Results 2001-2100 of 3594 (3502 ASCL, 92 submitted)

[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 (ascl:9910.004) 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 (ascl:1106.008);
- 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 (ascl:1011.012) 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.

[submitted]
MRS: The MOS Reduction Software

The MRS (The MOS Reduction Software) suite reduces the spectra taken with the multi-object spectrograph spectra used as the focal plane instrument of RTT150 telescope in the TÜBİTAK National Observatory.

[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:2009.024]
MSL: Mining for Substructure Lenses

MSL applies simulation-based inference techniques to the problem of substructure inference in galaxy-galaxy strong lenses. It leverages additional information extracted from the simulator, then trains neural networks to estimate likelihood ratios associated with population-level parameters characterizing dark matter substructure. The package including five high-level scripts which run the simulation and create samples, combing multiple simulation runs into a single file to use for training, then train the neural networks. After training, the estimated likelihood ratio is tested, and calibrated network predictions are made based on histograms of the network output.

[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.

[ascl:2102.002]
MST: Minimum Spanning Tree algorithm for identifying large-scale filaments

MST (Minimum Spanning Tree) identifies velocity coherent large-scale filaments through ATLASGAL clumps. It can also isolate filaments embedded in a crowded position–position–velocity (PPV) space. One strength of this method is its repeatability compared to manual approaches.

[ascl:1701.006]
MSWAVEF: Momentum-Space Wavefunctions

MSWAVEF calculates hydrogenic and non-hydrogenic momentum-space electronic wavefunctions. Such wavefunctions are often required to calculate various collision processes, such as excitation and line broadening cross sections. The hydrogenic functions are calculated using the standard analytical expressions. The non-hydrogenic functions are calculated within quantum defect theory according to the method of Hoang Binh and van Regemorter (1997). Required Hankel transforms have been determined analytically for angular momentum quantum numbers ranging from zero to 13 using Mathematica. Calculations for higher angular momentum quantum numbers are possible, but slow (since calculated numerically). The code is written in IDL.

[ascl:2212.005]
MTNeedlet: Spherical maps filtering

MTNeedlet uses needlets to filter spherical (Healpix) maps and detect and analyze the maxima population using a multiple testing approach. It has been developed with the CMB in mind, but it can be applied to other spherical maps. It pivots around three basic steps: 1.) The calculation of several types of needlets and their possible use to filter maps; 2.) The detection of maxima (or minima) on spherical maps, their visualization and basic analysis; and 3.) The multiple testing approach in order to detect anomalies in the maxima population of the maps with respect to the expected behavior for a random Gaussian map. MTNeedlet relies on Healpy (ascl:2008.022) to efficiently deal with spherical maps.

[ascl:1710.011]
mTransport: Two-point-correlation function calculator

mTransport computes the 2-point-correlation function of the curvature and tensor perturbations in multifield models of inflation in the presence of a curved field space. It is a Mathematica implementation of the transport method which encompasses scenarios with violations of slow-roll conditions and turns of the trajectory in field space. It can be used for an arbitrary mass spectrum, including massive modes, particle production and models with quasi-single-field dynamics.

[ascl:1811.012]
muLAn: gravitational MICROlensing Analysis Software

muLAn analyzes and fits light curves of gravitational microlensing events. The code includes all classical microlensing models (for example, single and binary microlenses, ground- and space-based parallax effects, orbital motion, finite-source effects, and limb-darkening); these can be combined into several time intervals of the analyzed light curve. Minimization methods include an Affine-Invariant Ensemble Sampler to generate a multivariate proposal function while running several Markov Chain Monte Carlo (MCMC) chains, for the set of parameters which is chosen to be fit; non-fitting parameters can be either kept fixed or set on a grid defined by the user. Furthermore, the software offers a model-free option to align all data sets together and allow inspection the light curve before any modeling work. It also comes with many useful routines (export publication-quality figures, data formatting and cleaning) and state-of-the-art statistical tools.

Modeling results can be interpreted using an interactive html page which contains all information about the light curve model, caustics, source trajectory, best-fit parameters and chi-square. Parameters uncertainties and statistical properties (such as multi-modal features of the posterior density) can be assessed from correlation plots. The code is modular, allowing the addition of other computation or minimization routines by directly adding their Python files without modifying the main code. The software has been designed to be easy to use even for the newcomer in microlensing, with external, synthetic and self-explanatory setup files containing all important commands and option settings. The user may choose to launch the code through command line instructions, or to import muLAn within another Python project like any standard Python package.

