Results 1201-1300 of 2287 (2246 ASCL, 41 submitted)

[ascl:1705.008]
MBProj2: Multi-Band x-ray surface brightness PROJector 2

MBProj2 obtains thermodynamic profiles of galaxy clusters. It forward-models cluster X-ray surface brightness profiles in multiple bands, optionally assuming hydrostatic equilibrium. The code is a set of Python classes the user can use or extend. When modelling a cluster assuming hydrostatic equilibrium, the user chooses a form for the density profile (e.g. binning or a beta model), the metallicity profile, and the dark matter profile (e.g. NFW). If hydrostatic equilibrium is not assumed, a temperature profile model is used instead of the dark matter profile. The code uses the emcee Markov Chain Monte Carlo code (ascl:1303.002) to sample the model parameters, using these to produce chains of thermodynamic profiles.

[ascl:1703.014]
MC-SPAM: Monte-Carlo Synthetic-Photometry/Atmosphere-Model

MC-SPAM (Monte-Carlo Synthetic-Photometry/Atmosphere-Model) generates limb-darkening coefficients from models that are comparable to transit photometry; it extends the original SPAM algorithm by Howarth (2011) by taking in consideration the uncertainty on the stellar and transit parameters of the system under analysis.

[ascl:1610.013]
MC^{3}: Multi-core Markov-chain Monte Carlo code

Cubillos, Patricio; Harrington, Joseph; Lust, Nate; Foster, AJ; Stemm, Madison; Loredo, Tom; Stevenson, Kevin; Campo, Chris; Hardin, Matt; Hardy, Ryan

MC^{3} (Multi-core Markov-chain Monte Carlo) is a Bayesian statistics tool that can be executed from the shell prompt or interactively through the Python interpreter with single- or multiple-CPU parallel computing. It offers Markov-chain Monte Carlo (MCMC) posterior-distribution sampling for several algorithms, Levenberg-Marquardt least-squares optimization, and uniform non-informative, Jeffreys non-informative, or Gaussian-informative priors. MC^{3} can share the same value among multiple parameters and fix the value of parameters to constant values, and offers Gelman-Rubin convergence testing and correlated-noise estimation with time-averaging or wavelet-based likelihood estimation methods.

[ascl:1204.005]
MC3D: Monte-Carlo 3D Radiative Transfer Code

MC3D is a 3D continuum radiative transfer code; it is based on the Monte-Carlo method and solves the radiative transfer problem self-consistently. It is designed for the simulation of dust temperatures in arbitrary geometric configurations and the resulting observables: spectral energy distributions, wavelength-dependent images, and polarization maps. The main objective is the investigation of "dust-dominated" astrophysical systems such as young stellar objects surrounded by an optically thick circumstellar disk and an optically thin(ner) envelope, debris disks around more evolved stars, asymptotic giant branch stars, the dust component of the interstellar medium, and active galactic nuclei.

[ascl:1511.008]
MCAL: M dwarf metallicity and temperature calculator

MCAL calculates high precision metallicities and effective temperatures for M dwarfs; the method behaves properly down to R = 40 000 and S/N = 25, and results were validated against a sample of stars in common with SOPHIE high resolution spectra.

[ascl:1906.017]
mcfit: Multiplicatively Convolutional Fast Integral Transforms

mcfit computes integral transforms, inverse transforms without analytic inversion, and integral kernels as derivatives. It can also transform input array along any axis, output the matrix form, an is easily extensible for other kernels.

[ascl:1107.015]
McLuster: A Tool to Make a Star Cluster

The tool McLuster is an open source code that can be used to either set up initial conditions for N-body computations or, alternatively, to generate artificial star clusters for direct investigation. There are two different versions of the code, one basic version for generating all kinds of unevolved clusters (in the following called mcluster) and one for setting up evolved stellar populations at a given age. The former is completely contained in the C file main.c. The latter (dubbed mcluster_sse) is more complex and requires additional FORTRAN routines, namely the Single-Star Evolution (SSE) routines by Hurley, Pols & Tout (ascl:1303.015) that are provided with the McLuster code.

[ascl:1407.004]
MCMAC: Monte Carlo Merger Analysis Code

Monte Carlo Merger Analysis Code (MCMAC) aids in the study of merging clusters. It takes observed priors on each subcluster's mass, radial velocity, and projected separation, draws randomly from those priors, and uses them in a analytic model to get posterior PDF's for merger dynamic properties of interest (e.g. collision velocity, time since collision).

[ascl:2001.012]
MCMCI: Markov Chain Monte Carlo + Isochrones method for characterizing exoplanetary systems

MCMCI (Markov chain Monte Carlo + isochrones) characterizes a whole exoplanetary system directly by modeling the star and its planets simultaneously. The code, written in Fortran, uses light curves and basic stellar parameters with a transit analysis algorithm that interacts with stellar evolutionary models, thus using both model-dependent and empirical age indicators to characterize the system.

[ascl:1210.017]
McPHAC: McGill Planar Hydrogen Atmosphere Code

The McGill Planar Hydrogen Atmosphere Code (McPHAC) v1.1 calculates the hydrostatic equilibrium structure and emergent spectrum of an unmagnetized hydrogen atmosphere in the plane-parallel approximation at surface gravities appropriate for neutron stars. McPHAC incorporates several improvements over previous codes for which tabulated model spectra are available: (1) Thomson scattering is treated anisotropically, which is shown to result in a 0.2%-3% correction in the emergent spectral flux across the 0.1-5 keV passband; (2) the McPHAC source code is made available to the community, allowing it to be scrutinized and modified by other researchers wishing to study or extend its capabilities; and (3) the numerical uncertainty resulting from the discrete and iterative solution is studied as a function of photon energy, indicating that McPHAC is capable of producing spectra with numerical uncertainties <0.01%. The accuracy of the spectra may at present be limited to ~1%, but McPHAC enables researchers to study the impact of uncertain inputs and additional physical effects, thereby supporting future efforts to reduce those inaccuracies. Comparison of McPHAC results with spectra from one of the previous model atmosphere codes (NSA) shows agreement to lsim1% near the peaks of the emergent spectra. However, in the Wien tail a significant deficit of flux in the spectra of the previous model is revealed, determined to be due to the previous work not considering large enough optical depths at the highest photon frequencies. The deficit is most significant for spectra with T eff < 105.6 K, though even there it may not be of much practical importance for most observations.

[ascl:2005.019]
MCRaT: Monte Carlo Radiation Transfer

MCRaT (Monte Carlo Radiation Transfer) analyzes the radiation signature expected from astrophysical outflows. MCRaT injects photons in a FLASH (ascl:1010.082) simulation and individually propagates and compton scatters the photons through the fluid until the end of the simulation. This process of injection and propagating occurs for a user specified number of times until there are no more photons to be injected. Users can then construct light curves and spectra with the MCRaT calculated results. The hydrodynamic simulations used with this version of MCRaT must be in 2D; however, the photon propagation and scattering is done in 3D by assuming cylindrical symmetry. Additionally, MCRaT uses the full Klein–Nishina cross section including the effects of polarization, which can be fully simulated in the code. MCRaT works with FLASH hydrodynamic simulations and PLUTO (ascl:1010.045) AMR simulations, with both 2D spherical (r, equation) and 2D cartesian ((x,y) and (r,z)).

[ascl:1907.026]
MCRGNet: Morphological Classification of Radio Galaxy Network

MCRGNet (Morphological Classification of Radio Galaxy Network) classifies radio galaxies of different morphologies. It is based on the Convolutional Neural Network (CNN), which is trained and applied under a three-step framework: 1.) pretraining the network unsupervisedly with unlabeled samples, 2.) fine-tuning the pretrained network parameters supervisedly with labeled samples, and 3.) classifying a new radio galaxy by the trained network. The code uses a dichotomous tree classifier composed of cascaded CNN based subclassifiers.

[ascl:1201.001]
McScatter: Three-Body Scattering with Stellar Evolution

McScatter illustrates a method of combining stellar dynamics with stellar evolution. The method is intended for elaborate applications, especially the dynamical evolution of rich star clusters. The dynamics is based on binary scattering in a multi-mass field of stars with uniform density and velocity dispersion, using the scattering cross section of Giersz (MNRAS, 2001, 324, 218-30).

