Results 3551-3600 of 3572 (3481 ASCL, 91 submitted)

[ascl:1404.002]
ZDCF: Z-Transformed Discrete Correlation Function

The cross-correlation function (CCF) is commonly employed in the study of AGN, where it is used to probe the structure of the broad line region by line reverberation, to study the continuum emission mechanism by correlating multi-waveband light curves and to seek correlations between the variability and other AGN properties. The z -transformed discrete correlation function (ZDCF) is a method for estimating the CCF of sparse, unevenly sampled light curves. Unlike the commonly used interpolation method, it does not assume that the light curves are smooth and it does provide errors on its estimates.

[ascl:1110.005]
ZEBRA: Zurich Extragalactic Bayesian Redshift Analyzer

The current version of the Zurich Extragalactic Bayesian Redshift Analyzer (ZEBRA) combines and extends several of the classical approaches to produce accurate photometric redshifts down to faint magnitudes. In particular, ZEBRA uses the template-fitting approach to produce Maximum Likelihood and Bayesian redshift estimates based on: (1.) An automatic iterative technique to correct the original set of galaxy templates to best represent the SEDs of real galaxies at different redshifts; (2.) A training set of spectroscopic redshifts for a small fraction of the photometric sample; and (3.) An iterative technique for Bayesian redshift estimates, which extracts the full two-dimensional redshift and template probability function for each galaxy.

[ascl:2205.012]
Zelda: Generate correlation functions and power spectra from a galaxy catalog

The Zelda command-line tool extracts correlation functions in velocity space from a galaxy catalog. Zelda is modular, extendable, and can be generalized to produce power spectra and to work in position space. Written in C, it was heavily inspired by the cosmological Boltzmann code CLASS (ascl:1106.020). Zelda is a parallel code using the OpenMP standard.

[ascl:1605.016]
zeldovich-PLT: Zel'dovich approximation initial conditions generator

zeldovich-PLT generates Zel'dovich approximation (ZA) initial conditions (i.e. first-order Lagrangian perturbation theory) for cosmological N-body simulations, optionally applying particle linear theory (PLT) corrections.

[ascl:1512.016]
ZeldovichRecon: Halo correlation function using the Zeldovich approximation

ZeldovichRecon computes the halo correlation function using the Zeldovich approximation. It includes 3 variants: 1.) zelrecon.cpp, which computes the various contributions to the correlation function; 2.) zelrecon_ctypes.cpp, which is designed to be called from Python using the ctypes library; and 3.) a version which implements the "ZEFT" formalism of "A Lagrangian effective field theory" [arxiv:1506.05264] including the alpha term described in that paper.

[ascl:1911.012]
Zeltron: Explicit 3D relativistic electromagnetic Particle-In-Cell code

Zeltron is an explicit 3D relativistic electromagnetic Particle-In-Cell code suited for modeling particle acceleration in astrophysical plasmas. The code is efficiently parallelized with the Message Passing Interface, and can be run on a laptop computer or on multiple cores on current supercomputers. Zeltron takes into account the effect of the radiation reaction force on the motion of the particles; it assigns variable weights to the macro-particles to model particle density gradients, and does not strictly conserve the total energy. The code uses linear interpolation to deposit the charges and currents generated by each particle at the nodes of the computational grid, and computes the charge and current densities for Maxwell's equations. Zeltron contains a large set of analysis tools, including plasma density, particle spectrum, optically thin synchrotron and inverse Compton spectra, angular distributions, and stress-energy tensor.

[ascl:1102.027]
ZENO: N-body and SPH Simulation Codes

The ZENO software package integrates N-body and SPH simulation codes with a large array of programs to generate initial conditions and analyze numerical simulations. Written in C, the ZENO system is portable between Mac, Linux, and Unix platforms. It is in active use at the Institute for Astronomy (IfA), at NRAO, and possibly elsewhere.

