Results 1901-1950 of 3560 (3466 ASCL, 94 submitted)

[ascl:1807.028]
ktransit: Exoplanet transit modeling tool in python

The routines in ktransit create and fit a transiting planet model. The underlying model is a Fortran implementation of the Mandel & Agol (2002) limb darkened transit model. The code calculates a full orbital model and eccentricity can be allowed to vary; radial velocity data can also be calculated via the model and included in the fit.

[ascl:1804.026]
KSTAT: KD-tree Statistics Package

KSTAT calculates the 2 and 3-point correlation functions in discreet point data. These include the two-point correlation function in 2 and 3-dimensions, the anisotripic 2PCF decomposed in either sigma-pi or Kazin's dist. mu projection. The 3-point correlation function can also work in anisotropic coordinates. The code is based on kd-tree structures and is parallelized using a mixture of MPI and OpenMP.

[ascl:1505.004]
KS Integration: Kelvin-Stokes integration

KS Intergration solves for mutual photometric effects produced by planets and spots allowing for analysis of planetary occultations of spots and spots regions. It proceeds by identifying integrable and non integrable arcs on the objects profiles and analytically calculates the solution exploiting the power of Kelvin-Stokes theorem. It provides the solution up to the second degree of the limb darkening law.

[ascl:1402.011]
KROME: Chemistry package for astrophysical simulations

Grassi, Tommaso; Bovino, Stefano; Prieto, Joaquín; Seifried, Daniel; Simoncini, Eugenio; Gianturco, Francesco; Schleicher, Dominik

KROME, given a chemical network (in CSV format), automatically generates all the routines needed to solve the kinetics of the system modeled as a system of coupled Ordinary Differential Equations. It provides a large set of physical processes connected to chemistry, including photochemistry, cooling, heating, dust treatment, and reverse kinetics. KROME is flexible and can be used for a wide range of astrophysical simulations. The package contains a network for primordial chemistry, a small metal network appropriate for the modeling of low metallicities environments, a detailed network for the modeling of molecular clouds, and a network for planetary atmospheres as well as a framework for the modelling of the dust grain population.

[ascl:1609.003]
Kranc: Cactus modules from Mathematica equations

Kranc turns a tensorial description of a time dependent partial differential equation into a module for the Cactus Computational Toolkit (ascl:1102.013). This Mathematica application takes a simple continuum description of a problem and generates highly efficient and portable code, and can be used both for rapid prototyping of evolution systems and for high performance supercomputing.

[ascl:1807.027]
kplr: Tools for working with Kepler data using Python

kplr provides a lightweight Pythonic interface to the catalog of planet candidates (Kepler Objects of Interest [KOIs]) in the NASA Exoplanet Archive and the data stored in the Barbara A. Mikulski Archive for Space Telescopes (MAST). kplr automatically supports loading Kepler data using pyfits (ascl:1207.009) and supports two types of data: light curves and target pixel files.

[ascl:1504.013]
kozai: Hierarchical triple systems evolution

The kozai Python package evolves hierarchical triple systems in the secular approximation. As its name implies, the kozai package is useful for studying Kozai-Lidov oscillations. The kozai package can represent and evolve hierarchical triples using either the Delaunay orbital elements or the angular momentum and eccentricity vectors. kozai contains functions to calculate the period of Kozai-Lidov oscillations and the maximum eccentricity reached; it also contains a module to study octupole order effects by averaging over individual Kozai-Lidov oscillations.

[ascl:2211.016]
Korg: 1D local thermodynamic equilibrium stellar spectral synthesis

Korg computes stellar spectra from 1D model atmospheres and linelists assuming local thermodynamic equilibrium and implements both plane-parallel and spherical radiative transfer. The code is generally faster than other codes, and is compatible with automatic differentiation libraries and easily extensible, making it ideal for statistical inference and parameter estimation applied to large data sets.

[ascl:2004.010]
kombine: Kernel-density-based parallel ensemble sampler

kombine is an ensemble sampler built for efficiently exploring multimodal distributions. By using estimates of ensemble’s instantaneous distribution as a proposal, it achieves very fast burnin, followed by sampling with very short autocorrelation times.

[ascl:2106.001]
KOBE: Kepler Observes Bern Exoplanets

KOBE (Kepler Observes Bern Exoplanets) adds the geometrical limitations and the physical detection biases of the transit method to a given population of theoretical planets. In addition, it also adds the completeness and reliability of a transit survey.