[ascl:1803.006]
MulensModel: Microlensing light curves modeling

MulensModel calculates light curves of microlensing events. Both single and binary lens events are modeled and various higher-order effects can be included: extended source (with limb-darkening), annual microlensing parallax, and satellite microlensing parallax. The code is object-oriented and written in Python3, and requires AstroPy (ascl:1304.002).

[ascl:2102.023]
Multi_CLASS: Cross-tracer angular power spectra of number counts using CLASS

Multi_CLASS modifies the Boltzmann code CLASS (ascl:1106.020) to compute of the cross-tracer angular power spectra of the number count fluctuations for two different tracers of the underlying dark matter density field. In other words, it generalizes the standard nCl output option of CLASS to the case of two different tracers, for example, two different galaxy populations with their own redshift distribution, and galaxy and magnification bias parameters, among others.

Multi_CLASS also includes an implementation of the effect of primordial non-Gaussianities of the local type, parametrized by the parameter f_NL (following the large-scale structure convention), on the effective bias of the tracers. There is also the possibility of having a tilted non-Gaussian correction, parametrized by n_NG, with a pivot scale determined by k_pivot_NG. The package includes galaxy redshift distributions for forthcoming galaxy surveys, with the ease of choosing between them (or an input file) from the parameters input file (*e.g.*, multi_explanatory.ini). In addition, Multi_CLASS includes the possibility of using resolved gravitational wave events as a tracer.

[ascl:1506.004]
multiband_LS: Multiband Lomb-Scargle Periodograms

The multiband periodogram is a general extension of the well-known Lomb-Scargle approach for detecting periodic signals in time-domain data. In addition to advantages of the Lomb-Scargle method such as treatment of non-uniform sampling and heteroscedastic errors, the multiband periodogram significantly improves period finding for randomly sampled multiband light curves (e.g., Pan-STARRS, DES and LSST). The light curves in each band are modeled as arbitrary truncated Fourier series, with the period and phase shared across all bands.

[ascl:1909.002]
MultiColorFits: Colorize and combine multiple fits images for visually aesthetic scientific plots

MultiColorFits is a tool to colorize and combine multiple fits images for making visually aesthetic scientific plots. The standard method to make color composites by combining fits images programmatically in python is to assign three images as separate red, green, and blue channels. This can produce unsatisfactory results for a variety of reasons, such as when less than three images are available, or additional images are desired to be shown. MultiColorFits breaks these limitations by allowing users to apply any color to a given image, not just red, green, or blue. Composites can then be created from an arbitrary number of images. Controls are included for stretching brightness scales with common functions.

[ascl:2207.001]
MULTIGRIS: Multicomponent probabilistic grid search

MULTIGRIS (also called mgris) uses the sequential Monte Carlo method in PyMC (ascl:1506.005) to extract the posterior distributions of primary grid parameters and predict unobserved parameters/observables. The code accepts either a discrete number of components and/or continuous (e.g., power-law, normal) distributions for any given parameter. MULTIGRIS, written in Python, infers the posterior probability functions of parameters in a multidimensional potentially incomplete grid with some observational tracers defined for each parameter set. Observed values and their potentially asymmetric uncertainties are used to calculate a likelihood which, together with predefined or custom priors, produces the posterior distributions. Linear combinations of parameter sets may be used with inferred mixing weights and nearest neighbor or linear interpolation may be used to sample the parameter space.

[ascl:2106.027]
MultiModeCode: Numerical exploration of multifield inflation models

MultiModeCode facilitates efficient Monte Carlo sampling of prior probabilities for inflationary model parameters and initial conditions and efficiently generates large sample-sets for inflation models with O(100) fields. The code numerically solves the equations of motion for the background and first-order perturbations of multi-field inflation models with canonical kinetic terms and arbitrary potentials, providing the adiabatic, isocurvature, and tensor power spectra at the end of inflation. For models with sum-separable potentials MultiModeCode also computes the slow-roll prediction via the δN formalism for easy model exploration and validation.

[ascl:2207.006]
MultiModes: Efficiently analyze pulsating stars

Pamos Ortega, David; García Hernández, Antonio; Suárez, Juan Carlos; Pascual Granado, Javier; Barceló Forteza, Sebastià; Rodón, José Ramón

MultiModes extracts the most significant frequencies of a sample of classical pulsating stars. The code takes a directory with light curves and initial parameters as input. For every light curve, the code calculates the frequencies spectrum, or periodogram, with the Fast Lomb Scargle algorithm, extracts the higher amplitude peak, and evaluates whether it is a real signal or noise. It fits frequency, amplitude, and phase through non-linear optimization, using a multisine function. This function is redefined with the new calculated parameters. MultiModes then does a simultaneous fit of a number of peaks (20 by default), subtracts them from the original signal, and goes back to the beginning of the loop with the residual, repeating the same process until the stop criterion is reached. After that, the code can filter suspicious spurious frequencies, those of low amplitude below the Rayleigh resolution, and possible combined frequencies.

