ASCL.net

Astrophysics Source Code Library

Making codes discoverable since 1999

Browsing Codes

Order
Title Date
 
Mode
Abstract Compact
Per Page
50100250All
[ascl:2104.020] LAPACK: Linear Algebra PACKage

LAPACK provides routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems. The associated matrix factorizations (LU, Cholesky, QR, SVD, Schur, generalized Schur) are also provided, as are related computations such as reordering of the Schur factorizations and estimating condition numbers. Dense and banded matrices are handled, but not general sparse matrices. In all areas, similar functionality is provided for real and complex matrices, in both single and double precision. The list of LAPACK Contributors is available online.

[ascl:1703.001] Larch: X-ray Analysis for Synchrotron Applications using Python

Larch is an open-source library and toolkit written in Python for processing and analyzing X-ray spectroscopic data. The primary emphasis is on X-ray spectroscopic and scattering data collected at modern synchrotron sources. Larch provides a wide selection of general-purpose processing, analysis, and visualization tools for processing X-ray data; its related target application areas include X-ray absorption fine structure (XAFS), micro-X-ray fluorescence (XRF) maps, quantitative X-ray fluorescence, X-ray absorption near edge spectroscopy (XANES), and X-ray standing waves and surface scattering. Larch provides a complete set of XAFS Analysis tools and has support for visualizing and analyzing XRF maps and spectra, and additional tools for X-ray spectral analysis, data handling, and general-purpose data modeling.

[ascl:1208.015] Lare3d: Lagrangian-Eulerian remap scheme for MHD

Lare3d is a Lagrangian-remap code for solving the non-linear MHD equations in three spatial dimensions.

[ascl:1806.021] LASR: Linear Algorithm for Significance Reduction

LASR removes stellar variability in the light curves of δ-Scuti and similar stars. It subtracts oscillations from a time series by minimizing their statistical significance in frequency space.

[ascl:2010.006] LaSSI: Large-Scale Structure Information

LaSSI produces forecasts for the LSST 3x2 point functions analysis, or the LSSTxCMB S4 and LSSTxSO 6x2 point functions analyses using a Fisher matrix. It computes the auto and cross correlations of galaxy number density, galaxy shear and CMB lensing convergence. The software includes the effect of Gaussian and outlier photo-z errors, shear multiplicative bias, linear galaxy bias, and extensions to ΛCDM.

[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.

[ascl:2205.006] LATTE: Lightcurve Analysis Tool for Transiting Exoplanet

LATTE identifies, vets and characterizes signals in TESS lightcurves to weed out instrumental and astrophysical false positives. The program performs a fast in-depth analysis of targets that have already been identified as promising candidates by the main TESS pipelines or via alternative methods such as citizen science. The code automatically downloads the data products for any chosen TIC ID (short or long cadence TESS data) and produces a number of diagnostic plots that are compiled in a concise report.

[ascl:1911.015] LATTICEEASY: Lattice simulator for evolving interacting scalar fields in an expanding universe

LATTICEEASY creates lattice simulations of the evolution of interacting scalar fields in an expanding universe. The program can do runs with different parameters and new models can be easily introduced for evaluation. Simulations can be done in one, two, or three dimensions by resetting a single variable. Mathematica notebooks for plotting the output and a range of models are also available for download; a parallel processing version of LATTICEEASY called CLUSTEREASY (ascl:1911.016) is also available.

[ascl:1202.011] Lattimer-Swesty Equation of State Code

The Lattimer-Swesty Equation of State code is rapid enough to use directly in hydrodynamical simulations such as stellar collapse calculations. It contains an adjustable nuclear force that accurately models both potential and mean-field interactions and allows for the input of various nuclear parameters, including the bulk incompressibility parameter, the bulk and surface symmetry energies, the symmetric matter surface tension, and the nucleon effective masses. This permits parametric studies of the equation of state in astrophysical situations. The equation of state is modeled after the Lattimer, Lamb, Pethick, and Ravenhall (LLPR) compressible liquid drop model for nuclei, and includes the effects of interactions and degeneracy of the nucleon outside nuclei.