[ascl:2006.022]
MCSED: Spectral energy distribution fitting package for galactic systems

MCSED models the optical, near-infrared and infrared spectral energy distribution (SED) of galactic systems. Its modularity and options make it flexible and able to address the varying physical properties of galaxies over cosmic time and environment and adjust to changes in understanding of stellar evolution, the details of mass loss, and the products of binary evolution through substitution or addition of new datasets or algorithms. MCSED is built to fit a galaxy’s full SED, from the far-UV to the far-IR. Among other physical processes, it can model continuum emission from stars, continuum and line-emission from ionized gas, attenuation from dust, and mid- and far-IR emission from dust and polycyclic aromatic hydrocarbons (PAHs). MCSED performs its calculations by creating a complex stellar population (CSP) out of a linear combination of simple-stellar populations (SSPs) using an efficient Markov Chain Monte Carlo algorithm. It is very quick, and takes advantage of parallel processing.

[ascl:1504.008]
MCSpearman: Monte Carlo error analyses of Spearman's rank test

Spearman’s rank correlation test is commonly used in astronomy to discern whether a set of two variables are correlated or not. Unlike most other quantities quoted in astronomical literature, the Spearman’s rank correlation coefficient is generally quoted with no attempt to estimate the errors on its value. This code implements a number of Monte Carlo based methods to estimate the uncertainty on the Spearman’s rank correlation coefficient.

[ascl:1302.012]
ME(SSY)**2: Monte Carlo Code for Star Cluster Simulations

ME(SSY)**2 stands for “Monte-carlo Experiments with Spherically SYmmetric Stellar SYstems." This code simulates the long term evolution of spherical clusters of stars; it was devised specifically to treat dense galactic nuclei. It is based on the pioneering Monte Carlo scheme proposed by Hénon in the 70's and includes all relevant physical ingredients (2-body relaxation, stellar mass spectrum, collisions, tidal disruption, ldots). It is basically a Monte Carlo resolution of the Fokker-Planck equation. It can cope with any stellar mass spectrum or velocity distribution. Being a particle-based method, it also allows one to take stellar collisions into account in a very realistic way. This unique code, featuring most important physical processes, allows million particle simulations, spanning a Hubble time, in a few CPU days on standard personal computers and provides a wealth of data only rivalized by N-body simulations. The current version of the software requires the use of routines from the "Numerical Recipes in Fortran 77" (http://www.nrbook.com/a/bookfpdf.php).

[ascl:1205.001]
Mechanic: Numerical MPI framework for dynamical astronomy

The Mechanic package is a numerical framework for dynamical astronomy, designed to help in massive numerical simulations by efficient task management and unified data storage. The code is built on top of the Message Passing Interface (MPI) and Hierarchical Data Format (HDF5) standards and uses the Task Farm approach to manage numerical tasks. It relies on the core-module approach. The numerical problem implemented in the user-supplied module is separated from the host code (core). The core is designed to handle basic setup, data storage and communication between nodes in a computing pool. It has been tested on large CPU-clusters, as well as desktop computers. The Mechanic may be used in computing dynamical maps, data optimization or numerical integration.

[ascl:1106.006]
MECI: A Method for Eclipsing Component Identification

We describe an automated method for assigning the most probable physical parameters to the components of an eclipsing binary, using only its photometric light curve and combined colors. With traditional methods, one attempts to optimize a multi-parameter model over many iterations, so as to minimize the chi-squared value. We suggest an alternative method, where one selects pairs of coeval stars from a set of theoretical stellar models, and compares their simulated light curves and combined colors with the observations. This approach greatly reduces the parameter space over which one needs to search, and allows one to estimate the components' masses, radii and absolute magnitudes, without spectroscopic data. We have implemented this method in an automated program using published theoretical isochrones and limb-darkening coefficients. Since it is easy to automate, this method lends itself to systematic analyses of datasets consisting of photometric time series of large numbers of stars, such as those produced by OGLE, MACHO, TrES, HAT, and many others surveys.

[ascl:1906.018]
MEGAlib: Medium Energy Gamma-ray Astronomy library

The Medium Energy Gamma-ray Astronomy library (MEGAlib) simulates, calibrates, and analyzes data of hard X-ray and gamma-ray detectors, with a specialization on Compton telescopes. The library comprises all necessary data analysis steps for these telescopes, from simulation/measurements via calibration, event reconstruction to image reconstruction.

MEGAlib contains a geometry and detector description tool for the detailed modeling of different detector types and characteristics, and provides an easy to use simulation program based on Geant4 (ascl:1010.079). For different Compton telescope detector types (electron tracking, multiple Compton or time of flight based), specialized Compton event reconstruction algorithms are implemented in different approaches (Chi-square and Bayesian). The high level data analysis tools calculate response matrices, perform image deconvolution (specialized in list-mode-likelihood-based Compton image reconstruction), determine detector resolutions and sensitivities, retrieve spectra, and determine polarization modulations.

[ascl:1203.008]
MegaLUT: Correcting ellipticity measurements of galaxies

MegaLUT is a simple and fast method to correct ellipticity measurements of galaxies from the distortion by the instrumental and atmospheric point spread function (PSF), in view of weak lensing shear measurements. The method performs a classification of galaxies and associated PSFs according to measured shape parameters, and builds a lookup table of ellipticity corrections by supervised learning. This new method has been applied to the GREAT10 image analysis challenge, and demonstrates a refined solution that obtains the highly competitive quality factor of Q = 142, without any power spectrum denoising or training. Of particular interest is the efficiency of the method, with a processing time below 3 ms per galaxy on an ordinary CPU.

[ascl:1711.012]
megaman: Manifold Learning for Millions of Points

megaman is a scalable manifold learning package implemented in python. It has a front-end API designed to be familiar to scikit-learn but harnesses the C++ Fast Library for Approximate Nearest Neighbors (FLANN) and the Sparse Symmetric Positive Definite (SSPD) solver Locally Optimal Block Precodition Gradient (LOBPCG) method to scale manifold learning algorithms to large data sets. It is designed for researchers and as such caches intermediary steps and indices to allow for fast re-computation with new parameters.

[ascl:1410.002]
MEPSA: Multiple Excess Peak Search Algorithm

MEPSA (Multiple Excess Peak Search Algorithm) identifies peaks within a uniformly sampled time series affected by uncorrelated Gaussian noise. MEPSA scans the time series at different timescales by comparing a given peak candidate with a variable number of adjacent bins. While this has originally been conceived for the analysis of gamma-ray burst light (GRB) curves, its usage can be readily extended to other astrophysical transient phenomena whose activity is recorded through different surveys. MEPSA's high flexibility permits the mask of excess patterns it uses to be tailored and optimized without modifying the code.

[ascl:1209.010]
MeqTrees: Software package for implementing Measurement Equations

MeqTrees is a software package for implementing Measurement Equations. This makes it uniquely suited for simulation and calibration of radioastronomical data, especially that involving new radiotelescopes and observational regimes. MeqTrees is implemented as a Python-based front-end called the meqbrowser, and an efficient (C++-based) computational back-end called the meqserver. Numerical models are defined on the front-end via a Python-based Tree Definition Language (TDL), then rapidly executed on the back-end. The use of TDL facilitates an extremely short turn-around time for experimentation with new ideas. This is also helped by unprecedented visualization capabilities for all final and intermediate results. A flexible data model and a number of important optimizations in the back-end ensures that the numerical performance is comparable to that of hand-written code.

MeqTrees includes a highly capable FITS viewer and sky model manager called Tigger, which can also work as a standalone tool.

[submitted]
MERA: Analysis Tool for Astrophysical Simulation Data in the Julia Language

MERA works with large 3D AMR/uniform-grid and N-body particle data sets from astrophysical simulations such as those produced by the hydrodynamic code RAMSES (ascl:1011.007) and is written entirely in the Julia language. The package provides essential functions for efficient and memory lightweight data loading and analysis. The core of MERA is a database framework.