[ascl:1606.012]
KMDWARFPARAM: Parameters estimator for K and M dwarf stars

KMDWARFPARAM estimates the physical parameters of a star with mass M < 0.8 M_sun given one or more observational constraints. The code runs a Markov-Chain Monte Carlo procedure to estimate the parameter values and their uncertainties.

[ascl:2008.003]
KLLR: Kernel Localized Linear Regression

Farahi, Arya; Evrard, August E.; McCarthy, Ian; Barnes, David J.; Kay, Scott T.; Anbajagane, Dhayaa; Dolag, Klaus; McCarthy, Ian G.; Nelson, Dylan; Pillepich, Annalisa

KLLR (Kernel Localized Linear Regression) generates estimates of conditional statistics in terms of the local slope, normalization, and covariance. This method provides a more nuanced description of population statistics appropriate for very large samples with non-linear trends. The code uses a bootstrap re-sampling technique to estimate the uncertainties and also provides tools to seamlessly generate visualizations of the model parameters.

[submitted]
Kliko - The Scientific Compute Container Format

We present Kliko, a Docker based container specification for running one or multiple related compute jobs. The key concepts of Kliko is the encapsulation of data processing software into a container and the formalisation of the input, output and task parameters. Formalisation is realised by bundling a container with a Kliko file, which describes the IO and task parameters. This Kliko container can then be opened and run by a Kliko runner. The Kliko runner will parse the Kliko definition and gather the values for these parameters, for example by requesting user input or pre defined values in a script. Parameters can be various primitive types, for example float, int or the path to a file. This paper will also discuss the implementation of a support library named Kliko which can be used to create Kliko containers, parse Kliko definitions, chain Kliko containers in workflows using, for example, Luigi a workflow manager. The Kliko library can be used inside the container interact with the Kliko runner. Finally this paper will discuss two reference implementations based on Kliko: RODRIGUES, a web based Kliko container schedular and output visualiser specifically for astronomical data, and VerMeerKAT, a multi container workflow data reduction pipeline which is being used as a prototype pipeline for the commisioning of the MeerKAT radio telescope.

[ascl:1401.001]
Kirin: N-body simulation library for GPUs

The use of graphics processing units offers an attractive alternative to specialized hardware, like GRAPE. The Kirin library mimics the behavior of the GRAPE hardware and uses the GPU to execute the force calculations. It is compatible with the GRAPE6 library; existing code that uses the GRAPE6 library can be recompiled and relinked to use the GPU equivalents of the GRAPE6 functions. All functions in the GRAPE6 library have an equivalent GPU implementation. Kirin can be used for direct N-body simulations as well as for treecodes; it can be run with shared-time steps or with block time-steps and allows non-softened potentials. As Kirin makes use of CUDA, it works only on NVIDIA GPUs.

[ascl:2006.003]
KinMS: Three-dimensional kinematic modeling of arbitrary gas distributions

The KinMS (KINematic Molecular Simulation) package simulates observations of arbitrary molecular/atomic cold gas distributions from interferometers and line observations from integral field units. This modeling tool is optimized for situations where one has analytic forms for *e.g.* the rotation curve and/or surface brightness profiles (and may want to fit the parameters of these parametric models). It can, however, also be used as a tilted-ring modelling code. The routines are flexible and have been used in various different applications, including investigating the kinematics of molecular gas in early-type galaxies and determining supermassive black-hole masses from CO interferometric observations. They are also useful for creating mock observations from hydrodynamic simulations, and input data-cubes for further simulation in, for example, CASA's (ascl:1107.013) sim_observe tool. Interactive Data Language (IDL) and Python versions of the code are available.

[ascl:2008.001]
kinesis: Kinematic modeling of clusters

Kinesis fits the internal kinematics of a star cluster with astrometry and (incomplete) radial velocity data of its members. In the most general model, the stars can be a mixture of background (contamination) and the cluster, for which the (3,3) velocity dispersion matrix and velocity gradient (*i.e.*, dv_x/dx and dv_y/dx) are included. There are also simpler versions of the most general model and utilities to generate mock clusters and mock observations.