[ascl:2210.018] LavAtmos: Gas-melt equilibrium calculations for a given temperature and melt composition

LavAtmos performs gas-melt equilibrium calculations for a given temperature and melt composition. The thermodynamics of the melt are modeled by the MELTS code as presented in the Thermoengine package (ascl:2208.006). In combination with atmospheric chemistry codes, LavAtmos enables the characterization of interior compositions through atmospheric signatures.

[ascl:2301.014] LBL: Line-by-line velocity measurements

LBL derives velocity measurements from high-resolution (R>50 000) datasets by accounting for outliers in the spectra data. It is tailored for fiber-fed multi-order spectrographs, both in optical and near-infrared (up to 2.5µm) domains. The domain is split into individual units (lines) and the velocity and its associated uncertainty are measured within each line and combined through a mixture model to allow for the presence of spurious values. In addition to the velocity, other quantities are also derived, the most important being a value (dW) that can be understood (for a Gaussian line) as a change in the line FWHM. These values provide useful stellar activity indicators. LBL works on data from a variety of instruments, including SPIRou, NIRPS, HARPS, and ESPRESSO. The code's output is an rdb table that can be uploaded to the online DACE pRV analysis tool.

[ascl:1405.001] LBLRTM: Line-By-Line Radiative Transfer Model

LBLRTM (Line-By-Line Radiative Transfer Model) is an accurate line-by-line model that is efficient and highly flexible. LBLRTM attributes provide spectral radiance calculations with accuracies consistent with the measurements against which they are validated and with computational times that greatly facilitate the application of the line-by-line approach to current radiative transfer applications. LBLRTM has been extensively validated against atmospheric radiance spectra from the ultra-violet to the sub-millimeter.

LBLRTM's heritage is in FASCODE [Clough et al., 1981, 1992].

[ascl:1708.017] LCC: Light Curves Classifier

Light Curves Classifier uses data mining and machine learning to obtain and classify desired objects. This task can be accomplished by attributes of light curves or any time series, including shapes, histograms, or variograms, or by other available information about the inspected objects, such as color indices, temperatures, and abundances. After specifying features which describe the objects to be searched, the software trains on a given training sample, and can then be used for unsupervised clustering for visualizing the natural separation of the sample. The package can be also used for automatic tuning parameters of used methods (for example, number of hidden neurons or binning ratio).

Trained classifiers can be used for filtering outputs from astronomical databases or data stored locally. The Light Curve Classifier can also be used for simple downloading of light curves and all available information of queried stars. It natively can connect to OgleII, OgleIII, ASAS, CoRoT, Kepler, Catalina and MACHO, and new connectors or descriptors can be implemented. In addition to direct usage of the package and command line UI, the program can be used through a web interface. Users can create jobs for ”training” methods on given objects, querying databases and filtering outputs by trained filters. Preimplemented descriptors, classifier and connectors can be picked by simple clicks and their parameters can be tuned by giving ranges of these values. All combinations are then calculated and the best one is used for creating the filter. Natural separation of the data can be visualized by unsupervised clustering.

[ascl:1805.003] lcps: Light curve pre-selection

lcps searches for transit-like features (i.e., dips) in photometric data. Its main purpose is to restrict large sets of light curves to a number of files that show interesting behavior, such as drops in flux. While lcps is adaptable to any format of time series, its I/O module is designed specifically for photometry of the Kepler spacecraft. It extracts the pre-conditioned PDCSAP data from light curves files created by the standard Kepler pipeline. It can also handle csv-formatted ascii files. lcps uses a sliding window technique to compare a section of flux time series with its surroundings. A dip is detected if the flux within the window is lower than a threshold fraction of the surrounding fluxes.