[ascl:1109.006]
MultiNest: Efficient and Robust Bayesian Inference

We present further development and the first public release of our multimodal nested sampling algorithm, called MultiNest. This Bayesian inference tool calculates the evidence, with an associated error estimate, and produces posterior samples from distributions that may contain multiple modes and pronounced (curving) degeneracies in high dimensions. The developments presented here lead to further substantial improvements in sampling efficiency and robustness, as compared to the original algorithm presented in Feroz & Hobson (2008), which itself significantly outperformed existing MCMC techniques in a wide range of astrophysical inference problems. The accuracy and economy of the MultiNest algorithm is demonstrated by application to two toy problems and to a cosmological inference problem focusing on the extension of the vanilla $Lambda$CDM model to include spatial curvature and a varying equation of state for dark energy. The MultiNest software is fully parallelized using MPI and includes an interface to CosmoMC (ascl:1106.025). It will also be released as part of the SuperBayeS package (ascl:1109.007) for the analysis of supersymmetric theories of particle physics.

[ascl:1109.008]
Multipole Vectors: Decomposing Functions on a Sphere

We propose a novel representation of cosmic microwave anisotropy maps, where each multipole order l is represented by l unit vectors pointing in directions on the sky and an overall magnitude. These "multipole vectors and scalars" transform as vectors under rotations. Like the usual spherical harmonics, multipole vectors form an irreducible representation of the proper rotation group SO(3). However, they are related to the familiar spherical harmonic coefficients, alm, in a nonlinear way, and are therefore sensitive to different aspects of the CMB anisotropy. Nevertheless, it is straightforward to determine the multipole vectors for a given CMB map and we present an algorithm to compute them. Using the WMAP full-sky maps, we perform several tests of the hypothesis that the CMB anisotropy is statistically isotropic and Gaussian random. We find that the result from comparing the oriented area of planes defined by these vectors between multipole pairs 2<=l1!=l2<=8 is inconsistent with the isotropic Gaussian hypothesis at the 99.4% level for the ILC map and at 98.9% level for the cleaned map of Tegmark et al. A particular correlation is suggested between the l=3 and l=8 multipoles, as well as several other pairs. This effect is entirely different from the now familiar planarity and alignment of the quadrupole and octupole: while the aforementioned is fairly unlikely, the multipole vectors indicate correlations not expected in Gaussian random skies that make them unusually likely. The result persists after accounting for pixel noise and after assuming a residual 10% dust contamination in the cleaned WMAP map. While the definitive analysis of these results will require more work, we hope that multipole vectors will become a valuable tool for various cosmological tests, in particular those of cosmic isotropy.

[ascl:1704.014]
Multipoles: Potential gain for binary lens estimation

Multipoles, written in Python, calculates the quadrupole and hexadecapole approximations of the finite-source magnification: quadrupole (Wk,rho,Gamma) and hexadecapole (Wk,rho,Gamma). The code is efficient and faster than previously available methods, and could be generalized for use on large portions of the light curves.

[ascl:1402.006]
Munipack: General astronomical image processing software

Munipack provides easy-to-use tools for all astronomical astrometry and photometry, access to Virtual Observatory as well as FITS files operations and a simple user interface along with a powerful processing engine. Its many features include a FITS images viewer that allows for basic (astronomical) operations with frames, advanced image processor supporting an infinite dynamic range and advanced color management, and astrometric calibration of images. The astrometry module uses robust statistical estimators and algorithms. The photometry module provides the classical method detection of stars and implements the aperture photometry, calibrated on the basis of photon statistics, and allows for the automatic detection and aperture photometry of stars; calibration on absolute fluxes is possible. The software also provides a standard way to correct for all the bias, dark and flat-field frames, and many other features.

[ascl:2207.013]
MuSCAT2_transit_pipeline: MuSCAT2 photometry and transit analysis pipelines

MuSCAT2_transit_pipeline provides photometry and transit analysis pipelines for MuSCAT2. It consists of a set of executable scripts and two Python packages: muscat2ph for photometry, and muscat2ta for transit analysis. The MuSCAT2 photometry can be carried out using the scripts only. The transit analysis can also in most cases be done using the main transit analysis script m2fit, but the muscat2ta package also offers high-level classes that can be used to carry out more customized transit analysis as a Python script (or Jupyter notebook).