[ascl:1403.019]
KINEMETRY: Analysis of 2D maps of kinematic moments of LOSVD

KINEMETRY, written in IDL, analyzes 2D maps of the moments of the line-of-sight velocity distribution (LOSVD). It generalizes the surface photometry to all moments of the LOSVD. It performs harmonic expansion of 2D maps of observed moments (surface brightness, velocity, velocity dispersion, h3, h4, etc.) along the best fitting ellipses (either fixed or free to change along the radii) to robustly quantify maps of the LOSVD moments, describe trends in structures, and detect morphological and kinematic sub-components.

[ascl:2403.003]
kinematic_scaleheight: Infer the vertical distribution of clouds in the solar neighborhood

kinematic_scaleheight uses MCMC methods to kinematically estimate the vertical distribution of clouds in the Galactic plane, including the least squares analysis of Crovisier (1978), an updated least squares analysis using a modern Galactic rotation model, and a Bayesian model sampled via MCMC as described in Wenger et al. (2024).

[ascl:2302.014]
kima: Exoplanet detection in RVs with DNest4 and GPs

kima fits Keplerian curves to a set of RV measurements, using the Diffusive Nested Sampling (ascl:1010.029) algorithm to sample the posterior distribution for the model parameters. Additionally, the code can calculate the fully marginalized likelihood of a model with a given number of Keplerians and also infer the number of Keplerian signals detected in a given dataset. kima implements dedicated models for different analyses of a given dataset. The models share a common organization, but each has its own parameters (and thus priors) and settings.

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

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

[ascl:2305.005]
killMS: Direction-dependent radio interferometric calibration package

killMS implements two very efficient algorithms for solving the Direction-Dependent calibration problem (also known as third generation calibration). This problem naturally arises in the Radio Interferometry Measurement Equation (RIME), but only became overwhelmingly problematic with the construction of the SKA precursors and pathfinders. Solving for the DDE calibration problem basically consists in inverting a number of non-linear equations, while the system is very large and often subject to ill conditioning. The two algorithms killMS uses are based on complex optimization techniques and exploit algorithmic shortcuts; killMS also runs an extended Kalman filter.

[ascl:2011.027]
kiauhoku: Stellar model grid interpolation

Claytor, Zachary R.; van Saders, Jennifer L.; Santos, Ângela R. G.; García, Rafael A.; Mathur, Savita; Tayar, Jamie; Pinsonneault, Marc H.; Shetrone, Matthew

Kiauhoku interacts with, manipulates, and interpolates between stellar evolutionary tracks in a model grid. It was built for interacting with YREC models, but other stellar evolution model grids, including MIST, Dartmouth, and GARSTEC, are also available.

[ascl:1502.020]
ketu: Exoplanet candidate search code

ketu, written in Python, searches K2 light curves for evidence of exoplanets; the code simultaneously fits for systematic effects caused by small (few-pixel) drifts in the telescope pointing and other spacecraft issues and the transit signals of interest. Though more computationally expensive than standard search algorithms, it can be efficiently implemented and used to discover transit signals.

[ascl:1708.021]
KERTAP: Strong lensing effects of Kerr black holes

KERTAP computes the strong lensing effects of Kerr black holes, including the effects on polarization. The key ingredients of KERTAP are a graphic user interface, a backward ray-tracing algorithm, a polarization propagator dealing with gravitational Faraday rotation, and algorithms computing observables such as flux magnification and polarization angles.

[ascl:2305.012]
KERN: Radio telescope toolkit

KERN contains most of the standard tools needed to work with radio telescope data. The suite saves time and reduces frustration in setting up of scientific pipelines, and also improves scientific reproducibility. It includes a wide variety of packages, including 21cmfast (ascl:1102.023), BRATS (ascl:1806.025), CARTA (ascl:2103.031), casacore (ascl:1912.002), CubiCal (ascl:1805.031), DDFacet (ascl:2305.008), PyBDSF (ascl:1502.007),TiRiFiC (ascl:1208.008), WSClean (ascl:1408.023), and many others. KERN can be run on a supported platform such as Ubuntu, with Docker and Singularity, or in a virtual machine.

[ascl:1806.022]
Keras: The Python Deep Learning library

Keras is a high-level neural networks API written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It focuses on enabling fast experimentation.

[ascl:1706.012]
KeplerSolver: Kepler equation solver

KeplerSolver solves Kepler's equation for arbitrary epoch and eccentricity, using continued fractions. It is written in C and its speed is nearly the same as the SWIFT routines, while achieving machine precision. It comes with a test program to demonstrate usage.

