Results 1001-1050 of 2516 (2473 ASCL, 43 submitted)
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.
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).
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.
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)
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.
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.
hfof is a 3-d friends-of-friends (FoF) cluster finder with Python bindings based on a fast spatial hashing algorithm that identifies connected sets of points where the point-wise connections are determined by a fixed spatial distance. This technique sorts particles into fine cells sufficiently compact to guarantee their cohabitants are linked, and uses locality sensitive hashing to search for neighboring (blocks of) cells. Tests on N-body simulations of up to a billion particles exhibit speed increases of factors up to 20x compared with FOF via trees, and is consistently complete in less than the time of a k-d tree construction, giving it an intrinsic advantage over tree-based methods.
hfs_fit performs parameter optimization in the analysis of emission line hyperfine structure (HFS). The code uses a simulated annealing algorithm to optimize the magnetic dipole interaction constants, electric quadrupole interaction constants, Voigt profile widths and the center of gravity wavenumber for a given emission line profile. The fit can be changed visually with sliders for parameters, which is useful when HFS constants are unknown.
HfS fits the hyperfine structure of spectral lines, with multiple velocity components. The HfS_nh3 procedures included in HfS fit simultaneously the hyperfine structure of the NH3 (J,K)= (1,1) and (2,2) inversion transitions, and perform a standard analysis to derive the NH3 column density, rotational temperature Trot, and kinetic temperature Tk. HfS uses a Monte Carlo approach for fitting the line parameters, with special attention to the derivation of the parameter uncertainties. HfS includes procedures that make use of parallel computing for fitting spectra from a data cube.
hh0 is a Bayesian hierarchical model (BHM) that describes the full distance ladder, from nearby geometric-distance anchors through Cepheids to SNe in the Hubble flow. It does not rely on any of the underlying distributions being Gaussian, allowing outliers to be modeled and obviating the need for any arbitrary data cuts.
HHTpywrapper is a python interface to call the Hilbert–Huang Transform (HHT) MATLAB package. HHT is a time-frequency analysis method to adaptively decompose a signal, that could be generated by non-stationary and/or nonlinear processes, into basis components at different timescales, and then Hilbert transform these components into instantaneous phases, frequencies and amplitudes as functions of time. HHT has been successfully applied to analyzing X-ray quasi-periodic oscillations (QPOs) from the active galactic nucleus RE J1034+396 (Hu et al. 2014) and two black hole X-ray binaries, XTE J1550–564 (Su et al. 2015) and GX 339-4 (Su et al. 2017). HHTpywrapper provides examples of reproducing HHT analysis results in Su et al. (2015) and Su et al. (2017). This project is originated from the Astro Hack Week 2015.
hi_class implements Horndeski's theory of gravity in the modern Cosmic Linear Anisotropy Solving System (ascl:1106.020). It can be used to compute any cosmological observable at the level of background or linear perturbations, such as cosmological distances, cosmic microwave background, matter power and number count spectra (including relativistic effects). hi_class can be readily interfaced with Monte Python (ascl:1307.002) to test Gravity and Dark Energy models.
HIBAYES implements fully-Bayesian extraction of the sky-averaged (global) 21-cm signal from the Cosmic Dawn and Epoch of Reionization in the presence of foreground emission. User-defined likelihood and prior functions are called by the sampler PyMultiNest (ascl:1606.005) in order to jointly explore the full (signal plus foreground) posterior probability distribution and evaluate the Bayesian evidence for a given model. Implemented models, for simulation and fitting, include gaussians (HI signal) and polynomials (foregrounds). Some simple plotting and analysis tools are supplied. The code can be extended to other models (physical or empirical), to incorporate data from other experiments, or to use alternative Monte-Carlo sampling engines as required.
HIDE (HI Data Emulator) forward-models the process of collecting astronomical radio signals in a single dish radio telescope instrument and outputs pixel-level time-ordered-data. Written in Python, HIDE models the noise and RFI modeling of the data and with its companion code SEEK (ascl:1607.020) provides end-to-end simulation and processing of radio survey data.
hierArc hierarchically infers strong lensing mass density profiles and the cosmological parameters, in particular the Hubble constant. The software supports lenses with imaging data and kinematics, and optionally time delays. The kinematics modeling is performed in conjunction with lenstronomy (ascl:1804.012).