[ascl:2310.002] lcsim: Light curve simulation code

lcsim creates artificial light curves using two algorithms. The first simulates Gaussian distributed light curves following a specific power spectral density (PSD) freely selectable by the user. The second algorithm simulates light curves following a specific PSD and matching a specific probability density function (PDF). The package provides methods to resample the simulated light curves and add "observational" noise. Furthermore, the package provides an interface to a SQLite3-based database to store and access the simulations.

[ascl:2205.013] ld-exosim: Simulate biases using different limb darkening laws

ld-exosim selects the optimal (i.e. best estimator in a MSE sense) limb-darkening law for a given transiting exoplanet lightcurve and calculates the limb-darkening induced biases on various exoplanet parameters. Limb-darkening laws include linear, quadratic, logarithmic, square-root and three-parameter laws.

[ascl:1511.018] LDC3: Three-parameter limb darkening coefficient sampling

LDC3 samples physically permissible limb darkening coefficients for the Sing et al. (2009) three-parameter law. It defines the physically permissible intensity profile as being everywhere-positive, monotonically decreasing from center to limb and having a curl at the limb. The approximate sampling method is analytic and thus very fast, reproducing physically permissible samples in 97.3% of random draws (high validity) and encompassing 94.4% of the physically permissible parameter volume (high completeness).

[ascl:1507.016] Least Asymmetry: Centering Method

Least Asymmetry finds the center of a distribution of light in an image using the least asymmetry method; the code also contains center of light and fitting a Gaussian routines. All functions in Least Asymmetry are designed to take optional weights.

[ascl:1104.006] LECTOR: Line-strengths in One-dimensional ASCII Spectra

LECTOR is a Fortran 77 code that measures line-strengths in one dimensional ascii spectra. The code returns the values of the Lick indices as well as those of Vazdekis & Arimoto 1999, Vazdekis et al. 2001, Rose 1994, Jones & Worthey 1995 and Cenarro et al. 2001. The code measures as many indices as you wish if the limits of two pseudocontinua (at each side of the feature) and the feature itself (i.e. Lick-style index definition) are provided. The Lick-style indices could be either expressed in pseudo-equivalent widths or in magnitudes. If requested the program provides index error estimates on the basis of photon statistics.

[ascl:2307.054] LEFTfield: Forward modeling of cosmological density fields

LEFTfield forward models cosmological matter density fields and biased tracers of large-scale structure. The model, written in C++ code, is centered around classes encapsulating scalar, vector, and tensor grids. It includes the complete bias expansion at any order in perturbations and captures general expansion histories without relying on the EdS approximation; however, the latter is also implemented and results in substantially smaller computational demands. LEFTfield includes a subset of the nonlinear higher-derivative terms in the bias expansion of general tracers.

[ascl:2204.003] legacystamps: Retrieve DESI Legacy Imaging Surveys cutouts

The Python module legacystamps provides easy retrieval, both standalone and scripted, of FITS and JPEG cutouts from the DESI Legacy Imaging Surveys through URLs provided by the Legacy Survey viewer.

[ascl:2010.013] Legolas: Large Eigensystem Generator for One-dimensional pLASmas

Legolas (Large Eigensystem Generator for One-dimensional pLASmas) is a finite element code for MHD spectroscopy of 1D Cartesian/cylindrical equilibria with flow that balance pressure gradients, enriched with various non-adiabatic effects. The code's capabilities range from full spectrum calculations to eigenfunctions of specific modes to full-on parametric studies of various equilibrium configurations in different geometries.

[ascl:2111.007] LEGWORK: LISA Evolution and Gravitational Wave ORbit Kit

LEGWORK (LISA Evolution and Gravitational Wave ORbit Kit) is a simple package for gravitational wave calculations. It evolves binaries and computes signal-to-noise ratios for binary systems potentially observable with LISA; it also visualizes the results. LEGWORK can also compare different detector sensitivity curves, compute the horizon distance for a collection of sources, and tracks signal-to-noise evolution over time.