[ascl:1605.007]
MUSCLE: MUltiscale Spherical-ColLapse Evolution

MUSCLE (MUltiscale Spherical ColLapse Evolution) produces low-redshift approximate N-body realizations accurate to few-Megaparsec scales. It applies a spherical-collapse prescription on multiple Gaussian-smoothed scales. It achieves higher accuracy than perturbative schemes (Zel'dovich and second-order Lagrangian perturbation theory - 2LPT), and by including the void-in-cloud process (voids in large-scale collapsing regions), solves problems with a single-scale spherical-collapse scheme.

[ascl:1610.004]
MUSE-DRP: MUSE Data Reduction Pipeline

The MUSE pipeline turns the complex raw data of the MUSE integral field spectrograph into a ready-to-use datacube for scientific analysis.

[ascl:2102.012]
MUSE-PSFR: PSF reconstruction for MUSE WFM-AO mode

Fusco, Thierry; Bacon, Roland; Kamann, Sebastian; Conseil, Simon; Neichel, Benoit; Correia, Carlos; Beltramo-Martin, Olivier; Vernet, Joel; Kolb, Johan; Madec, Pierre-Yves

MUSE-PSFR reconstructs a PSF for the MUSE WFM-AO mode using telemetry data from SPARTA. The algorithm conducts a Fourier analysis of the laser-assisted ground layer adaptive optics (GLAO) residual phase statistics and has been test in end-to-end simulations. A sensitivity analysis was conducted to determine the required accuracy in terms of input parameters. MUSE-PSFR is capable of reconstructing the critical parameters of a PSF and can be used with MUSE 3D data by all MUSE users.

[ascl:1311.011]
MUSIC: MUlti-Scale Initial Conditions

MUSIC generates multi-scale initial conditions with multiple levels of refinements for cosmological ‘zoom-in’ simulations. The code uses an adaptive convolution of Gaussian white noise with a real-space transfer function kernel together with an adaptive multi-grid Poisson solver to generate displacements and velocities following first- (1LPT) or second-order Lagrangian perturbation theory (2LPT). MUSIC achieves rms relative errors of the order of 10−4 for displacements and velocities in the refinement region and thus improves in terms of errors by about two orders of magnitude over previous approaches. In addition, errors are localized at coarse-fine boundaries and do not suffer from Fourier space-induced interference ringing.

[ascl:2008.024]
MUSIC2-monofonIC: 3LPT initial condition generator

The original MUSIC code (ascl:1311.011) was designed to provide initial conditions for zoom initial conditions and is limited for applications to large-scale cosmological simulations. MUSIC2-monofonIC generates high order LPT/PPT cosmological initial conditions for single resolution cosmological simulations, and can be used for rapid predictions of large-scale structure. MUSIC2-monofonIC offers support for up to 3rd order Lagrangian perturbation theory, PPT (Semiclassical PT for Eulerian grids) up to 2nd order, and for mixed CDM+baryon sims. It direct interfaces with CLASS and can use file input from CAMB; it offers multiple output modules for RAMSES (ascl:1011.007), Arepo (ascl:1909.010), Gadget-2/3 (ascl:0003.001), and HACC via plugins, and new modules/plugins can be easily added.

[ascl:2205.011]
myRadex: Radex with a twist

myRadex solves essentially the same problem as RADEX (ascl:1010.075), except that it takes a different approach to solve the statistical equilibrium problem. Given an initial distribution, myRadex evolves the system towards equilibrium using an ODE solver. Frequencies in the input file are used by default, and a function for calculating critical densities of all the transitions of a molecule is included.

[ascl:2206.006]
MYRaf: Aperture photometry GUI for IRAF

MYRaf is a practicable astronomical image reduction and photometry software and interface for IRAF (ascl:9911.002). The library uses IRAF, PyRAF (ascl:1207.011), Ginga (ascl:1303.020), and other python packages with a Qt framework for automated software processing of data from robotic telescopes.