[ascl:2107.027]
KeplerPORTS: Kepler Planet Occurrence Rate Tools

KeplerPORTS calculates the detection efficiency of the DR25 Kepler Pipeline. It uses a detection contour model to quantify the recoverability of transiting planet signals due to the Kepler pipeline, and accurately portrays the ability of the Kepler pipeline to generate a Threshold Crossing Event (TCE) for a given hypothetical planet.

[ascl:2308.012]
KeplerFit: Keplerian velocity distribution model fitter

Bosco, Felix; Beuther, H.; Ahmadi, A.; Mottram, J. C; Kuiper, R.; Linz, H.; Maud, L.; Winters, J. M.; Henning, T.; Feng, S.; Peters, T.; Semenov, D.; Klaassen, P. D.; Schilke, P.; Urquhart, J. S.; Beltrán, M. T.; Lumsden, S. L.; Leurini, S.; Moscadelli, L.; Cesaroni, R.; Sánchez-Monge, Á.; Palau, A.; Pudritz, R.; Wyrowski, F.; Longmore, S.

KeplerFit fits a Keplerian velocity distribution model to position-velocity (PV) data to obtain an estimate of the enclosed mass. The code extracts the scales of the pixels in both directions, spatial and spectral, then extracts the most extreme velocity at each position; this returns two arrays of positions and velocities. KeplerFit then models the extracted PV data and returns a set of the best-fit parameters, the standard deviations in each of the parameters, and the total residual of the fit.

[ascl:2105.021]
Kepler's Goat Herd: Solving Kepler's equation via contour integration

Kepler's Goat Herd solves Kepler's equation using contour integration to solve the "geometric goat problem". The C++ code implements a variety of solution: 1.) Newton-Raphson: The quadratic Newton-Raphson root finder; 2.) Danby: The quartic root; 3.) Series: An elliptical series method; and 4.) Contour: A new method based on contour integration. Given an array of mean anomalies, an eccentricity and a desired precision, the code estimates the eccentric anomaly using each method. The accuracy of each approach is increased until the desired precision is reached, and timing is performed using the C++ chrono package.

[ascl:1702.007]
KEPLER: General purpose 1D multizone hydrodynamics code

KEPLER is a general purpose stellar evolution/explosion code that incorporates implicit hydrodynamics and a detailed treatment of nuclear burning processes. It has been used to study the complete evolution of massive and supermassive stars, all major classes of supernovae, hydrostatic and explosive nucleosynthesis, and x- and gamma-ray bursts on neutron stars and white dwarfs.

[ascl:1712.001]
KDUtils: Kinematic Distance Utilities

The Kinematic Distance utilities (KDUtils) calculate kinematic distances and kinematic distance uncertainties. The package includes methods to calculate "traditional" kinematic distances as well as a Monte Carlo method to calculate kinematic distances and uncertainties.

[ascl:2301.018]
kderp: Keck Cosmic Web Imager Data Extraction and Reduction Pipeline in IDL

kderp (KCWI Data Extraction and Reduction Pipeline) reduces data for the Keck Cosmic Web Imager. Written in IDL, it performs basic CCD reduction on raw images to produce bias and overscan subtracted, gain-corrected, trimmed and cosmic ray removed images; it can also subtract the sky. It defines the geometric transformations required to map each pixel in the 2d image into slice, postion, and wavelength, and performs flat field and illumination corrections. It generates cubes, applying the transformations previously solved to the object intensity, variance and mask images output from any of the previous stages, and uses a standard star observation to generate an inverse sensitivity curve which is applied to the corresponding observations to flux calibrate them.

This pipeline has been superseded by KCWI_DRP (ascl:2301.019).

[ascl:2107.022]
Kd-match: Correspondences of objects between two catalogs through pattern matching

Kd-match matches stellar catalogs for which the transformation between the coordinate systems of the two catalogs is unknown and might include shearing. The code uses the ratio of sides as the invariant under a coordinate transformation and searches for several triangles with similar transformations by building quadrilaterals from sets of four objects in each catalog and calculating the ratio of areas of the triangles that comprise the quadrilaterals. The k-d tree accelerates this quadrilateral search dramatically and is significantly faster than the customary direct search over triangles.