Zeno programs can perform a wide range of simulation and analysis tasks. While many of these programs were first created for specific projects, they embody algorithms of general applicability and embrace a modular design strategy, so existing code is easily applied to new tasks. Major elements of the system include structured data file utilities facilitate basic operations on binary data, including import/export of ZENO data to other systems; snapshot generation routines to create particle distributions with various properties; systems with user-specified density profiles can be realized in collisionless or gaseous form; multiple spherical and disk components may be set up in mutual equilibrium; and snapshot manipulation routines permit the user to sift, sort, and combine particle arrays, translate and rotate particle configurations, and assign new values to data fields associated with each particle.

Simulation codes include both pure N-body and combined N-body/SPH programs. Pure N-body codes are available in both uniprocessor and parallel versions. SPH codes offer a wide range of options for gas physics, including isothermal, adiabatic, and radiating models. Snapshot analysis programs calculate temporal averages, evaluate particle statistics, measure shapes and density profiles, compute kinematic properties, and identify and track objects in particle distributions. Visualization programs generate interactive displays and produce still images and videos of particle distributions; the user may specify arbitrary color schemes and viewing transformations.

[ascl:1306.014]
ZEUS-2D: Simulation of fluid dynamical flows

ZEUS-2D is a hydrodynamics code based on ZEUS which adds a covariant differencing formalism and algorithms for compressible hydrodynamics, MHD, and radiation hydrodynamics (using flux-limited diffusion) in Cartesian, cylindrical, or spherical polar coordinates.

[ascl:1102.028]
ZEUS-MP/2: Computational Fluid Dynamics Code

Hayes, John C.; Norman, Michael L.; Fiedler, Robert A.; Bordner, James O.; Li, Pak Shing; Clark, Stephen E.; Ud-Doula, Asif; Mac Low, Mordecai-Mark

ZEUS-MP is a multiphysics, massively parallel, message-passing implementation of the ZEUS code. ZEUS-MP offers an MHD algorithm that is better suited for multidimensional flows than the ZEUS-2D module by virtue of modifications to the method of characteristics scheme first suggested by Hawley & Stone. This MHD module is shown to compare quite favorably to the TVD scheme described by Ryu et al. ZEUS-MP is the first publicly available ZEUS code to allow the advection of multiple chemical (or nuclear) species. Radiation hydrodynamic simulations are enabled via an implicit flux-limited radiation diffusion (FLD) module. The hydrodynamic, MHD, and FLD modules can be used, singly or in concert, in one, two, or three space dimensions. In addition, so-called 1.5D and 2.5D grids, in which the "half-D'' denotes a symmetry axis along which a constant but nonzero value of velocity or magnetic field is evolved, are supported. Self-gravity can be included either through the assumption of a GM/r potential or through a solution of Poisson's equation using one of three linear solver packages (conjugate gradient, multigrid, and FFT) provided for that purpose. Point-mass potentials are also supported.

Because ZEUS-MP is designed for large simulations on parallel computing platforms, considerable attention is paid to the parallel performance characteristics of each module in the code. Strong-scaling tests involving pure hydrodynamics (with and without self-gravity), MHD, and RHD are performed in which large problems (2563 zones) are distributed among as many as 1024 processors of an IBM SP3. Parallel efficiency is a strong function of the amount of communication required between processors in a given algorithm, but all modules are shown to scale well on up to 1024 processors for the chosen fixed problem size.

[ascl:2008.010]
zeus: Lightning Fast MCMC

Zeus is a pure-Python implementation of the Ensemble Slice Sampling method. Ensemble Slice Sampling improves upon Slice Sampling by bypassing some of that method's difficulties; it also exploits an ensemble of parallel walkers, thus making it immune to linear correlations. Zeus offers fast and robust Bayesian inference and efficient Markov Chain Monte Carlo without hand-tuning. The code provides excellent performance in terms of autocorrelation time and convergence rate, can scale to multiple CPUs without any extra effort, and includes convergence diagnostics.