HiFLEx reduces echelle data taken with a single or bifurcated fiber input. It takes a FITS image file (i.e., a CCD image) and runs data reduction steps, extracts out orders from an Echelle spectrograph (regardless of separation and curvature, as long as orders are distinguishable from one-another), applies the wavelength correction, measures the radial velocity, and performs further calibration steps.
HiGal SED Fitter fits modified blackbody SEDs to Herschel data, specifically targeted at Herschel Hi-Gal data.
Motivated by experimental probes of general relativity, we adopt methods from perturbative (quantum) field theory to compute, up to certain integrals, the effective lagrangian for its n-body problem. Perturbation theory is performed about a background Minkowski spacetime to O[(v/c)^4] beyond Newtonian gravity, where v is the typical speed of these n particles in their center of energy frame. For the specific case of the 2 body problem, the major efforts underway to measure gravitational waves produced by in-spiraling compact astrophysical binaries require their gravitational interactions to be computed beyond the currently known O[(v/c)^7]. We argue that such higher order post-Newtonian calculations must be automated for these field theoretic methods to be applied successfully to achieve this goal. In view of this, we outline an algorithm that would in principle generate the relevant Feynman diagrams to an arbitrary order in v/c and take steps to develop the necessary software. The Feynman diagrams contributing to the n-body effective action at O[(v/c)^6] beyond Newton are derived.
HiGPUs is an implementation of the numerical integration of the classical, gravitational, N-body problem, based on a 6th order Hermite’s integration scheme with block time steps, with a direct evaluation of the particle-particle forces. The main innovation of this code is its full parallelization, exploiting both OpenMP and MPI in the use of the multicore Central Processing Units as well as either Compute Unified Device Architecture (CUDA) or OpenCL for the hosted Graphic Processing Units. We tested both performance and accuracy of the code using up to 256 GPUs in the supercomputer IBM iDataPlex DX360M3 Linux Infiniband Cluster provided by the italian supercomputing consortium CINECA, for values of N ≤ 8 millions. We were able to follow the evolution of a system of 8 million bodies for few crossing times, task previously unreached by direct summation codes.
HiGPUs is also available as part of the AMUSE project.
HII-CHI-mistry_UV derives oxygen and carbon abundances using the ultraviolet (UV) lines emitted by the gas phase ionized by massive stars. The code first fixes C/O using ratios of appropriate emission lines and, in a second step, calculates O/H and the ionization parameter from carbon lines in the UV. An optical version of this Python code, HII-CHI-mistry (ascl:1807.007), is also available.
HII-CHI-mistry calculates the oxygen abundance for gaseous nebulae ionized by massive stars using optical collisionally excited emission lines. This code takes the extinction-corrected emission line fluxes and, based on a Χ2 minimization on a photoionization models grid, determines chemical-abundances (O/H, N/O) and ionization parameters. An ultraviolet version of this Python code, HII-CHI-mistry-UV (ascl:1807.008), is also available.
HIIexplorer detects and extracts the integrated spectra of HII regions from IFS datacubes. The procedure assumes H ii regions are peaky/isolated structures with a strong ionized gas emission, clearly above the continuum emission and the average ionized gas emission across the galaxy and that H ii regions have a typical physical size of about a hundred or a few hundreds of parsecs, which corresponds to a typical projected size at the distance of the galaxies of a few arcsec for galaxies at z~0.016. All input parameters can be derived from either a visual inspection and/or a statistical analysis of the Hα emission line map. The algorithm produces a segmentation FITS file describing the pixels associated to each H ii region.
HIIPHOT enables accurate photometric characterization of H II regions while permitting genuine adaptivity to irregular source morphology. It makes a first guess at the shapes of all sources through object recognition techniques; it then allows for departure from such idealized "seeds" through an iterative growing procedure and derives photometric corrections for spatially coincident diffuse emission from a low-order surface fit to the background after exclusion of all detected sources.