[ascl:2406.020] LeHaMoC: Leptonic-Hadronic Modeling Code for high-energy astrophysical sources

LeHaMoC simulates high-energy astrophysical sources. It simulates the behavior of relativistic pairs, protons interacting with magnetic fields, and photons in a spherical region. The package contains numerous physical processes, including synchrotron emission and self-absorption, inverse Compton scattering, photon-photon pair production, and adiabatic losses. It also includes proton-photon pion production, proton-photon (Bethe-Heitler) pair production, and proton-proton collisions. LeHaMoC can model expanding spherical sources with a variable magnetic field strength. In addition, three types of external radiation fields can be defined: grey body or black body, power-law, and tabulated.

[ascl:1809.001] LEMON: Differential photometry pipeline

LEMON is a differential-photometry pipeline, written in Python, that determines the changes in the brightness of astronomical objects over time and compiles their measurements into light curves. This code makes it possible to completely reduce thousands of FITS images of time series in a matter of only a few hours, requiring minimal user interaction.

[ascl:2106.014] Lemon: Linear integral Equations' Monte carlo solver based On the Neumann solution

Lemon solves the radiative transfer (RT) processes that contain scattering. These processes are described by differentio-integral equations with given initial or boundary conditions; Lemon solves these differentio-integral equations, which can be converted into the second kind integral equations of Fredholm. The code then obtains the Neumman solution (a series that consists of infinite terms of multiple integrals) from the Fredholm integral equation, and uses the Monte Carlo (MC) method to evaluate these integrals. Lemon is written in Fortran; IDL programs are included for plotting the results.

[ascl:1905.016] LensCNN: Gravitational lens detector

The LensCNN (Convolutional Neural Network) identifies images containing gravitational lensing systems after being trained and tested on simulated images, recovering most systems that are identifiable by eye.

[ascl:1505.026] Lensed: Forward parametric modelling of strong lenses

Lensed performs forward parametric modelling of strong lenses. Using a provided model, Lensed renders the expected image of the lensing event for a large number of parameter settings, thereby exploring the space of possible realizations of the observation. It compares the expectation to the observed image by calculating the likelihood that the observation was indeed produced by the assumed model, thus reconstructing the probability distribution over the parameter space of the model. Written in C, the code uses a massively parallel ray-tracing kernel to perform the necessary calculations on a graphics processing unit (GPU), making the precise rendering of the background lensed sources fast and allowing the simultaneous optimization of tens of parameters for the selected model.

[ascl:1308.004] LensEnt2: Maximum-entropy weak lens reconstruction

LensEnt2 is a maximum entropy reconstructor of weak lensing mass maps. The method takes each galaxy shape as an independent estimator of the reduced shear field and incorporates an intrinsic smoothness, determined by Bayesian methods, into the reconstruction. The uncertainties from both the intrinsic distribution of galaxy shapes and galaxy shape estimation are carried through to the final mass reconstruction, and the mass within arbitrarily shaped apertures are calculated with corresponding uncertainties. The input is a galaxy ellipticity catalog with each measured galaxy shape treated as a noisy tracer of the reduced shear field, which is inferred on a fine pixel grid assuming positivity, and smoothness on scales of w arcsec where w is an input parameter. The ICF width w can be chosen by computing the evidence for it.

[ascl:2406.005] Lenser: Measure weak gravitational flexion

Lenser estimates weak gravitational lensing signals, particularly flexion, from real survey data or realistically simulated images. Lenser employs a hybrid of image moment analysis and an Analytic Image Modeling (AIM) analysis. In addition to extracting flexion measurements by fitting a (modified Sérsic) model to a single image of a galaxy, Lenser can do multi-band, multi-epoch fitting. In multi-band mode, Lenser fits a single model to multiple postage stamps, each representing an exposure of a single galaxy in a particular band.