[ascl:2306.017]
Zeus21: Simulations of 21-cm at cosmic dawn

Zeus21 (Zippy Early-Universe Solver for 21-cm) captures the nonlocal and nonlinear physics of cosmic dawn to create an effective model for the 21-cm power spectrum and global signal. The code takes advantage of the approximate log-normality of the star-formation rate density (SFRD) during cosmic dawn to compute the 21-cm power spectrum analytically. It agrees with more expensive semi-numerical simulations to roughly 10% precision, but has comparably negligible computational cost (~ s) and memory requirements. Zeus21 pairs well with data from HERA, but can be used for any 21-cm inference or prediction. Its capabilities include finding the 21-cm power spectrum (at a broad range of k and z), the global signal, IGM temperatures (Tk, Ts, Tcolor), neutral fraction xHI, Lyman-alpha fluxes, and the evolution of the SFRD; all across cosmic dawn z=5-35. It can also predict UVLFs for HST and JWST. Zeus21 can use three different astrophysical models, one of which emulates 21cmFAST (ascl:1102.023), and can vary the cosmology through CLASS (ascl:1106.020).

[ascl:1511.022]
ZInCo: Zoomed Initial Conditions

ZInCo manipulates existing initial conditions (ICs) compatible with GADGET-2/3 (ascl:0003.001) ICs, allowing different flavors of zoom-in simulations rather then producing new ICs from scratch. The code can manipulate initial conditions with multiple types of particles, unlike the vast majority of zoom-in ICs codes available, preserving their properties and random field. This allows ZInCo to take advantage of other codes that produce ICs featuring a broad range of different cosmologies; it can be used also on existing ICs even in the unlikely case nothing is known about their properties. The code is written in C++ and parallelized using MPI.

[ascl:1202.002]
ZODIPIC: Zodiacal Cloud Image Synthesis

ZODIPIC synthesizes images of exozodiacal clouds. As a default, ZODIPIC creates an image of the solar zodiacal cloud as seen from 10 pc, but it contains many parameters that are tweakable from the command line, making it a handy general-purpose model for optically-thin debris disks that yields both accurate images and photometric information simultaneously. Written in IDL, ZODIPIC includes dust with real optical constants, user-specified dust maps and can compute images as seen through a linear polarizer.

[ascl:2306.012]
ZodiPy: Zodiacal emission simulations in timestreams or HEALPix for solar system observers

ZodiPy simulates the zodiacal emission in intensity that an arbitrary solar system observer is predicted to see given an interplanetary dust model, either in the form of timestreams or full-sky HEALPix maps. Written in Python, the code makes zodiacal emission simulations more accessible by providing a simple interface to existing models.

[ascl:2105.010]
ZOGY: Python implementation of proper image subtraction

ZOGY performs optimal image subtraction; the code is designed specifically for the MeerLICHT and BlackGEM pipelines, but should also be useful to apply to images of other telescopes. The module accepts a new and a reference FITS image, runs SExtractor (ascl:1010.064) on them, and finds their WCS solution using Astrometry.net (ascl:1208.001). ZOGY then uses PSFex (ascl:1301.001) to infer the position-dependent PSFs of the images and SWarp (ascl:1010.068) to map the reference image to the new image and performs optimal image subtraction. This produces the subtracted image, the significance image, the corrected significance image, and the PSF photometry image and associated error image. The inferred PSFs are also used to extract optimal photometry of all sources detected by SExtractor.

[ascl:2203.027]
Zoobot: Deep learning galaxy morphology classifier

Walmsley, Mike; Lintott, Chris; Géron, Tobias; Kruk, Sandor; Krawczyk, Coleman; Willett, Kyle W.; Bamford, Steven; Kelvin, Lee S.; Fortson, Lucy; Gal, Yarin; Keel, William; Masters, Karen L.; Mehta, Vihang; Simmons, Brooke D.; Smethurst, Rebecca; Smith, Lewis; Baeten, Elisabeth M.; Macmillan, Christine

Zoobot classifies galaxy morphology with Bayesian CNN. Deep learning models were trained on volunteer classifications; these models were able to both learn from uncertain volunteer responses and predict full posteriors (rather than point estimates) for what volunteers would have said. The code reproduces and improves Galaxy Zoo DECaLS automated classifications, and can be finetuned for new tasks.