[ascl:1203.009]
MYRIAD: N-body code for simulations of star clusters

MYRIAD is a C++ code for collisional N-body simulations of star clusters. The code uses the Hermite fourth-order scheme with block time steps, for advancing the particles in time, while the forces and neighboring particles are computed using the GRAPE-6 board. Special treatment is used for close encounters, binary and multiple sub-systems that either form dynamically or exist in the initial configuration. The structure of the code is modular and allows the appropriate treatment of more physical phenomena, such as stellar and binary evolution, stellar collisions and evolution of close black-hole binaries. Moreover, it can be easily modified so that the part of the code that uses GRAPE-6 could be replaced by another module that uses other accelerating-hardware like the Graphics Processing Units (GPUs). Appropriate choice of the free parameters give a good accuracy and speed for simulations of star clusters up to and beyond core collapse. The code accuracy becomes comparable and even better than the accuracy of existing codes when a number of close binary systems is dynamically created in a simulation; this is due to the high accuracy of the method that is used for close binary and multiple sub-systems. The code can be used for evolving star clusters containing equal-mass stars or star clusters with an initial mass function (IMF) containing an intermediate mass black hole (IMBH) at the center and/or a fraction of primordial binaries, which are systems of particular astrophysical interest.

[ascl:1502.003]
N-GenIC: Cosmological structure initial conditions

N-GenIC is an initial conditions code for cosmological structure formation that can be used to set-up random N-body realizations of Gaussian random fields with a prescribed power spectrum in a homogeneously sampled periodic box. The code creates cosmological initial conditions based on the Zeldovich approximation, in a format directly compatible with GADGET (ascl:0003.001) or AREPO (ascl:1909.010).

[ascl:1102.001]
N-MODY: A Code for Collisionless N-body Simulations in Modified Newtonian Dynamics

N-MODY is a parallel particle-mesh code for collisionless N-body simulations in modified Newtonian dynamics (MOND). N-MODY is based on a numerical potential solver in spherical coordinates that solves the non-linear MOND field equation, and is ideally suited to simulate isolated stellar systems. N-MODY can be used also to compute the MOND potential of arbitrary static density distributions. A few applications of N-MODY indicate that some astrophysically relevant dynamical processes are profoundly different in MOND and in Newtonian gravity with dark matter.

[ascl:1411.014]
NAFE: Noise Adaptive Fuzzy Equalization

NAFE (Noise Adaptive Fuzzy Equalization) is an image processing method allowing for visualization of fine structures in SDO AIA high dynamic range images. It produces artifact-free images and gives significantly better results than methods based on convolution or Fourier transform.

[ascl:1409.009]
Nahoon: Time-dependent gas-phase chemical model

Nahoon is a gas-phase chemical model that computes the chemical evolution in a 1D temperature and density structure. It uses chemical networks downloaded from the KInetic Database for Astrochemistry (KIDA) but the model can be adapted to any network. The program is written in Fortran 90 and uses the DLSODES (double precision) solver from the ODEPACK package (ascl:1905.021) to solve the coupled stiff differential equations. The solver computes the chemical evolution of gas-phase species at a fixed temperature and density and can be used in one dimension (1D) if a grid of temperature, density, and visual extinction is provided. Grains, both neutral and negatively charged, and electrons are considered as chemical species and their concentrations are computed at the same time as those of the other species. Nahoon contains a test to check the temperature range of the validity of the rate coefficients and avoid extrapolations outside this range. A test is also included to check for duplication of chemical reactions, defined over complementary ranges of temperature.

[ascl:2303.004]
naif: Frequency analysis package

naif extracts frequencies and respective amplitudes from time-series, such as that of an orbital coordinate. Based on the Numerical Analysis of Fundamental Frequencies (NAFF) algorithm and written in Python, naif offers some improvements, particularly in computation time. It also offers functions to plot the power-spectrum before extraction of each frequency, which can be useful for debugging particular orbits.

[ascl:1708.022]
Naima: Derivation of non-thermal particle distributions through MCMC spectral fitting

Naima computes non-thermal radiation from relativistic particle populations. It includes tools to perform MCMC fitting of radiative models to X-ray, GeV, and TeV spectra using emcee (ascl:1303.002), an affine-invariant ensemble sampler for Markov Chain Monte Carlo. Naima is an Astropy (ascl:1304.002) affiliated package.

[ascl:2307.048]
NaMaster: Unified pseudo-Cl framework

NaMaster computes full-sky angular cross-power spectra of masked, spin-0 and spin-2 fields with an arbitrary number of known contaminants using a pseudo-Cl (aka MASTER) approach. The code also implements E/B-mode purification and offers both full-sky and flat-sky modes. NaMaster is available as a C library, Python module, and standalone program.

[ascl:1803.004]
nanopipe: Calibration and data reduction pipeline for pulsar timing

nanopipe is a data reduction pipeline for calibration, RFI removal, and pulse time-of-arrival measurement from radio pulsar data. It was developed primarily for use by the NANOGrav project. nanopipe is written in Python, and depends on the PSRCHIVE (ascl:1105.014) library.