[ascl:2210.027] LensingETC: Lensing Exposure Time Calculator

LensingETC optimizes observing strategies for multi-filter imaging campaigns of galaxy-scale strong lensing systems. It uses the lens modelling software lenstronomy (ascl:1804.012) to simulate and model mock imaging data, forecasts the lens model parameter uncertainties, and optimizes observing strategies.

[ascl:2102.021] lensingGW: Lensing of gravitational waves

lensingGW simulates lensed gravitational waves in ground-based interferometers from arbitrary compact binaries and lens models. Its algorithm resolves strongly lensed images and microimages simultaneously, such as the images resulting from hundreds of microlenses embedded in galaxies and galaxy clusters. It is based on Lenstronomy (ascl:1804.012),

[ascl:2404.008] LensIt: CMB lensing delensing tools

LensIt enables CMB lensing and CMB delensing using the flat-sky approximation. The package can find the maximum posterior estimation of CMB lensing deflection maps from temperature and/or polarization maps and perform Wiener filtering of masked CMB data and allow for inhomogenous noise, including lensing deflections, using a multigrid preconditioner. It contains fast and accurate simulation libraries for lensed CMB skies, and standard quadratic estimator lensing reconstruction tools. LensIt also includes CMB internal delensing tools, including internal delensing biases calculation for temperature and/or polarization maps.

[ascl:2410.010] lensitbiases: rFFT-based flat-sky CMB lensing tools

lensitbiases is an rFFT-based N1 lensing bias calculation and tests. It is tuned for TT, P-only or MV (GMV) like quadratic estimators. It performs rFFT-based N1 and N1 matrix calculations in ~ O(ms) time per lensing multipole for Planck-like config, which allows on-the-fly evaluation of the bias. It also calculates 5 rFFT's of moderate size per L for N1 TT, 20 for PP, and 45 for MV or GMV. lensitbiases is not particularly efficient for low lensing L's, since in this case one must use large boxes.

[ascl:9903.001] LENSKY: Galactic Microlensing Probability

Given a model for the Galaxy, this program computes the microlensing rate in any direction. Program features include the ability to include the brightness of the lens and to compute the probability of lens detection at any level of lensing amplification. The program limits itself to lensing by single stars of single sources. The program is currently setup to accept input from the Galactic models of Bahcall and Soniera (1982, 1986).

There are three files needed for LENSKY, the Fortran file lensky.for and two input files: galmod.dsk (15 Megs) and galmod.sph (22 Megs). The zip file available below contains all three files. The program generates output to the file lensky.out. The program is pretty self-explanatory past that.

[ascl:1010.050] LensPerfect: Gravitational Lens Massmap Reconstructions Yielding Exact Reproduction of All Multiple Images

LensPerfect is a new approach to the massmap reconstruction of strong gravitational lenses. Conventional methods iterate over possible lens models which reproduce the observed multiple image positions well but not exactly. LensPerfect only produces solutions which fit all of the data exactly. Magnifications and shears of the multiple images can also be perfectly constrained to match observations.

[ascl:1102.025] LensPix: Fast MPI full sky transforms for HEALPix

Modelling of the weak lensing of the CMB will be crucial to obtain correct cosmological parameter constraints from forthcoming precision CMB anisotropy observations. The lensing affects the power spectrum as well as inducing non-Gaussianities. We discuss the simulation of full sky CMB maps in the weak lensing approximation and describe a fast numerical code. The series expansion in the deflection angle cannot be used to simulate accurate CMB maps, so a pixel remapping must be used. For parameter estimation accounting for the change in the power spectrum but assuming Gaussianity is sufficient to obtain accurate results up to Planck sensitivity using current tools. A fuller analysis may be required to obtain accurate error estimates and for more sensitive observations. We demonstrate a simple full sky simulation and subsequent parameter estimation at Planck-like sensitivity.