[ascl:1511.020]
Mercury-T: Tidally evolving multi-planet systems code

Mercury-T calculates the evolution of semi-major axis, eccentricity, inclination, rotation period and obliquity of the planets as well as the rotation period evolution of the host body; it is based on the N-body code Mercury (Chambers 1999, ascl:1201.008). It is flexible, allowing computation of the tidal evolution of systems orbiting any non-evolving object (if its mass, radius, dissipation factor and rotation period are known), but also evolving brown dwarfs (BDs) of mass between 0.01 and 0.08 M⊙, an evolving M-dwarf of 0.1 M⊙, an evolving Sun-like star, and an evolving Jupiter.

[ascl:1201.008]
Mercury: A software package for orbital dynamics

Mercury is a new general-purpose software package for carrying out orbital integrations for problems in solar-system dynamics. Suitable applications include studying the long-term stability of the planetary system, investigating the orbital evolution of comets, asteroids or meteoroids, and simulating planetary accretion. Mercury is designed to be versatile and easy to use, accepting initial conditions in either Cartesian coordinates or Keplerian elements in "cometary" or "asteroidal" format, with different epochs of osculation for different objects. Output from an integration consists of osculating elements, written in a machine-independent compressed format, which allows the results of a calculation performed on one platform to be transferred (e.g. via FTP) and decoded on another.

During an integration, Mercury monitors and records details of close encounters, sungrazing events, ejections and collisions between objects. The effects of non-gravitational forces on comets can also be modeled. The package supports integrations using a mixed-variable symplectic routine, the Bulirsch-Stoer method, and a hybrid code for planetary accretion calculations.

[ascl:1305.015]
Merger Trees: Formation history of dark matter haloes

Merger Trees uses a Monte Carlo algorithm to generate merger trees describing the formation history of dark matter haloes; the algorithm is implemented in Fortran. The algorithm is a modification of the algorithm of Cole et al. used in the GALFORM semi-analytic galaxy formation model (ascl:1510.005) based on the Extended Press–Schechter theory. It should be applicable to hierarchical models with a wide range of power spectra and cosmological models. It is tuned to be in accurate agreement with the conditional mass functions found in the analysis of merger trees extracted from the Λ cold dark matter Millennium N-body simulation. The code should be a useful tool for semi-analytic models of galaxy formation and for modelling hierarchical structure formation in general.

[ascl:1010.083]
MESA: Modules for Experiments in Stellar Astrophysics

Stellar physics and evolution calculations enable a broad range of research in astrophysics. Modules for Experiments in Stellar Astrophysics (MESA) is a suite of open source libraries for a wide range of applications in computational stellar astrophysics. A newly designed 1-D stellar evolution module, MESA star, combines many of the numerical and physics modules for simulations of a wide range of stellar evolution scenarios ranging from very-low mass to massive stars, including advanced evolutionary phases. MESA star solves the fully coupled structure and composition equations simultaneously. It uses adaptive mesh refinement and sophisticated timestep controls, and supports shared memory parallelism based on OpenMP. Independently usable modules provide equation of state, opacity, nuclear reaction rates, and atmosphere boundary conditions. Each module is constructed as a separate Fortran 95 library with its own public interface. Examples include comparisons to other codes and show evolutionary tracks of very low mass stars, brown dwarfs, and gas giant planets; the complete evolution of a 1 Msun star from the pre-main sequence to a cooling white dwarf; the Solar sound speed profile; the evolution of intermediate mass stars through the thermal pulses on the He-shell burning AGB phase; the interior structure of slowly pulsating B Stars and Beta Cepheids; evolutionary tracks of massive stars from the pre-main sequence to the onset of core collapse; stars undergoing Roche lobe overflow; and accretion onto a neutron star.

[ascl:1709.003]
MeshLab: 3D triangular meshes processing and editing

MeshLab processes and edits 3D triangular meshes. It includes tools for editing, cleaning, healing, inspecting, rendering, texturing and converting meshes, and offers features for processing raw data produced by 3D digitization tools and devices and for preparing models for 3D printing.

[ascl:1612.012]
Meso-NH: Non-hydrostatic mesoscale atmospheric model

Meso-NH is the non-hydrostatic mesoscale atmospheric model of the French research community jointly developed by the Laboratoire d'Aérologie (UMR 5560 UPS/CNRS) and by CNRM (UMR 3589 CNRS/Météo-France). Meso-NH incorporates a non-hydrostatic system of equations for dealing with scales ranging from large (synoptic) to small (large eddy) scales while calculating budgets and has a complete set of physical parameterizations for the representation of clouds and precipitation. It is coupled to the surface model SURFEX for representation of surface atmosphere interactions by considering different surface types (vegetation, city, ocean, lake) and allows a multi-scale approach through a grid-nesting technique. Meso-NH is versatile, vectorized, parallelized, and operates in 1D, 2D or 3D; it is coupled with a chemistry module (including gas-phase, aerosol, and aqua-phase components) and a lightning module, and has observation operators that compare model output directly with satellite observations, radar, lidar and GPS.

[ascl:1111.009]
MESS: Multi-purpose Exoplanet Simulation System

Bonavita, M.; Chauvin, G.; Desidera, S.; Gratton, R.; Janson, M.; Beuzit, J. L.; Kasper, M.; Mordasini, C.

MESS is a Monte Carlo simulation IDL code which uses either the results of the statistical analysis of the properties of discovered planets, or the results of the planet formation theories, to build synthetic planet populations fully described in terms of frequency, orbital elements and physical properties. They can then be used to either test the consistency of their properties with the observed population of planets given different detection techniques or to actually predict the expected number of planets for future surveys. It can be used to probe the physical and orbital properties of a putative companion within the circumstellar disk of a given star and to test constrain the orbital distribution properties of a potential planet population around the members of the TW Hydrae association. Finally, using in its predictive mode, the synergy of future space and ground-based telescopes instrumentation has been investigated to identify the mass-period parameter space that will be probed in future surveys for giant and rocky planets.

[ascl:1205.010]
Meudon PDR: Atomic & molecular structure of interstellar clouds

The Meudon PDR code computes the atomic and molecular structure of interstellar clouds. It can be used to study the physics and chemistry of diffuse clouds, photodissociation regions (PDRs), dark clouds, or circumstellar regions. The model computes the thermal balance of a stationary plane-parallel slab of gas and dust illuminated by a radiation field and takes into account heating processes such as the photoelectric effect on dust, chemistry, cosmic rays, etc. and cooling resulting from infrared and millimeter emission of the abundant species. Chemistry is solved for any number of species and reactions. Once abundances of atoms and molecules and level excitation of the most important species have been computed at each point, line intensities and column densities can be deduced.

[ascl:1907.031]
MGB: Interactive spectral classification code

MGB (Marxist Ghost Buster) attacks spectral classification by using an interactive comparison with spectral libraries. It allows the user to move along the two traditional dimensions of spectral classification (spectral subtype and luminosity classification) plus the two additional ones of rotation index and spectral peculiarities. Double-lined spectroscopic binaries can also be fitted using a combination of two standards. The code includes OB2500 v2.0, a standard grid of blue-violet *R* ~ 2500 spectra of O stars from the Galactic O-Star Spectroscopic Survey, but other grids can be added to MGB.

[ascl:1106.013]
MGCAMB: Modification of Growth with CAMB

CAMB is a public Fortran 90 code written by Antony Lewis and Anthony Challinor for evaluating cosmological observables. MGCAMB is a modified version of CAMB in which the linearized Einstein equations of General Relativity (GR) are modified. MGCAMB can also be used in CosmoMC to fit different modified-gravity (MG) models to data.

[ascl:1403.017]
MGE_FIT_SECTORS: Multi-Gaussian Expansion fits to galaxy images

MGE_FIT_SECTORS performs Multi-Gaussian Expansion (MGE) fits to galaxy images. The MGE parameterizations are useful in the construction of realistic dynamical models of galaxies, PSF deconvolution of images, the correction and estimation of dust absorption effects, and galaxy photometry. The algorithm is well suited for use with multiple-resolution images (e.g. Hubble Space Telescope (HST) and ground-based images).