[ascl:1905.020]
NAPLES: Numerical Analysis of PLanetary EncounterS

NAPLES (Numerical Analysis of PLanetary EncounterS) performs batch propagations of close encounters in the three-body problem and computes the numerical error with respect to reference trajectories computed in quadruple precision. It uses the LSODAR integrator from ODEPACK (ascl:1905.021) and the equations of motion correspond to several regularized formulations.

[ascl:2110.013]
Nauyaca: N-body approach for determining planetary masses and orbital elements

Nauyaca infers planetary masses and orbits from mid-transit times fitting. The code requires transit ephemeris per planet and stellar mass and radius, and uses minimization routines and a Markov chain Monte Carlo method to find planet parameters that best reproduce the transit times based on numerical simulations. The code package provides customized plotting tools for analyzing the results.

[ascl:2307.045]
NAVanalysis: Normalized Additional Velocity analysis

NAVanalysis studies the non-baryonic, or non-Newtonian, contribution to galaxy rotation curves straight from a given data sample. Conclusions on the radial profile of a given model can be drawn without individual galaxy fits to provide an efficient sample comparison. The method can be used to eliminate model parameter regions, find the most probable parameter regions, and uncover trends not easy to find from standard fits. Further, NAVanalysis can compare different approaches and models.

[ascl:1102.006]
NBODY Codes: Numerical Simulations of Many-body (N-body) Gravitational Interactions

I review the development of direct N-body codes at Cambridge over nearly 40 years, highlighting the main stepping stones. The first code (NBODY1) was based on the simple concepts of a force polynomial combined with individual time steps, where numerical problems due to close encounters were avoided by a softened potential. Fortuitously, the elegant Kustaanheimo-Stiefel two-body regularization soon permitted small star clusters to be studied (NBODY3). Subsequent extensions to unperturbed three-body and four-body regularization proved beneficial in dealing with multiple interactions. Investigations of larger systems became possible with the Ahmad-Cohen neighbor scheme which was used more than 20 years ago for expanding universe models of 4000 galaxies (NBODY2). Combining the neighbor scheme with the regularization procedures enabled more realistic star clusters to be considered (NBODY5). After a period of simulations with no apparent technical progress, chain regularization replaced the treatment of compact subsystems (NBODY3, NBODY5). More recently, the Hermite integration method provided a major advance and has been implemented on the special-purpose HARP computers (NBODY4) together with an alternative version for workstations and supercomputers (NBODY6). These codes also include a variety of algorithms for stellar evolution based on fast lookup functions. The treatment of primordial binaries contains efficient procedures for chaotic two-body motion as well as tidal circularization, and special attention is paid to hierarchical systems and their stability. This family of N-body codes constitutes a powerful tool for dynamical simulations which is freely available to the astronomical community, and the massive effort owes much to collaborators.

[ascl:1502.010]
nbody6tt: Tidal tensors in N-body simulations

nbody6tt, based on Aarseth's nbody6 (ascl:1102.006) code, includes the treatment of complex galactic tides in a direct N-body simulation of a star cluster through the use of tidal tensors (tt) and offers two complementary methods. The first allows consideration of any kind of galaxy and orbit, thus offering versatility; this method cannot be used to study tidal debris, as it relies on the tidal approximation (linearization of the tidal force). The second method is not limited by this and does not require a galaxy simulation; the user defines a numerical function which takes position and time as arguments, and the galactic potential is returned. The space and time derivatives of the potential are used to (i) integrate the motion of the cluster on its orbit in the galaxy (starting from user-defined initial position and velocity vector), and (ii) compute the tidal acceleration on the stars.

[ascl:2404.020]
NbodyIMRI: N-body solver for intermediate-mass ratio inspirals of black holes and dark matter spikes

Kavanagh, Bradley J.; Karydas, Theophanes K.; Bertone, Gianfranco; Di Cintio, Pierfrancesco; Pasquato, Mario

NbodyIMRI uses N-body simulations to study Dark Matter-dressed intermediate-mass ratio inspirals (IMRI) and extreme mass ratio inspiral (EMRI) systems. The code calculates all BH-BH forces and BH-DM forces directly while neglecting DM-DM pairwise interactions. This allows the code to scale up to very large numbers of DM particles in order to study stochastic processes like dynamical friction.

[ascl:1904.027]
nbodykit: Massively parallel, large-scale structure toolkit

nbodykit provides algorithms for analyzing cosmological datasets from N-body simulations and large-scale structure surveys, and takes advantage of the abundance and availability of large-scale computing resources. The package provides a unified treatment of simulation and observational datasets by insulating algorithms from data containers, and reduces wall-clock time by scaling to thousands of cores. All algorithms are parallel and run with Message Passing Interface (MPI); the code is designed to be deployed on large super-computing facilities. nbodykit offers an interactive user interface that performs as well in a Jupyter notebook as on super-computing machines.