[ascl:1705.009] LensPop: Galaxy-galaxy strong lensing population simulation

LensPop simulates observations of the galaxy-galaxy strong lensing population in the Dark Energy Survey (DES), the Large Synoptic Survey Telescope (LSST), and Euclid surveys.

[ascl:2010.010] lenspyx: Curved-sky python lensed CMB maps simulation package

lenspyx creates curved-sky python lensed CMB maps simulations; the software allows those familiar with healpy (ascl:2008.022) to build very easily lensed CMB simulations. Parallelization is done with openmp. The numerical cost is approximately that of an high-res harmonic transform. lenspyx provides two methods to build a simulation; one method computes a deflected spin-0 healpix map from its alm and deflection field alm, and the other computes a deflected spin-weight Healpix map from its gradient and curl modes and deflection field alm. lenspyx can be used in conjunction with the Planck 2018 CMB lensing pipeline plancklens (ascl:2010.009) to reproduce the published map and band-powers.

[ascl:1905.017] LensQuEst: CMB Lensing QUadratic Estimator

LensQuEst forecasts the signal-to-noise of CMB lensing estimators (standard, shear-only, magnification-only), generates mock maps, lenses them, and applies various lensing estimators to them. It can manipulate flat sky maps in various ways, including FFT, filtering, power spectrum, generating Gaussian random field, and applying lensing to a map, and evaluate these estimators on flat sky maps.

[ascl:1102.004] LENSTOOL: A Gravitational Lensing Software for Modeling Mass Distribution of Galaxies and Clusters (strong and weak regime)

We describe a procedure for modelling strong lensing galaxy clusters with parametric methods, and to rank models quantitatively using the Bayesian evidence. We use a publicly available Markov chain Monte-Carlo (MCMC) sampler ('Bayesys'), allowing us to avoid local minima in the likelihood functions. To illustrate the power of the MCMC technique, we simulate three clusters of galaxies, each composed of a cluster-scale halo and a set of perturbing galaxy-scale subhalos. We ray-trace three light beams through each model to produce a catalogue of multiple images, and then use the MCMC sampler to recover the model parameters in the three different lensing configurations. We find that, for typical Hubble Space Telescope (HST)-quality imaging data, the total mass in the Einstein radius is recovered with ~1-5% error according to the considered lensing configuration. However, we find that the mass of the galaxies is strongly degenerated with the cluster mass when no multiple images appear in the cluster centre. The mass of the galaxies is generally recovered with a 20% error, largely due to the poorly constrained cut-off radius. Finally, we describe how to rank models quantitatively using the Bayesian evidence. We confirm the ability of strong lensing to constrain the mass profile in the central region of galaxy clusters in this way. Ultimately, such a method applied to strong lensing clusters with a very large number of multiple images may provide unique geometrical constraints on cosmology.

[ascl:1602.009] LensTools: Weak Lensing computing tools

LensTools implements a wide range of routines frequently used in Weak Gravitational Lensing, including tools for image analysis, statistical processing and numerical theory predictions. The package offers many useful features, including complete flexibility and easy customization of input/output formats; efficient measurements of power spectrum, PDF, Minkowski functionals and peak counts of convergence maps; survey masks; artificial noise generation engines; easy to compute parameter statistical inferences; ray tracing simulations; and many others. It requires standard numpy and scipy, and depending on tools used, may require Astropy (ascl:1304.002), emcee (ascl:1303.002), matplotlib, and mpi4py.

[ascl:1804.012] Lenstronomy: Multi-purpose gravitational lens modeling software package

Lenstronomy is a multi-purpose open-source gravitational lens modeling python package. Lenstronomy reconstructs the lens mass and surface brightness distributions of strong lensing systems using forward modelling and supports a wide range of analytic lens and light models in arbitrary combination. The software is also able to reconstruct complex extended sources as well as point sources. Lenstronomy is flexible and numerically accurate, with a clear user interface that could be deployed across different platforms. Lenstronomy has been used to derive constraints on dark matter properties in strong lenses, measure the expansion history of the universe with time-delay cosmography, measure cosmic shear with Einstein rings, and decompose quasar and host galaxy light.