[ascl:1010.081]
MGGPOD: A Monte Carlo Suite for Gamma-Ray Astronomy

We have developed MGGPOD, a user-friendly suite of Monte Carlo codes built around the widely used GEANT (Version 3.21) package. The MGGPOD Monte Carlo suite and documentation are publicly available for download. MGGPOD is an ideal tool for supporting the various stages of gamma-ray astronomy missions, ranging from the design, development, and performance prediction through calibration and response generation to data reduction. In particular, MGGPOD is capable of simulating ab initio the physical processes relevant for the production of instrumental backgrounds. These include the build-up and delayed decay of radioactive isotopes as well as the prompt de-excitation of excited nuclei, both of which give rise to a plethora of instrumental gamma-ray background lines in addition to continuum backgrounds.

[ascl:1402.035]
MGHalofit: Modified Gravity extension of Halofit

MGHalofit is a modified gravity extension of the fitting formula for the matter power spectrum of HALOFIT and its improvement by Takahashi et al. MGHalofit is implemented in MGCAMB, which is based on CAMB. MGHalofit calculates the nonlinear matter power spectrum P(k) for the Hu-Sawicki model. Comparing MGHalofit predictions at various redshifts (z<=1) to the f(R) simulations, the accuracy on P(k) is 6% at k<1 h/Mpc and 12% at 1<k<10 h/Mpc respectively.

[ascl:1511.007]
MHF: MLAPM Halo Finder

MHF is a Dark Matter halo finder that is based on the refinement grids of MLAPM. The grid structure of MLAPM adaptively refines around high-density regions with an automated refinement algorithm, thus naturally "surrounding" the Dark Matter halos, as they are simply manifestations of over-densities within (and exterior) to the underlying host halo. Using this grid structure, MHF restructures the hierarchy of nested isolated MLAPM grids into a "grid tree". The densest cell in the end of a tree branch marks center of a prospective Dark Matter halo. All gravitationally bound particles about this center are collected to obtain the final halo catalog. MHF automatically finds halos within halos within halos.

[ascl:1205.003]
MIA+EWS: MIDI data reduction tool

MIA+EWS is a package of two data reduction tools for MIDI data which uses power-spectrum analysis or the information contained in the spectrally-dispersed fringe measurements in order to estimate the correlated flux and the visibility as function of wavelength in the N-band. MIA, which stands for MIDI Interactive Analysis, uses a Fast Fourier Transformation to calculate the Fourier amplitudes of the fringe packets to calculate the correlated flux and visibility. EWS stands for Expert Work-Station, which is a collection of IDL tools to apply coherent visibility analysis to reduce MIDI data. The EWS package allows the user to control and examine almost every aspect of MIDI data and its reduction. The usual data products are the correlated fluxes, total fluxes and differential phase.

[ascl:2005.002]
michi2: SED and SLED fitting tool

michi2 fits combinations of arbitrary numbers of libraries/components to a given observational data. Written in C++ and Python, this chi-square fitting tool can fit a galaxy's spectral energy distribution (SED) with stellar, active galactic nuclear, dust and radio SED templates, and fit a galaxy's spectral line energy distribution (SLED) with one or more gas components using radiative transfer LVG model grid libraries.

michi2 first samples the high-dimensional parameter space (N1*N2*N3*..., where N is the number of independent templates in each library, and 1/2/3 is the ID of components) in an optimized way for a few thousand or tens of thousand times to compute the chi-square to the input observational data, then uses Python scripts to analyze the chi-square distribution and derive the best-fit, median, lower and higher 1-sigma values for each parameter in each library/component. This tool is useful for fitting larger number of templates and arbitrary combinations of libraries/components, including some constraining of one library/component onto another.

[ascl:1011.017]
Microccult: Occultation and Microlensing

Occultation and microlensing are different limits of the same phenomena of one body passing in front of another body. We derive a general exact analytic expression which describes both microlensing and occultation in the case of spherical bodies with a source of uniform brightness and a non-relativistic foreground body. We also compute numerically the case of a source with quadratic limb-darkening. In the limit that the gravitational deflection angle is comparable to the angular size of the foreground body, both microlensing and occultation occur as the objects align. Such events may be used to constrain the size ratio of the lens and source stars, the limb-darkening coefficients of the source star, and the surface gravity of the lens star (if the lens and source distances are known). Application of these results to microlensing during transits in binaries and giant-star microlensing are discussed. These results unify the microlensing and occultation limits and should be useful for rapid model fitting of microlensing, eclipse, and "microccultation" events.

[ascl:1303.007]
micrOMEGAs: Calculation of dark matter properties

micrOMEGAs calculates the properties of cold dark matter in a generic model of particle physics. First developed to compute the relic density of dark matter, the code also computes the rates for dark matter direct and indirect detection. The code provides the mass spectrum, cross-sections, relic density and exotic fluxes of gamma rays, positrons and antiprotons. The propagation of charged particles in the Galactic halo is handled with a module that allows to easily modify the propagation parameters. The cross-sections for both spin dependent and spin independent interactions of WIMPS on protons are computed automatically as well as the rates for WIMP scattering on nuclei in a large detector. Annihilation cross-sections of the dark matter candidate at zero velocity, relevant for indirect detection of dark matter, are computed automatically, and the propagation of charged particles in the Galactic halo is also handled.

[ascl:1010.008]
midIR_sensitivity: Mid-infrared astronomy with METIS

Kendrew, Sarah; Jolissaint, Laurent; Brandl, Bernhard; Lenzen, Rainer; Pantin, Eric; Glasse, Alistair; Blommaert, Joris; Venema, Lars; Siebenmorgen, Ralf; Molster, Frank

midIR_sensitivity is IDL code that calculates the sensitivity of a ground-based mid-infrared instrument for astronomy. The code was written for the Phase A study of the instrument METIS (http://www.strw.leidenuniv.nl/metis), the Mid-Infrared E-ELT Imager and Spectrograph, for the 42-m European Extremely Large Telescope. The model uses a detailed set of input parameters for site characteristics and atmospheric profiles, optical design, and thermal background. The code and all input parameters are highly tailored for the particular design parameters of the E-ELT and METIS, however, the program is structured in such a way that the parameters can easily be adjusted for a different system, or alternative input files used.

[ascl:1807.016]
MIDLL: Markwardt IDL Library

The Markwardt IDL Library contains routines for curve fitting and function minimization, including MPFIT (ascl:1208.019), statistical tests, and non-linear optimization (TNMIN); graphics programs including plotting three-dimensional data as a cube and fixed- or variable-width histograms; adaptive numerical integration (Quadpack), Chebyshev approximation and interpolation, and other mathematical tools; many ephemeris and timing routines; and array and set operations, such as computing the fast product of a large array, efficiently inserting or deleting elements in an array, and performing set operations on numbers and strings; and many other useful and varied routines.

[ascl:1810.019]
MIEX: Mie scattering code for large grains

Miex calculates Mie scattering coefficients and efficiency factors for broad grain size distributions and a very wide wavelength range (λ ≈ 10-10-10-2m) of the interacting radiation and incorporates standard solutions of the scattering amplitude functions. The code handles arbitrary size parameters, and single scattering by particle ensembles is calculated by proper averaging of the respective parameters.

[ascl:1511.012]
milkywayproject_triggering: Correlation functions for two catalog datasets

This triggering code calculates the correlation function between two astrophysical data catalogs using the Landy-Szalay approximator generalized for heterogeneous datasets (Landy & Szalay, 1993; Bradshaw et al, 2011) or the auto-correlation function of one dataset. It assumes that one catalog has positional information as well as an object size (effective radius), and the other only positional information.

[ascl:1811.010]
MillCgs: Searching for Compact Groups in the Millennium Simulation

MillCgs clusters galaxies from the semi-analytic models run on top of the Millennium Simulation to identify Compact Groups. MillCgs uses a machine learning clustering algorithm to find the groups and then runs analytics to filter out the groups that do not fit the user specified criteria. The package downloads the data, processes it, and then creates graphs of the data.