[ascl:1010.019]
NBSymple: A Double Parallel, Symplectic N-body Code Running on Graphic Processing Units

NBSymple is a numerical code which numerically integrates the equation of motions of N 'particles' interacting via Newtonian gravitation and move in an external galactic smooth field. The force evaluation on every particle is done by mean of direct summation of the contribution of all the other system's particle, avoiding truncation error. The time integration is done with second-order and sixth-order symplectic schemes. NBSymple has been parallelized twice, by mean of the Computer Unified Device Architecture to make the all-pair force evaluation as fast as possible on high-performance Graphic Processing Units NVIDIA TESLA C 1060, while the O(N) computations are distributed on various CPUs by mean of OpenMP Application Program. The code works both in single precision floating point arithmetics or in double precision. The use of single precision allows the use at best of the GPU performances but, of course, limits the precision of simulation in some critical situations. We find a good compromise in using a software reconstruction of double precision for those variables that are most critical for the overall precision of the code.

[ascl:2303.008]
nd-redshift: Number Density Redshift Evolution Code

Behroozi, Peter S.; Marchesini, Danilo; Wechsler, Risa H.; Muzzin, Adam; Papovich, Casey; Stefanon, Mauro

Comparing galaxies across redshifts via cumulative number densities is a popular way to estimate the evolution of specific galaxy populations. nd-redshift uses abundance matching in the ΛCDM paradigm to estimate the median change in number density with redshift. It also provides estimates for the 1σ range of number densities corresponding to galaxy progenitors and descendants.

[ascl:2405.024]
ndcube: Multi-dimensional contiguous and non-contiguous coordinate-aware arrays

Ryan, Daniel F.; Mumford, Stuart; Barnes, Will T.; Baruah, Ankit Kumar; Bhope, Adwait; Buchlin, Éric; Freij, Nabil; Ginsburg, Adam; Hayes, Laura A.; Homeier, Derek; Hughes, J. Marcus; Lowder, Chris; O'Steen, Richard; Pellorce, Baptiste; Robitaille, Thomas; Sharma, Yash; Stansby, David; Shih, Albert Y.; Tollerud, Erik; Weberg, Micah J.; West, Matthew J.

ndcube manipulates, inspects, and visualizes multi-dimensional contiguous and non-contiguous coordinate-aware data arrays. A sunpy (ascl:1401.010) affiliated package, it combines data, uncertainties, units, metadata, masking, and coordinate transformations into classes with unified slicing and generic coordinate transformations and plotting and animation capabilities. ndcube handles data of any number of dimensions and axis types (*e.g.*, spatial, temporal, and spectral) whose relationship between the array elements and the real world can be described by World Coordinate System (WCS) translations.

[ascl:1411.023]
NDF: Extensible N-dimensional Data Format Library

The Extensible N-Dimensional Data Format (NDF) stores bulk data in the form of N-dimensional arrays of numbers. It is typically used for storing spectra, images and similar datasets with higher dimensionality. The NDF format is based on the Hierarchical Data System (HDS) and is extensible; not only does it provide a comprehensive set of standard ancillary items to describe the data, it can also be extended indefinitely to handle additional user-defined information of any type. The NDF library is used to read and write files in the NDF format. It is distributed with the Starlink software (ascl:1110.012).

[ascl:1101.002]
NDSPMHD Smoothed Particle Magnetohydrodynamics Code

This paper presents an overview and introduction to Smoothed Particle Hydrodynamics and Magnetohydrodynamics in theory and in practice. Firstly, we give a basic grounding in the fundamentals of SPH, showing how the equations of motion and energy can be self-consistently derived from the density estimate. We then show how to interpret these equations using the basic SPH interpolation formulae and highlight the subtle difference in approach between SPH and other particle methods. In doing so, we also critique several `urban myths' regarding SPH, in particular the idea that one can simply increase the `neighbour number' more slowly than the total number of particles in order to obtain convergence. We also discuss the origin of numerical instabilities such as the pairing and tensile instabilities. Finally, we give practical advice on how to resolve three of the main issues with SPMHD: removing the tensile instability, formulating dissipative terms for MHD shocks and enforcing the divergence constraint on the particles, and we give the current status of developments in this area. Accompanying the paper is the first public release of the NDSPMHD SPH code, a 1, 2 and 3 dimensional code designed as a testbed for SPH/SPMHD algorithms that can be used to test many of the ideas and used to run all of the numerical examples contained in the paper.

