velocities of local particles. It also implements a default set of four models for these steps. HALOGEN uses 2LPTic (ascl:1201.005) and CUTE (ascl:1505.016); the software is flexible and can be adapted to varying cosmologies and simulation specifications.

HaloFlow uses a machine learning approach to infer Mh and stellar mass, M∗, using grizy band magnitudes, morphological properties quantifying characteristic size, concentration, and asymmetry, total measured satellite luminosity, and number of satellites.

We perform N-body simulations of theories with infinite-volume extra dimensions, such as the Dvali-Gabadadze-Porrati (DGP) model and its higher-dimensional generalizations, where 4D gravity is mediated by massive gravitons. The longitudinal mode of these gravitons mediates an extra scalar force, which we model as a density-dependent modification to the Poisson equation. This enhances gravitational clustering, particularly on scales that have undergone mild nonlinear processing. While the standard non-linear fitting algorithm of Smith et al. overestimates this power enhancement on non-linear scales, we present a modified fitting formula that offers a remarkably good fit to our power spectra. Due to the uncertainty in galaxy bias, our results are consistent with precision power spectrum determinations from galaxy redshift surveys, even for graviton Compton wavelengths as small as 300 Mpc. Our model is sufficiently general that we expect it to capture the phenomenology of a wide class of related higher-dimensional gravity scenarios.

HALOFIT provides an explanatory framework for galaxy bias and clustering and has been incorporated into CMB packages such as CMBFAST (ascl:9909.004) and CAMB (ascl:1102.026). It attains a reasonable level of precision, though the halo model does not match N-body data perfectly. The code is written in Fortran 77. HALOFIT tends to underpredict the power on the smallest scales in standard LCDM universes (although HALOFIT was designed to work for a much wider range of power spectra); its accuracy can be improved by using a supplied correction.

HaloAnalysis reads and analyzes halo/galaxy catalogs, generated from Rockstar (ascl:1210.008) or AHF (ascl:1102.009), and merger trees generated from Consistent Trees (ascl:1210.011). Written in Python, it offers the following functionalities: reads halo/galaxy/tree catalogs from multiple file formats; assigns baryonic particles and galaxy properties to dark-matter halos; combines and re-generates halo/galaxy/tree files in hdf5 format; analyzes properties of halos/galaxies; and selects halos to generate zoom-in initial conditions. The code includes a tutorial in the form of a Jupyter notebook.

HAFFET (Hybrid Analytic Flux FittEr for Transients) analyzes supernovae photometric and spectroscopic data. It handles observational data for a set of targets, estimates their physical parameters, and visualizes the population of inferred parameters. HAFFET defines two classes, snobject for data and fittings for one specific object, and snelist to organize the overall running for a list of objects. The HAFFET package includes utilities for downloading SN data from online sources, intepolating multi band lightcurves, characterizing the first light and rising of SNe with power law fits, and matching epochs of different bands. It can also calculate colors, and/or construct the spectral energy distribution (SED), estimate bolometric LCs and host galaxy extinction, fit the constructed bolometric lightcurves to different models, and identify and fit the absorption minima of spectral lines, in addition to performing other tasks. In addition to utilizing the built-in models, users can add their own models or import models from other python packages.

HADES analyzse dust levels in simulated CMB galactic dust maps with realistic experimental noise and lensing configurations. It allows detection of dust via its anisotropy properties in CMB B-modes. It also includes techniques for computing null-tests and a rudimentary technique for dedusting.