[submitted]
millennium-tap-query: A Python Tool to Query the Millennium Simulation UWS/TAP client

millennium-tap-query is a simple wrapper for the Python package requests to deal with connections to the Millennium TAP Web Client. With this tool you can perform basic or advanced queries to the Millennium Simulation database and download the data products. millennium-tap-query is similar to the TAP query tool in the German Astrophysical Virtual Observatory (GAVO) VOtables package.

[ascl:0101.001]
MILLISEARCH: A Search for Millilensing in BATSE GRB Data

The millisearch.for code was used to generate a new search for the gravitational lens effects of a significant cosmological density of supermassive compact objects (SCOs) on gamma-ray bursts. No signal attributable to millilensing was found. We inspected the timing data of 774 BATSE-triggered GRBs for evidence of millilensing: repeated peaks similar in light-curve shape and spectra. Our null detection leads us to conclude that, in all candidate universes simulated, Omega_{SCO} < 0.1 is favored for 10^{5} < M_{SCO}/M_{odot} < 10^{9}, while in some universes and mass ranges the density limits are as much as 10 times lower. Therefore, a cosmologically significant population of SCOs near globular cluster mass neither came out of the primordial universe, nor condensed at recombination.

[ascl:1911.023]
miluphcuda: Smooth particle hydrodynamics code

Schaefer, Christoph M.; Riecker, Sven; Wandel, Oliver; Maindl, Thomas I.; Scherrer, Samuel; Werner, Janka; Burger, Christoph; Morlock, Marius

miluphcuda is the CUDA port of the original miluph code; it runs on single Nvidia GPUs with compute capability 5.0 and higher and provides fast and efficient computation. The code can be used for hydrodynamical simulations and collision and impact physics, and features self-gravity via Barnes-Hut trees and porosity models such as P-alpha and epsilon-alpha. It can model solid bodies, including ductile and brittle materials, as well as non-viscous fluids, granular media, and porous continua.

[ascl:2001.001]
Min-CaLM: Mineral compositional analysis on debris disk spectra

Min-CaLM performs automated mineral compositional analysis on debris disk spectra. The user inputs the debris disk spectrum, and using Min-CaLM's built-in mineralogical library, Min-CaLM calculates the relative mineral abundances within the disk. To do this calculation, Min-CaLM converts the debris disk spectrum and the mineralogical library spectra into a system of linear equations, which it then solves using non-negative least square minimization. This code comes with a GitHub tutorial on how to use the Min-CaLM package.

[ascl:1302.006]
Minerva: Cylindrical coordinate extension for Athena

Minerva is a cylindrical coordinate extension of the Athena astrophysical MHD code of Stone, Gardiner, Teuben, and Hawley. The extension follows the approach of Athena's original developers and has been designed to alter the existing Cartesian-coordinates code as minimally and transparently as possible. The numerical equations in cylindrical coordinates are formulated to maintain consistency with constrained transport (CT), a central feature of the Athena algorithm, while making use of previously implemented code modules such as the Riemann solvers. Angular momentum transport, which is critical in astrophysical disk systems dominated by rotation, is treated carefully.

[submitted]
MiraPy: Python package for Deep Learning in Astronomy

MiraPy is a Python package for problem-solving in astronomy using Deep Learning for astrophysicist, researchers and students. Current applications of MiraPy are X-Ray Binary classification, ATLAS variable star feature classification, OGLE variable star light-curve classification, HTRU1 dataset classification and Astronomical image reconstruction using encoder-decoder network. It also contains modules for loading various datasets, curve-fitting, visualization and other utilities. It is built using Keras for developing ML models to run on CPU and GPU seamlessly.

[ascl:1106.007]
MIRIAD: Multi-channel Image Reconstruction, Image Analysis, and Display

MIRIAD is a radio interferometry data-reduction package, designed for taking raw visibility data through calibration to the image analysis stage. It has been designed to handle any interferometric array, with working examples for BIMA, CARMA, SMA, WSRT, and ATCA. A separate version for ATCA is available, which differs in a few minor ways from the CARMA version.

[ascl:1110.025]
MIS: A Miriad Interferometry Singledish Toolkit

MIS is a pipeline toolkit using the package MIRIAD to combine Interferometric and Single Dish data. This was prompted by our observations made with the Combined Array For Research in Millimeter-wave Astronomy (CARMA) interferometer of the star-forming region NGC 1333, a large survey highlighting the new 23-element and singledish observing modes. The project consists of 20 CARMA datasets each containing interferometric as well as simultaneously obtained single dish data, for 3 molecular spectral lines and continuum, in 527 different pointings, covering an area of about 8 by 11 arcminutes. A small group of collaborators then shared this toolkit and their parameters via CVS, and scripts were developed to ensure uniform data reduction across the group. The pipeline was run end-to-end each night that new observations were obtained, producing maps that contained all the data to date. This approach could serve as a model for repeated calibration and mapping of large mixed-mode correlation datasets from ALMA.

[ascl:1010.062]
MissFITS: Basic Maintenance and Packaging Tasks on FITS Files

MissFITS is a program that performs basic maintenance and packaging tasks on FITS files using an optimized FITS library. MissFITS can:

- add, edit, and remove FITS header keywords;
- split and join Multi-Extension-FITS (MEF) files;
- unpile and pile FITS data-cubes; and,
- create, check, and update FITS checksums, using R. Seaman’s protocol.

[ascl:1505.011]
missForest: Nonparametric missing value imputation using random forest

missForest imputes missing values particularly in the case of mixed-type data. It uses a random forest trained on the observed values of a data matrix to predict the missing values. It can be used to impute continuous and/or categorical data including complex interactions and non-linear relations. It yields an out-of-bag (OOB) imputation error estimate without the need of a test set or elaborate cross-validation and can be run in parallel to save computation time. missForest has been used to, among other things, impute variable star colors in an All-Sky Automated Survey (ASAS) dataset of variable stars with no NOMAD match.

[ascl:1910.016]
MiSTree: Construct and analyze Minimum Spanning Tree graphs

MiSTree quickly constructs minimum spanning tree graphs for various coordinate systems, including Celestial coordinates, by using a k-nearest neighbor graph (k NN, rather than a matrix of pairwise distances) which is then fed to Kruskal's algorithm to create the graph. MiSTree bins the MST statistics into histograms and plots the distributions; enabling the inclusion of high-order statistics information from the cosmic web to provide additional information that improves cosmological parameter constraints. Though MiSTree was designed for use in cosmology, it can be used in any field requiring extracting non-Gaussian information from point distributions.

[ascl:1409.001]
mixT: single-temperature fit for a multi-component thermal plasma

mixT accurately predicts T derived from a single-temperature fit for a multi-component thermal plasma. It can be applied in the deprojection analysis of objects with the temperature and metallicity gradients, for correction of the PSF effects, for consistent comparison of numerical simulations of galaxy clusters and groups with the X-ray observations, and for estimating how emission from undetected components can bias the global X-ray spectral analysis.

[ascl:1206.010]
mkj_libs: Helper routines for plane-fitting & analysis tools

mkj_libs provides a set of helper routines (vector operations, astrometry, statistical analysis of spherical data) for the main plane-fitting and analysis tools.

[ascl:0104.001]
MLAPM: Simulating Structure Formation from Collisionless Matter

MLAPM simulates structure formation from collisionless matter. The code, written in C, is purely grid-based and uses a recursively refined Cartesian grid to solve Poisson's equation for the potential, rather than obtaining the potential from a Green's function. Refinements can have arbitrary shapes and in practice closely follow the complex morphology of the density field that evolves. The timestep shortens by a factor two with each successive refinement. It is argued that an appropriate choice of softening length is of great importance and that the softening should be at all points an appropriate multiple of the local inter-particle separation. Unlike tree and P3M codes, multigrid codes automatically satisfy this requirement.