[ascl:1307.005] LENSVIEW: Resolved gravitational lens images modeling

Lensview models resolved gravitational lens systems based on LensMEM but using the Skilling & Bryan MEM algorithm. Though its primary purpose is to find statistically acceptable lens models for lensed images and to reconstruct the surface brightness profile of the source, LENSVIEW can also be used for more simple tasks such as projecting a given source through a lens model to generate a “true” image by conserving surface brightness. The user can specify complicated lens models based on one or more components, such as softened isothermal ellipsoids, point masses, exponential discs, and external shears; LENSVIEW generates a best-fitting source matching the observed data for each specific combination of model parameters.

[ascl:1910.011] LEO-Py: Likelihood Estimation of Observational data with Python

LEO-Py uses a novel technique to compute the likelihood function for data sets with uncertain, missing, censored, and correlated values. It uses Gaussian copulas to decouple the correlation structure of variables and their marginal distributions to compute likelihood functions, thus mitigating inconsistent parameter estimates and accounting for non-normal distributions in variables of interest or their errors.

[ascl:2404.026] LEO-vetter: Automated vetting for TESS planet candidates

LEO-vetter automatically vets transit signals found in light curve data. Inspired by the Kepler Robovetter (ascl:2012.006), LEO-vetter computes vetting metrics to be compared to a series of pass-fail thresholds. If a signal passes all tests, it is considered a planet candidate (PC). If a signal fails at least one test, it may be either an astrophysical false positive (FP; e.g., eclipsing binary, nearby eclipsing signal) or false alarm (FA; e.g., systematic, stellar variability). Pass-fail thresholds can be changed to suit individual research purposes, and LEO-vetter produces vetting reports for manual inspection of signals. Flux-level vetting can be applied to any light curve dataset (such as Kepler, K2, and TESS), including light curves with mixes of cadences, while pixel-level vetting has been implemented for TESS.

[ascl:1108.009] LePHARE: Photometric Analysis for Redshift Estimate

LePHARE is a set of Fortran commands to compute photometric redshifts and to perform SED fitting. The latest version includes new features with FIR fitting and a more complete treatment of physical parameters and uncertainties based on PÉGASE and Bruzual & Charlot population synthesis models. The program is based on a simple chi2 fitting method between the theoretical and observed photometric catalogue. A simulation program is also available in order to generate realistic multi-colour catalogues taking into account observational effects.

[ascl:2208.009] LeXInt: Leja Exponential Integrators

LeXInt (Leja interpolation for eXponential Integrators) is a temporal exponential integration package using the method of polynomial interpolation at Leja points. Exponential Rosenbrock (EXPRB) and Exponential Propagation Iterative Runge-Kutta (EPIRK) methods use the Leja interpolation method to compute the functions. For linear PDEs, one can get the exact solution (in time) by directly computing the matrix exponential.

[ascl:1711.018] LExTeS: Link Extraction and Testing Suite

LExTeS (Link Extraction and Testing Suite) extracts hyperlinks from PDF documents, tests the extracted links to see which are broken, and tabulates the results. Though written to support a particular set of PDF documents, the dataset and scripts can be edited for use on other documents.

[ascl:1804.024] LFlGRB: Luminosity function of long gamma-ray bursts

LFlGRB models the luminosity function (LF) of long Gamma Ray Bursts (lGRBs) by using a sample of Swift and Fermi lGRBs to re-derive the parameters of the Yonetoku correlation and self-consistently estimate pseudo-redshifts of all the bursts with unknown redshifts. The GRB formation rate is modeled as the product of the cosmic star formation rate and a GRB formation efficiency for a given stellar mass.

Would you like to view a random code?