Hilal-Obs authenticates lunar crescent first visibility reports. The code, written in Python, uses PyEphem (ascl:1112.014) for astrometrics, and takes into account all the factors that affect lunar crescent visibility, including atmospheric extinction, observer physiology, sky and lunar brightness, contrast threshold, and the type of observation.
The Herschel Space Observatory is the fourth cornerstone mission in the ESA science programme and performs photometry and spectroscopy in the 55 - 672 micron range. The development of the Herschel Data Processing System started in 2002 to support the data analysis for Instrument Level Tests. The Herschel Data Processing System was used for the pre-flight characterisation of the instruments, and during various ground segment test campaigns. Following the successful launch of Herschel 14th of May 2009 the Herschel Data Processing System demonstrated its maturity when the first PACS preview observation of M51 was processed within 30 minutes of reception of the first science data after launch. Also the first HIFI observations on DR21 were successfully reduced to high quality spectra, followed by SPIRE observations on M66 and M74. A fast turn-around cycle between data retrieval and the production of science-ready products was demonstrated during the Herschel Science Demonstration Phase Initial Results Workshop held 7 months after launch, which is a clear proof that the system has reached a good level of maturity.
HIPSTER (HIgh-k Power Spectrum EstimatoR) computes small-scale power spectra and isotropic bispectra for cosmological simulations and galaxy surveys of arbitrary shape. The code computes the Legendre multipoles of the power spectrum, Pℓ(k), or bispectrum Bℓ(k1,k2), by computing weighted pair counts over the simulation box or survey, truncated at some maximum radius. The code can be run either in 'aperiodic' or 'periodic' mode for galaxy surveys or cosmological simulations respectively. HIPSTER also supports weighted spectra, for example when tracer particles are weighted by their mass in a multi-species simulation. Generalization to anisotropic bispectra is straightforward (and requires no additional computing time) and can be added on request.
HISS stacks HI (emission and absorption) spectra in a consistent and reliable manner to enable statistical analysis of average HI properties. It provides plots of the stacked spectrum and reference spectrum with any fitted function, of the stacked noise response, and of the distribution of the integrated fluxes when calculating the uncertainties. It also produces a table containing the integrated flux calculated from the fitted functions and the stacked spectrum, among other output files.
HLattice simulates scalar fields and gravity in the early universe. The code allows the user to select between symplectic integrators, descretization schemes, and metrics such as Minkowski or FRW backgrounds and adaptice schemes in an "all-in-one" configuration file.
HLINOP is a collection of codes for computing hydrogen line profiles and opacities in the conditions typical of stellar atmospheres. It includes HLINOP for approximate quick calculation of any line of neutral hydrogen (suitable for model atmosphere calculations), based on the Fortran code of Kurucz and Peterson found in ATLAS9. It also includes HLINPROF, for detailed, accurate calculation of lower Balmer line profiles (suitable for detailed analysis of Balmer lines) and HBOP, to implement the occupation probability formalism of Daeppen, Anderson and Milhalas (1987) and thus account for the merging of bound-bound and bound-free opacity (used often as a wrapper to HLINOP for model atmosphere calculations).
HMcode computes the halo-model matter power spectrum. It is written in Fortran90 and has been designed to quickly (~0.5s for 200 k-values across 16 redshifts on a single core) produce matter spectra for a wide range of cosmological models. In testing it was shown to match spectra produced by the 'Coyote Emulator' to an accuracy of 5 per cent for k less than 10h Mpc^-1. However, it can also produce spectra well outside of the parameter space of the emulator.
HMF calculates the Halo Mass Function (HMF) given any set of cosmological parameters and fitting function and serves as the backend for the web application HMFcalc. Written in Python, it allows for dynamic accurate calculation of the transfer function with CAMB (ascl:1102.026) and efficient and self-consistent parameter updates. HMF offers exploration of the effects of cosmological parameters, redshift and fitting function on the predicted HMF.