[ascl:1403.003]
MLZ: Machine Learning for photo-Z

The parallel Python framework MLZ (Machine Learning and photo-Z) computes fast and robust photometric redshift PDFs using Machine Learning algorithms. It uses a supervised technique with prediction trees and random forest through TPZ that can be used for a regression or a classification problem, or a unsupervised methods with self organizing maps and random atlas called SOMz. These machine learning implementations can be efficiently combined into a more powerful one resulting in robust and accurate probability distributions for photometric redshifts.

[ascl:1412.010]
MMAS: Make Me A Star

Make Me A Star (MMAS) quickly generates stellar collision remnants and can be used in combination with realistic dynamical simulations of star clusters that include stellar collisions. The code approximates the merger process (including shock heating, hydrodynamic mixing, mass ejection, and angular momentum transfer) with simple algorithms based on conservation laws and a basic qualitative understanding of the hydrodynamics. These simple models agree very well with those from SPH (smoothed particle hydrodynamics) calculations of stellar collisions, and the subsequent stellar evolution of these models also matches closely that of the more accurate hydrodynamic models.

[ascl:1905.005]
MMIRS-DRP: MMIRS Data Reduction Pipeline

The MMIRS data reduction pipeline provides complete and flexible data reduction for long-slit and multi-slit spectroscopic observations collected using the MMT and Magellan Infrared Spectrograph (MMIRS). Written in IDL, it offers sky subtraction, correction for telluric absorpition, and is fast enough to permit real-time data reduction for quality control.

[ascl:1110.010]
MOCASSIN: MOnte CArlo SimulationS of Ionized Nebulae

MOCASSIN is a fully 3D or 2D photoionisation and dust radiative transfer code which employs a Monte Carlo approach to the transfer of radiation through media of arbitrary geometry and density distribution. Written in Fortran, it was originally developed for the modelling of photoionised regions like HII regions and planetary nebulae and has since expanded and been applied to a variety of astrophysical problems, including modelling clumpy dusty supernova envelopes, star forming galaxies, protoplanetary disks and inner shell fluorence emission in the photospheres of stars and disk atmospheres. The code can deal with arbitrary Cartesian grids of variable resolution, it has successfully been used to model complex density fields from SPH calculations and can deal with ionising radiation extending from Lyman edge to the X-ray. The dust and gas microphysics is fully coupled both in the radiation transfer and in the thermal balance.

[ascl:1010.009]
ModeCode: Bayesian Parameter Estimation for Inflation

ModeCode is a publicly available code that computes the primordial scalar and tensor power spectra for single field inflationary models. ModeCode solves the inflationary mode equations numerically, avoiding the slow roll approximation. It provides an efficient and robust numerical evaluation of the inflationary perturbation spectrum, and allows the free parameters in the inflationary potential to be estimated within an MCMC computation. ModeCode also allows the estimation of reheating uncertainties once a potential has been specified. It is interfaced with CAMB and CosmoMC to compute cosmic microwave background angular power spectra and perform likelihood analysis and parameter estimation. It can be run as a standalone code as well. Errors in the results from ModeCode contribute negligibly to the error budget for analyses of data from Planck or other next generation experiments.

[ascl:1109.023]
MOKA: A New Tool for Strong Lensing Studies

MOKA simulates the gravitational lensing signal from cluster-sized haloes. This algorithm implements recent results from numerical simulations to create realistic lenses with properties independent of numerical resolution and can be used for studies of the strong lensing cross section in dependence of halo structure.

[ascl:1501.013]
Molecfit: Telluric absorption correction tool

Smette, A.; Kausch, W; Sana, H; Noll, S.; Horst, H.; Kimeswenger, S.; Barden, M; Szyszka, C.; Jones, A. M.; Gallene, A.; Vinther, J.; Ballester, P.; Kerber, F.

Molecfit corrects astronomical observations for atmospheric absorption features based on fitting synthetic transmission spectra to the astronomical data, which saves a significant amount of valuable telescope time and increases the instrumental efficiency. Molecfit can also estimate molecular abundances, especially the water vapor content of the Earth’s atmosphere. The tool can be run from a command-line or more conveniently through a GUI.

[ascl:1212.004]
MOLIERE-5: Forward and inversion model for sub-mm wavelengths

MOLIERE-5 (Microwave Observation LIne Estimation and REtrieval) is a versatile forward and inversion model for the millimeter and submillimeter wavelengths range and includes an inversion model. The MOLIERE-5 forward model includes modules for the calculation of absorption coefficients, radiative transfer, and instrumental characteristics. The radiative transfer model is supplemented by a sensitivity module for estimating the contribution to the spectrum of each catalog line at its center frequency enabling the model to effectively filter for small spectral lines. The instrument model consists of several independent modules, including the calculation of the convolution of spectra and weighting functions with the spectrometer response functions. The instrument module also provides several options for modeling of frequency-switched observations. The MOLIERE-5 inversion model calculates linear Optimal Estimation, a least-squares retrieval method which uses statistical apriori knowledge on the retrieved parameters for the regularization of ill-posed inversion problems and computes diagnostics such as the measurement and smoothing error covariance matrices along with contribution and averaging kernel functions.

[ascl:1907.012]
molly: 1D astronomical spectra analyzer

molly analyzes 1D astronomical spectra. Its prime purpose is for handling large numbers of similar spectra (*e.g.,* time series spectroscopy), but it contains many of the standard operations used for normal spectrum analysis as well. It overlaps with the various similar programs such as dipso (ascl:1405.016) and has strengths (particularly for time series spectra) and weaknesses compared to them.

[ascl:1206.004]
MOLSCAT: MOLecular SCATtering

MOLSCAT is a FORTRAN code for quantum mechanical (coupled channel) solution of the nonreactive molecular scattering problem and was developed to obtain collision rates for molecules in the interstellar gas which are needed to understand microwave and infrared astronomical observations. The code is implemented for various types of collision partners. In addition to the essentially exact close coupling method several approximate methods, including the Coupled States and Infinite Order Sudden approximations, are provided.

[ascl:1908.002]
Molsoft: Molonglo Telescope Observing Software

Molsoft operates, monitors and schedules observations, both through predetermined schedule files and fully dynamically, at the refurbished Molonglo Observatory Synthesis Radio Telescope (MOST). It was developed as part of the UTMOST upgrade of the facility. The software runs a large-scale pulsar timing program; the autonomous observing system and the dynamic scheduler have increased the observing efficiency by a factor of 2-3 in comparison with static scheduling.

[ascl:1010.036]
Montage: An Astronomical Image Mosaicking Toolkit

Jacob, Joseph C.; Katz, Daniel S.; Berriman, G. Bruce; Good, John; Laity, Anastasia C.; Deelman, Ewa; Kesselman, Carl; Singh, Gurmeet; Su, Mei-Hui; Prince, Thomas A.; Williams, Roy

Montage is an open source code toolkit for assembling Flexible Image Transport System (FITS) images into custom mosaics. It runs on all common Linux/Unix platforms, on desktops, clusters and computational grids, and supports all World Coordinate System (WCS) projections and common coordinate systems. Montage preserves spatial and calibration fidelity of input images, processes 40 million pixels in up to 32 minutes on 128 nodes on a Linux cluster, and provides independent engines for analyzing the geometry of images on the sky, re-projecting images, rectifying background emission to a common level, and co-adding images. It offers convenient tools for managing and manipulating large image files.

[ascl:1502.006]
Montblanc: GPU accelerated Radio Interferometer Measurement Equations in support of Bayesian Inference for Radio Observations

Montblanc, written in Python, is a GPU implementation of the Radio interferometer measurement equation (RIME) in support of the Bayesian inference for radio observations (BIRO) technique. The parameter space that BIRO explores results in tens of thousands of computationally expensive RIME evaluations before reduction to a single *X ^{2}* value. The RIME is calculated over four dimensions, time, baseline, channel and source and the values in this 4D space can be independently calculated; therefore, the RIME is particularly amenable to a parallel implementation accelerated by Graphics Programming Units (GPUs). Montblanc is implemented for NVIDIA's CUDA architecture and outperforms MeqTrees (ascl:1209.010) and OSKAR.