[ascl:2404.003]
KCWIKit: KCWI Post-Processing and Improvements

KCWIKit extends the official KCWI DRP (ascl:2301.019) with a variety of stacking tools and DRP improvements. The software offers masking and median filtering scripts to be used while running the KCWI DRP, and a step-by-step KCWI_DRP implementation for finer control over the reduction process. Once the DRP has finished, KCWIKit can be used to stack the output cubes via the Montage package. Various functions cross-correlate and mosaic the constituent cubes and the final stacked cubes are WCS corrected. Helper functions can then be used to deproject the stacked cube into lower-dimensional representations should the user desire.

[ascl:2301.019]
KCWI_DRP: Keck Cosmic Web Imager Data Reduction Pipeline in Python

KCWI_DRP, written in Python and based on kderp (ascl:2301.018), is the official DRP for the Keck Cosmic Web Imager at the W. M. Keck Observatory. It provides all of the functionality of the older pipeline and has three execution modes: multi-threading for CPU intensive tasks such as wavelength calibration, and multi-processing for large datasets. It offers vacuum to air and heliocentric or barycentric correction and the ability to use KOA file names or original file names. KCWI_DRP also improves the provenance and traceability of DRP versions and execution steps in the headers over kderp, and has versatile sky subtraction modes including using external sky frames and ability of masking regions.

[ascl:1701.010]
kcorrect: Calculate K-corrections between observed and desired bandpasses

kcorrect fits very restricted spectral energy distribution models to galaxy photometry or spectra in the restframe UV, optical and near-infrared. The main purpose of the fits are for calculating K-corrections. The templates used for the fits may also be interpreted physically, since they are based on the Bruzual-Charlot stellar evolution synthesis codes. Thus, for each fit galaxy kcorrect can provide an estimate of the stellar mass-to-light ratio.

[ascl:2211.002]
KC: Analytical propagator with collision detection for Keplerian systems

The analytic propagator Kepler-Collisions calculates collisions for Keplerian systems. The algorithm maintains a list of collision possibilities and jumps from one collision to the next; since collisions are rare in astronomical scales, jumping from collision to collision and calculating each one is more efficient than calculating all the time steps that are between collisions.

[ascl:1701.005]
KAULAKYS: Inelastic collisions between hydrogen atoms and Rydberg atoms

KAULAKYS calculates cross sections and rate coefficients for inelastic collisions between Rydberg atoms and hydrogen atoms according to the free electron model of Kaulakys (1986, 1991). It is written in IDL and requires the code MSWAVEF (ascl:1701.006) to calculate momentum-space wavefunctions. KAULAKYS can be easily adapted to collisions with perturbers other than hydrogen atoms by providing the appropriate scattering amplitudes.

[ascl:2106.026]
Katu: Interaction of particles in plasma simulator

Katu evolves the interaction of particles (photons, protons, neutrons, leptons, pions and neutrinos) in plasma. The package comes with wrappers for emcee (ascl:1303.002) and pymultinest (ascl:1606.005) for Bayesian analysis, making the software applicable to blazars and able to extract relevant statistical information from their electromagnetic (and neutrino, if applicable) flux. The code is optimized for fast performance, and can be easily modified and extended.

[ascl:2305.004]
katdal: MeerKAT Data Access Library

katdal interacts with the chunk stores and HDF5 files produced by the MeerKAT radio telescope and its predecessors (KAT-7 and Fringe Finder), which are collectively known as MeerKAT Visibility Format (MVF) data sets. The library uses memory carefully, allowing data sets to be inspected and partially loaded into memory. Data sets may be concatenated and split via a flexible selection mechanism. In addition, katdal provides a script to convert these data sets to CASA MeasurementSets.

[ascl:2209.006]
KaRMMa: Curved-sky mass map reconstruction

KaRMMa (Kappa Reconstruction for Mass MApping) performs curved-sky mass map reconstruction using a lognormal prior from weak-lensing surveys. It uses a fully Bayesian approach with a physically motivated lognormal prior to sample from the posterior distribution of convergence maps. The posterior distribution of KaRMMa maps are nearly unbiased in one-point and two-point functions and peak/void counts. KaRMMa successfully captures the non-Gaussian nature of the distribution of κ values in the simulated maps, and KaRMMa posteriors correctly characterize the uncertainty in summary statistics.

[ascl:1102.018]
Karma: Visualisation Test-Bed Toolkit

Karma is a toolkit for interprocess communications, authentication, encryption, graphics display, user interface and manipulating the Karma network data structure. It contains KarmaLib (the structured libraries and API) and a large number of modules (applications) to perform many standard tasks. A suite of visualisation tools are distributed with the library.