[ascl:1011.003]
ZPEG: An Extension of the Galaxy Evolution Model PEGASE.2

Photometric redshifts are estimated on the basis of template scenarios with the help of the code ZPEG, an extension of the galaxy evolution model PEGASE.2 and available on the PEGASE web site. The spectral energy distribution (SED) templates are computed for nine spectral types including starburst, irregular, spiral and elliptical. Dust, extinction and metal effects are coherently taken into account, depending on evolution scenarios. The sensitivity of results to adding near-infrared colors and IGM absorption is analyzed. A comparison with results of other models without evolution measures the evolution factor which systematically increases the estimated photometric redshift values by $Delta z$ > 0.2 for z > 1.5. Moreover we systematically check that the evolution scenarios match observational standard templates of nearby galaxies, implying an age constraint of the stellar population at z=0 for each type. The respect of this constraint makes it possible to significantly improve the accuracy of photometric redshifts by decreasing the well-known degeneracy problem. The method is applied to the HDF-N sample. From fits on SED templates by a $chi^2$-minimization procedure, not only is the photometric redshift derived but also the corresponding spectral type and the formation redshift $z_for$ when stars first formed. Early epochs of galaxy formation z > 5 are found from this new method and results are compared to faint galaxy count interpretations.

[ascl:2106.034]
ztf-viewer: SNAD ZTF data releases object viewer

The SNAD ZTF DR4 object viewer enables quick expert investigation of objects within the public Zwicky Transient Facility (ZTF) data releases. The viewer allows visualization of raw and folded light curves and metadata, as well as cross-match information with the General Catalog of Variable Stars, the International Variable Stars Index, the ATLAS Catalog of Variable Stars, the ZTF Catalog of Periodic Variable Stars, the Transient Name Server, the Open Astronomy Catalogs, the OGLE III Catalog of Variable Stars, the Simbad Astronomical Data Base, Gaia DR2 distances (Bailer-Jones+, 2018), and Vizier. The viewer is also available for ZTF DR2 and ZTF DR3.

[ascl:2106.033]
ZWAD: Anomaly detection pipeline

Malanchev, K. L.; Pruzhinskaya, M. V.; Korolev, V. S.; Aleo, P. D.; Kornilov, M. V.; Ishida, E. E. O.; Krushinsky, V. V.; Mondon, F.; Sreejith, S.; Volnova, A. A.; Belinski, A. A.; Dodin, A. V.; Tatarnikov, A. M.; Zheltoukhov, S. G.

ZWAD (ZTF anomaly detection pipeline) examines data and performs tailored feature extraction. The code then uses machine learning methods to searches for outliers, and identifies anomalies to be examined for validation by experts. Used with the SNAD ZTF data releases object viewer (ascl:2106.034), the infrastructure helps experts to form global views of specific scientifically interesting candidates.

[ascl:2202.003]
Zwindstroom: Cosmological growth factors from fluid calculations

Zwindstroom computes background quantities and scale-dependent growth factors for cosmological models with free-streaming species, such as massive neutrinos. Following the earlier REPS code (ascl:1612.022), the code uses a Newtonian fluid approximation with external neutrino sound speed to close the Boltzmann hierarchy. Zwindstroom supports multi-fluid models with distinct transfer functions and sound speeds. A flexible python interface facilitates interaction with CLASS (ascl:1106.020) through classy. There is also a Zwindstroom plugin for the cosmological initial conditions generator monofonIC (ascl:2008.024) that allows for higher-order LPT ICs for massive neutrino simulations in a single step.

[ascl:2306.006]
β-SGP: Scaled Gradient Projection algorithm using β-divergence

β-SGP deconvolves an astronomical image with a known Point Spread Function, providing a means for restoration of telescopic images due to issues ranging from atmospheric turbulence to instrumental aberrations. The code supports improved astrometry, deblending of overlapping sources, faint source detection, and identification of point sources near bright extended objects, and other tasks. β-SGP generalizes the Scaled Gradient Projection (SGP) image deconvolution algorithm using β-divergence as a loss function to restore distorted stellar shapes.

[ascl:2307.050]
νHawkHunter: Forecasting of PBH neutrinos

νHawkHunter explores the prospects of detecting neutrinos produced by the evaporation of primordial black holes in ground-based experiments. It makes use of neutrino fluxes from Hawking radiation computed with BlackHawk (ascl:2012.020). νHawkHunter is also be used for Diffuse Supernova Neutrino Background or similar studies by replacing the signal fluxes by the proper ones.

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