[ascl:1307.002]
Monte Python: Monte Carlo code for CLASS in Python

Monte Python is a parameter inference code which combines the flexibility of the python language and the robustness of the cosmological code CLASS into a simple and easy to manipulate Monte Carlo Markov Chain code.

This version has been archived and replaced by MontePython 3 (ascl:1805.027).

[ascl:1805.027]
MontePython 3: Parameter inference code for cosmology

MontePython 3 provides numerous ways to explore parameter space using Monte Carlo Markov Chain (MCMC) sampling, including Metropolis-Hastings, Nested Sampling, Cosmo Hammer, and a Fisher sampling method. This improved version of the Monte Python (ascl:1307.002) parameter inference code for cosmology offers new ingredients that improve the performance of Metropolis-Hastings sampling, speeding up convergence and offering significant time improvement in difficult runs. Additional likelihoods and plotting options are available, as are post-processing algorithms such as Importance Sampling and Adding Derived Parameter.

[ascl:1202.009]
MOOG: LTE line analysis and spectrum synthesis

MOOG performs a variety of LTE line analysis and spectrum synthesis tasks. The typical use of MOOG is to assist in the determination of the chemical composition of a star. The basic equations of LTE stellar line analysis are followed. The coding is in various subroutines that are called from a few driver routines; these routines are written in standard FORTRAN. The standard MOOG version has been developed on unix, linux and macintosh computers.

One of the chief assets of MOOG is its ability to do on-line graphics. The plotting commands are given within the FORTRAN code. MOOG uses the graphics package SM, chosen for its ease of implementation in FORTRAN codes. Plotting calls are concentrated in just a few routines, and it should be possible for users of other graphics packages to substitute other appropriate FORTRAN commands.

[ascl:1308.018]
MoogStokes: Zeeman polarized radiative transfer

MOOGStokes is a version of the MOOG one-dimensional local thermodynamic equilibrium radiative transfer code that incorporates a Stokes vector treatment of polarized radiation through a magnetic medium. It consists of three complementary programs that together can synthesize the disk-averaged emergent spectrum of a star with a magnetic field. The MOOGStokes package synthesizes emergent spectra of stars with magnetic fields in a familiar computational framework and produces disk-averaged spectra for all Stokes vectors ( I, Q, U, V ), normalized by the continuum.

[ascl:1111.006]
MOPEX: MOsaicker and Point source EXtractor

MOPEX (MOsaicker and Point source EXtractor) is a package for reducing and analyzing imaging data, as well as MIPS SED data. MOPEX includes the point source extraction package, APEX.

MOPEX is designed to allow the user to:

- perform sophisticated background matching of individual data frames
- mosaic the individual frames downloaded from the Spitzer archive
- perform both temporal and spatial outlier rejection during mosaicking
- apply offline pointing refinement for MIPS data (refinement is already applied to IRAC data)
- perform source detection on the mosaics using APEX
- compute aperture photometry or PRF-fitting photometry for point sources
- perform interpolation, coaddition, and spectrum extraction of MIPS SED images.

[ascl:1303.011]
MOPSIC: Extended Version of MOPSI

MOPSIC was created to analyze bolometer data but can be used for much more versatile tasks. It is an extension of MOPSI; this software had been merged with the command interpreter of GILDAS. For data reduction, MOPSIC uses a special method to calculate the chopped signal. This gives much better results than the straight difference of the signals obtained at both chopper positions. In addition there are also scripts to reduce pointings, skydips, and to calculate the RCPs (Receiver Channel Parameters) from calibration maps. MOPSIC offers a much broader range of applications including advanced planning functions for mapping and onoff observations, post-reduction data analysis and processing and even reduction of non-bolometer data (optical, IR, spectroscopy).

[ascl:1911.014]
MORDI: Massively-Overlapped Ring-Diagram Inversion

MORDI (Massively-Overlapped Ring-Diagram Inversion) performs three-dimensional ring-diagram inversions. The code reads in frequency shift measurements and their associated sensitivity kernels and outputs two-dimensional slices of the subsurface flow field at a constant depth and (optionally) the associated averaging kernels. It relies on both distributed-memory (MPI) and shared-memory (OpenMP) parallelism to scale efficiently up to a few thousand processors, but can also run reasonably well on small machines (1-4 cpus). The actions of the code are modified by command-line parameters, which enable a significant amount of flexibility when setting up an inversion.

[ascl:1906.013]
MORPHEUS: A 3D Eulerian Godunov MPI-OpenMP hydrodynamics code with multiple grid geometries

MORPHEUS (Manchester Omni-geometRical Program for Hydrodynamical EUlerian Simulations) is a 3D hydrodynamical code used to simulate astrophysical fluid flows. It has three different grid geometries (cartesian, spherical, and cylindrical) and uses a second-order Godunov method to solve the equations of hydrodynamics. Physical modules also include radiative cooling and gravity, and a hybrid MPI-OpenMP parallelization allows computations to be run on large-scale architectures. MORPHEUS is written in Fortran90 and does not require any libraries (apart from MPI) to run.

[ascl:1906.012]
Morpheus: Library to generate morphological semantic segmentation maps of astronomical images

Morpheus generates pixel level morphological classifications of astronomical sources by leveraging advances in deep learning to perform source detection, source segmentation, and morphological classification pixel-by-pixel via a semantic segmentation algorithm adopted from the field of computer vision. By utilizing morphological information about the flux of real astronomical sources during object detection, Morpheus shows resiliency to false positive identifications of sources.

[ascl:1908.007]
MosfireDRP: MOSFIRE Data Reduction Pipeline

MosfireDRP reduces data from the MOSFIRE spectrograph of the Keck Observatory; it produces flat-fielded, wavelength calibrated, rectified, and stacked 2D spectrograms for each slit on a given mask in nearly real time. Background subtraction is performed in two states: a simple pairwise subtraction of interleaved stacks, and then fitting a 2D b-spline model to the background residuals.

[ascl:1710.006]
MOSFiT: Modular Open-Source Fitter for Transients

Guillochon, James; Nicholl, Matt; Villar, V. Ashley; Mockler, Brenna; Narayan, Gautham; Mandel, Kaisey S.; Berger, Edo; Williams, Peter K. G.

MOSFiT (Modular Open-Source Fitter for Transients) downloads transient datasets from open online catalogs (e.g., the Open Supernova Catalog), generates Monte Carlo ensembles of semi-analytical light curve fits to those datasets and their associated Bayesian parameter posteriors, and optionally delivers the fitting results back to those same catalogs to make them available to the rest of the community. MOSFiT helps bridge the gap between observations and theory in time-domain astronomy; in addition to making the application of existing models and creation of new models as simple as possible, MOSFiT yields statistically robust predictions for transient characteristics, with a standard output format that includes all the setup information necessary to reproduce a given result.

[ascl:1611.003]
MPDAF: MUSE Python Data Analysis Framework

MPDAF, the MUSE Python Data Analysis Framework, provides tools to work with MUSE-specific data (for example, raw data and pixel tables), and with more general data such as spectra, images, and data cubes. Originally written to work with MUSE data, it can also be used for other data, such as that from the Hubble Space Telescope. MPDAF also provides MUSELET, a SExtractor-based tool to detect emission lines in a data cube, and a format to gather all the information on a source in one FITS file. MPDAF was developed and is maintained by CRAL (Centre de Recherche Astrophysique de Lyon).

[ascl:1208.019]
MPFIT: Robust non-linear least squares curve fitting

These IDL routines provide a robust and relatively fast way to perform least-squares curve and surface fitting. The algorithms are translated from MINPACK-1, which is a rugged minimization routine found on Netlib, and distributed with permission. This algorithm is more desirable than CURVEFIT because it is generally more stable and less likely to crash than the brute-force approach taken by CURVEFIT, which is based upon Numerical Recipes.