[ascl:1611.010]
Kapteyn Package: Tools for developing astronomical applications

The Kapteyn Package provides tools for the development of astronomical applications with Python. It handles spatial and spectral coordinates, WCS projections and transformations between different sky systems; spectral translations (e.g., between frequencies and velocities) and mixed coordinates are also supported. Kapteyn offers versatile tools for writing small and dedicated applications for the inspection of FITS headers, the extraction and display of (FITS) data, interactive inspection of this data (color editing) and for the creation of plots with world coordinate information. It includes utilities for use with matplotlib such as obtaining coordinate information from plots, interactively modifiable colormaps and timer events (module mplutil); tools for parsing and interpreting coordinate information entered by the user (module positions); a function to search for gaussian components in a profile (module profiles); and a class for non-linear least squares fitting (module kmpfit).

[ascl:1502.008]
KAPPA: Optically thin spectra synthesis for non-Maxwellian kappa-distributions

Based on the freely available CHIANTI (ascl:9911.004) database and software, KAPPA synthesizes line and continuum spectra from the optically thin spectra that arise from collisionally dominated astrophysical plasmas that are the result of non-Maxwellian κ-distributions detected in the solar transition region and flares. Ionization and recombination rates together with the ionization equilibria are provided for a range of κ values. Distribution-averaged collision strengths for excitation are obtained by an approximate method for all transitions in all ions available within CHIANTI; KAPPA also offers tools for calculating synthetic line and continuum intensities.

[ascl:1403.022]
KAPPA: Kernel Applications Package

KAPPA comprising about 180 general-purpose commands for image processing, data visualization, and manipulation of the standard Starlink data format--the NDF. It works with Starlink's various specialized packages; in addition to the NDF, KAPPA can also process data in other formats by using the "on-the-fly" conversion scheme. Many commands can process data arrays of arbitrary dimension, and others work on both spectra and images. KAPPA operates from both the UNIX C-shell and the ICL command language. KAPPA uses the Starlink environment (ascl:1110.012).

[ascl:1906.005]
Kalman: Forecasts and interpolations for ALMA calibrator variability

Kalman models an inhomogeneous time series of measurements at different frequencies as noisy sampling from a finite mixture of Gaussian Ornstein-Uhlenbeck processes to try to reproduce the variability of the fluxes and of the spectral indices of the quasars used as calibrators in the Atacama Large Millimeter/Sub-millimeter Array (ALMA), assuming sensible parameters are provided to the model (obtained, for example, from maximum likelihood estimation). One routine in the Kalman Perl module calculates best forecast estimations based on a state space representation of the stochastic model using Kalman recursions, and another routine calculates the smoothed estimation (or interpolations) of the measurements and of the state space also using Kalman recursions. The code does not include optimization routines to calculate best fit parameters for the stochastic processes.

[ascl:2011.003]
Kalkayotl: Inferring distances to stellar clusters from Gaia parallaxes

Olivares, J.; Sarro, L. M.; Bouy, H.; Miret-Roig, N.; Casamiquela, L.; Galli, P. A. B.; Berihuete, A.; Tarricq, Y.

Kalkayotl obtains samples of the joint posterior distribution of cluster parameters and distances to the cluster stars from Gaia parallaxes using Bayesian inference. The code is designed to deal with the parallax spatial correlations of Gaia data, and can accommodate different values of parallax zero point and spatial correlation functions.

[ascl:1607.013]
Kālī: Time series data modeler

The fully parallelized and vectorized software package Kālī models time series data using various stochastic processes such as continuous-time ARMA (C-ARMA) processes and uses Bayesian Markov Chain Monte-Carlo (MCMC) for inferencing a stochastic light curve. Kālī is written in c++ with Python language bindings for ease of use. Kālī is named jointly after the Hindu goddess of time, change, and power and also as an acronym for KArma LIbrary.

[ascl:1803.005]
Kadenza: Kepler/K2 Raw Cadence Data Reader

Kadenza enables time-critical data analyses to be carried out using NASA's Kepler Space Telescope. It enables users to convert Kepler's raw data files into user-friendly Target Pixel Files upon downlink from the spacecraft. The primary motivation for this tool is to enable the microlensing, supernova, and exoplanet communities to create quicklook lightcurves for transient events which require rapid follow-up.

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