HNBody is a new set of software utilities geared to the integration of hierarchical (nearly-Keplerian) N-body systems. Our focus is on symplectic methods, and we have included explicit support for three classes of particles (heavy, light, and massless), second and fourth order methods, post-Newtonian corrections, and the use of a symplectic corrector (among other things). For testing purposes, we also provide support for more general integration schemes (Bulirsch-Stoer & Runge-Kutta). Configuration files employing an intuitive syntax allow for easy problem setup, and many simple simulations can be done without the user compiling any code. Low-level interfaces are also available, enabling extensive customization.
HO-CHUNK calculates radiative equilibrium temperature solution, thermal and PAH/vsg emission, scattering and polarization in protostellar geometries. It is useful for computing spectral energy distributions (SEDs), polarization spectra, and images.
HOMER (Helper Of My Eternal Retrievals) is a machine-learning-accelerated Bayesian inverse modeling code. Given some data and uncertainties, the code determines the posterior distribution of a model. HOMER uses MC3 (ascl:1610.013) for its MCMC; its forward model is a neural network surrogate model trained by MARGE (ascl:2003.010). The code produces plots of the 1D marginalized posteriors, 2D pairwise posteriors, and parameter history traces, and can also overplot the 1D and 2D posteriors for comparison with another posterior. HOMER computes the Bhattacharyya coefficient to compare the similarity of two 1D marginalized posteriors.
We describe a new method (HOP) for identifying groups of particles in N-body simulations. Having assigned to every particle an estimate of its local density, we associate each particle with the densest of the Nh particles nearest to it. Repeating this process allows us to trace a path, within the particle set itself, from each particle in the direction of increasing density. The path ends when it reaches a particle that is its own densest neighbor; all particles reaching the same such particle are identified as a group. Combined with an adaptive smoothing kernel for finding the densities, this method is spatially adaptive, coordinate-free, and numerically straight-forward. One can proceed to process the output by truncating groups at a particular density contour and combining groups that share a (possibly different) density contour. While the resulting algorithm has several user-chosen parameters, we show that the results are insensitive to most of these, the exception being the outer density cutoff of the groups.
HOPE is a specialized Python just-in-time (JIT) compiler designed for numerical astrophysical applications. HOPE focuses on a subset of the language and is able to translate Python code into C++ while performing numerical optimization on mathematical expressions at runtime. To enable the JIT compilation, the user only needs to add a decorator to the function definition. By using HOPE, the user benefits from being able to write common numerical code in Python while getting the performance of compiled implementation.
HorizonGRound forward models general relativistic effects from the tracer luminosity function. It also compares relativistic corrections with the local primordial non-Gaussianity signature in ultra-large-scale clustering statistics. The package includes several recipes along with the data required to run them.
HOTPANTS (High Order Transform of PSF ANd Template Subtraction) implements the Alard 1999 algorithm for image subtraction. It photometrically aligns one input image with another after they have been astrometrically aligned.
The Hellenic Open University Reconstruction & Simulation (HOURS) software package contains a realistic simulation package of the detector response of very large (km3-scale) underwater neutrino telescopes, including an accurate description of all the relevant physical processes, the production of signal and background as well as several analysis strategies for triggering and pattern recognition, event reconstruction, tracking and energy estimation. HOURS also provides tools for simulating calibration techniques and other studies for estimating the detector sensitivity to several neutrino sources.
HII Region Models fits HII region models to observed radio recombination line and radio continuum data. The algorithm includes the calculations of departure coefficients to correct for non-LTE effects. HII Region Models has been used to model star formation in the nucleus of IC 342.
Hrothgar is a parallel minimizer and Markov Chain Monte Carlo generator. It has been used to solve optimization problems in astrophysics (galaxy cluster mass profiles) as well as in experimental particle physics (hadronic tau decays).