[ascl:1304.014]
MPgrafic: A parallel MPI version of Grafic-1

MPgrafic is a parallel MPI version of Grafic-1 which can produce large cosmological initial conditions on a cluster without requiring shared memory. The real Fourier transforms are carried in place using fftw while minimizing the amount of used memory (at the expense of performance) in the spirit of Grafic-1. The writing of the output file is also carried in parallel. In addition to the technical parallelization, it provides three extensions over Grafic-1:

- it can produce power spectra with baryon wiggles (DJ Eisenstein and W. Hu, Ap. J. 496);
- it has the optional ability to load a lower resolution noise map corresponding to the low frequency component which will fix the larger scale modes of the simulation (extra flag 0/1 at the end of the input process) in the spirit of Grafic-2;
- it can be used in conjunction with constrfield, which generates initial conditions phases from a list of local constraints on density, tidal field density gradient and velocity.

[ascl:1712.002]
MPI_XSTAR: MPI-based parallelization of XSTAR program

MPI_XSTAR parallelizes execution of multiple XSTAR runs using Message Passing Interface (MPI). XSTAR (ascl:9910.008), part of the HEASARC's HEAsoft (ascl:1408.004) package, calculates the physical conditions and emission spectra of ionized gases. MPI_XSTAR invokes XSTINITABLE from HEASoft to generate a job list of XSTAR commands for given physical parameters. The job list is used to make directories in ascending order, where each individual XSTAR is spawned on each processor and outputs are saved. HEASoft's XSTAR2TABLE program is invoked upon the contents of each directory in order to produce table model FITS files for spectroscopy analysis tools.

[ascl:1208.014]
MPI-AMRVAC: MPI-Adaptive Mesh Refinement-Versatile Advection Code

van der Holst, Bar; Keppens, Rony; Meliani, Zakaria; Porth, Oliver; van Marle, Allard Jan; Delmont, Peter; Xia, Chun

MPI-AMRVAC is an MPI-parallelized Adaptive Mesh Refinement code, with some heritage (in the solver part) to the Versatile Advection Code or VAC, initiated by Gábor Tóth at the Astronomical Institute at Utrecht in November 1994, with help from Rony Keppens since 1996. Previous incarnations of the Adaptive Mesh Refinement version of VAC were of restricted use only, and have been used for basic research in AMR strategies, or for well-targeted applications. This MPI version uses a full octree block-based approach, and allows for general orthogonal coordinate systems. MPI-AMRVAC aims to advance any system of (primarily hyperbolic) partial differential equations by a number of different numerical schemes. The emphasis is on (near) conservation laws, with shock-dominated problems as a main research target. The actual equations are stored in separate modules, can be added if needed, and they can be selected by a simple configuration of the VACPP preprocessor. The dimensionality of the problem is also set through VACPP. The numerical schemes are able to handle discontinuities and smooth flows as well.

[ascl:1106.022]
MPI-Defrost: Extension of Defrost to MPI-based Cluster Environment

MPI-Defrost extends Frolov’s Defrost to an MPI-based cluster environment. This version has been restricted to a single field. Restoring two-field support should be straightforward, but will require some code changes. Some output options may also not be fully supported under MPI.

This code was produced to support our own work, and has been made available for the benefit of anyone interested in either oscillon simulations or an MPI capable version of Defrost, and it is provided on an "as-is" basis. Andrei Frolov is the primary developer of Defrost and we thank him for placing his work under the GPL (GNU Public License), and thus allowing us to distribute this modified version.

[ascl:2007.008]
MPSolve: Multiprecision Polynomial SOLVEr

MPSolve (Multiprecision Polynomial SOLVEr) provides an easy-to-use universal blackbox for solving polynomials and secular equations. Its features include arbitrary precision approximation and guaranteed inclusion radii for the results. It can exploit polynomial structures, taking advantage of sparsity as well as coefficients in a particular domain (*i.e.*, integers or rationals), and can be specialized for specific classes of polynomials.

[ascl:1212.003]
MPWide: Light-weight communication library for distributed computing

MPWide is a light-weight communication library for distributed computing. It is specifically developed to allow message passing over long-distance networks using path-specific optimizations. An early version of MPWide was used in the Gravitational Billion Body Project to allow simulations across multiple supercomputers.

[ascl:1912.020]
MRExo: Non-parametric mass-radius relationship for exoplanets

MRExo performs non-parametric fitting and analysis of the mass-radius (M-R) relationship for exoplanets. Written in Python, it offers tools for fitting the M-R relationship to a given data set and also includes predicting (M->R, and R->M) and plotting functions.

[ascl:1102.005]
MRLENS: Multi-Resolution methods for gravitational LENSing

The MRLENS package offers a new method for the reconstruction of weak lensing mass maps. It uses the multiscale entropy concept, which is based on wavelets, and the False Discovery Rate which allows us to derive robust detection levels in wavelet space. We show that this new restoration approach outperforms several standard techniques currently used for weak shear mass reconstruction. This method can also be used to separate E and B modes in the shear field, and thus test for the presence of residual systematic effects. We concentrate on large blind cosmic shear surveys, and illustrate our results using simulated shear maps derived from N-Body Lambda-CDM simulations with added noise corresponding to both ground-based and space-based observations.

[ascl:1809.015]
MrMoose: Multi-Resolution Multi-Object/Origin Spectral Energy distribution fitting procedure

MrMoose (Multi-Resolution Multi-Object/Origin Spectral Energy) fits user-defined models onto a set of multi-wavelength data using a Bayesian framework. The code can handle blended sources, large variation in resolution, and even upper limits consistently. It also generates a series of outputs allowing for an quick interpretation of the results. The code uses emcee (ascl:1303.002), and saves the emcee sampler object, thus allowing users to transfer the output to a personal graphical interface.

[ascl:1802.015]
mrpy: Renormalized generalized gamma distribution for HMF and galaxy ensemble properties comparisons

mrpy calculates the MRP parameterization of the Halo Mass Function. It calculates basic statistics of the truncated generalized gamma distribution (TGGD) with the TGGD class, including mean, mode, variance, skewness, pdf, and cdf. It generates MRP quantities with the MRP class, such as differential number counts and cumulative number counts, and offers various methods for generating normalizations. It can generate the MRP-based halo mass function as a function of physical parameters via the mrp_b13 function, and fit MRP parameters to data in the form of arbitrary curves and in the form of a sample of variates with the SimFit class. mrpy also calculates analytic hessians and jacobians at any point, and allows the user to alternate parameterizations of the same form via the reparameterize module.

[ascl:1504.016]
MRrelation: Posterior predictive mass distribution

MRrelation calculates the posterior predictive mass distribution for an individual planet. The probabilistic mass-radius relationship (M-R relation) is evaluated within a Bayesian framework, which both quantifies this intrinsic dispersion and the uncertainties on the M-R relation parameters.

[ascl:1112.010]
MRS3D: 3D Spherical Wavelet Transform on the Sphere

Future cosmological surveys will provide 3D large scale structure maps with large sky coverage, for which a 3D Spherical Fourier-Bessel (SFB) analysis is natural. Wavelets are particularly well-suited to the analysis and denoising of cosmological data, but a spherical 3D isotropic wavelet transform does not currently exist to analyse spherical 3D data. We present a new fast Discrete Spherical Fourier-Bessel Transform (DSFBT) based on both a discrete Bessel Transform and the HEALPIX angular pixelisation scheme. We tested the 3D wavelet transform and as a toy-application, applied a denoising algorithm in wavelet space to the Virgo large box cosmological simulations and found we can successfully remove noise without much loss to the large scale structure. The new spherical 3D isotropic wavelet transform, called MRS3D, is ideally suited to analysing and denoising future 3D spherical cosmological surveys; it uses a novel discrete spherical Fourier-Bessel Transform. MRS3D is based on two packages, IDL and Healpix and can be used only if these two packages have been installed.

[ascl:1709.007]
MSSC: Multi-Source Self-Calibration

Multi-Source Self-Calibration (MSSC) provides direction-dependent calibration to standard phase referencing. The code combines multiple faint sources detected within the primary beam to derive phase corrections. Each source has its CLEAN model divided into the visibilities which results in multiple point sources that are stacked in the uv plane to increase the S/N, thus permitting self-calibration. This process applies only to wide-field VLBI data sets that detect and image multiple sources within one epoch.

Would you like to view a random code?