HSIM simulates observations with HARMONI on the Extremely Large Telescope. HSIM takes high spectral and spatial resolution input data cubes, encoding physical descriptions of astrophysical sources, and generates mock observed data cubes. The simulations incorporate detailed models of the sky, telescope, instrument, and detectors to produce realistic mock data. HSIM performs in-depth simulations for several key science cases as part of the design and development of the HARMONI integral field spectrograph, including the ELT AO performance, atmospheric effects and realistic detector statistics.
HSTCosmicrays finds and characterizes cosmic rays found in dark frames (exposures taken with the shutter closed) taken with instruments on the Hubble Space Telescope (HST). Dark exposures are obtained routinely by all the Hubble Space Telescope instruments for calibration. The main processing pipeline runs locally or in the cloud on AWS utilizing the HST Public Dataset.
HUAYNO implements integrators derived from second order Hamiltonian splitting for N-body dynamics. This integration scheme conserves energy and momentum with little or no systematic drift. The code uses an explicit but approximate formula for the time symmetrization that is compatible with the use of individual time steps, making an iterative scheme unnecessary. HUAYNO is available as part of the AMUSE package (ascl:1107.007).
HumVI creates a composite color image from sets of input FITS files, following the Lupton et al (2004, ascl:1511.013) composition algorithm. Written in Python, it takes three FITS files as input and returns a color composite, color-saturated png image with an arcsinh stretch. HumVI reads the zero points out of the FITS headers and uses them to put all the images on the same flux scale; photometrically calibrated images produce the best results.
We describe the first parallel implementation of an adaptive particle-particle, particle-mesh code with smoothed particle hydrodynamics. Parallelisation of the serial code, "Hydra," is achieved by using CRAFT, a Cray proprietary language which allows rapid implementation of a serial code on a parallel machine by allowing global addressing of distributed memory.
The collisionless variant of the code has already completed several 16.8 million particle cosmological simulations on a 128 processor Cray T3D whilst the full hydrodynamic code has completed several 4.2 million particle combined gas and dark matter runs. The efficiency of the code now allows parameter-space explorations to be performed routinely using $64^3$ particles of each species. A complete run including gas cooling, from high redshift to the present epoch requires approximately 10 hours on 64 processors.
HydraLens generates gravitational lens model files for Lenstool (ascl:1102.004), PixeLens (ascl:1102.007), glafic (ascl:1010.012) and Lensmodel and can also translate lens model files among these four lens model codes. Through a GUI, the user enters a new model by specifying the type of model and is then led through screens to collect the data. Written in MS Visual Basic, the code can also translate an existing model from any of the four supported codes to any of the other three.
HydroCode1D is a 1D finite volume code that can run any problem with 1D or 2D/3D spherical symmetry including external gravity or self-gravity. The program provides, depending on the configuration, output files that contain the midpoint position, density, velocity and pressure for each cell in the grid (in SI units). The program will by default use all available threads (as given by the environment variable OMP_NUM_THREADS). This can be overwritten by giving the desired number of threads as a command line argument to the program.
The R package Hyper-Fit fits hyperplanes (hyper.fit) and creates 2D/3D visualizations (hyper.plot2d / hyper.plot3d) to produce robust 1D linear fits for 2D x vs y type data, and robust 2D plane fits to 3D x vs y vs z type data. This hyperplane fitting works generically for any N-1 hyperplane model being fit to a N dimensional dataset. All fits include intrinsic scatter in the generative model orthogonal to the hyperplane. A web interface for online fitting is also available at http://hyperfit.icrar.org.
Hyperion is a three-dimensional dust continuum Monte-Carlo radiative transfer code that is designed to be as generic as possible, allowing radiative transfer to be computed through a variety of three-dimensional grids. The main part of the code is problem-independent, and only requires an arbitrary three-dimensional density structure, dust properties, the position and properties of the illuminating sources, and parameters controlling the running and output of the code. Hyperion is parallelized, and is shown to scale well to thousands of processes. Two common benchmark models for protoplanetary disks were computed, and the results are found to be in excellent agreement with those from other codes. Finally, to demonstrate the capabilities of the code, dust temperatures, SEDs, and synthetic multi-wavelength images were computed for a dynamical simulation of a low-mass star formation region.
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