[submitted]
NE2001p: A Native Python Implementation of the NE2001 Galactic Electron Density Model

NE2001p is a fully Python implementation of the NE2001 Galactic electron density model. NE2001p forward models the dispersion and scattering of compact radio sources, including pulsars, fast radio bursts, AGNs, and masers, and the model predicts the distances of radio sources that lack independent distance measures.

[ascl:1411.013]
NEAT: Nebular Empirical Analysis Tool

NEAT is a fully automated code which carries out a complete analysis of lists of emission lines to estimate the amount of interstellar extinction, calculate representative temperatures and densities, compute ionic abundances from both collisionally excited lines and recombination lines, and finally to estimate total elemental abundances using an ionization correction scheme. NEAT uses a Monte Carlo technique to robustly propagate uncertainties from line flux measurements through to the derived abundances.

[ascl:1809.009]
NEBULA: Radiative transfer code of ionized nebulae at radio wavelengths

NEBULA performs the radiative transfer of the 3He+ hyperfine transition, radio recombination lines (RRLs), and free-free continuum emission through a model nebula. The model nebula is composed of only H and He within a three-dimension Cartesian grid with arbitrary density, temperature, and ionization structure. The 3He+ line is assumed to be in local thermodynamic equilibrium (LTE), but non-LTE effects and pressure broadening from electron impacts can be included for the RRLs. All spectra are broadened by thermal and microturbulent motions.

[ascl:1608.019]
NEBULAR: Spectrum synthesis for mixed hydrogen-helium gas in ionization equilibrium

NEBULAR synthesizes the spectrum of a mixed hydrogen helium gas in collisional ionization equilibrium. It is not a spectral fitting code, but it can be used to resample a model spectrum onto the wavelength grid of a real observation. It supports a wide range of temperatures and densities. NEBULAR includes free-free, free-bound, two-photon and line emission from HI, HeI and HeII. The code will either return the composite model spectrum, or, if desired, the unrescaled atomic emission coefficients. It is written in C++ and depends on the GNU Scientific Library (GSL).

[ascl:1010.004]
Needatool: A Needlet Analysis Tool for Cosmological Data Processing

NeedATool (Needlet Analysis Tool) performs data analysis based on needlets, a wavelet rendition powerful for the analysis of fields defined on a sphere. Needlets have been applied successfully to the treatment of astrophysical and cosmological observations, particularly to the analysis of cosmic microwave background (CMB) data. Wavelets have emerged as a useful tool for CMB data analysis, as they combine most of the advantages of both pixel space, where it is easier to deal with partial sky coverage and experimental noise, and the harmonic domain, in which beam treatment and comparison with theoretical predictions are more effective due in large part to their sharp localization.

[ascl:2210.009]
NEMESIS: Non-linear optimal estimator for multivariate spectral analysis

Irwin, P. G. J.; Teanby, N. A.; de Kok, R.; Fletcher, L. N.; Howett, C. J. A.; Tsang, C. C. C.; Wilson, C. F.; Calcutt, S. B.; Nixon, C. A.; Parrish, P. D.

NEMESIS (Non-linear optimal Estimator for MultivariatE spectral analySIS) is the general purpose correlated-k/LBL retrieval code developed from the RADTRAN project (ascl:2210.008). Originally based on the correlated-k approximation, NEMESIS also works in line-by-line (LBL) mode. It has been designed to be generally applicable to any planet and with any observing mode and so is suitable for both solar-system studies and also exoplanetary studies.

[ascl:2311.015]
nemiss: Neutrino emission from hydrocode data

nemiss calculates neutrino emission from an astrophysical jet. nemiss works as part of the PLUTO-nemiss-rlos pipeline. PLUTO (ascl:1010.045) produces a hydrodynamical jet. Then, nemiss calculates beamed neutrino emission at each eligible cell along a given direction in space. Finally, rlos (ascl:1811.009) produces a synthetic neutrino image of the jet along the given direction, taking into consideration the finite nature of the speed of light.

[ascl:1010.051]
NEMO: A Stellar Dynamics Toolbox

NEMO is an extendible Stellar Dynamics Toolbox, following an Open-Source Software model. It has various programs to create, integrate, analyze and visualize N-body and SPH like systems, following the pipe and filter architecture. In addition there are various tools to operate on images, tables and orbits, including FITS files to export/import to/from other astronomical data reduction packages. A large growing fraction of NEMO has been contributed by a growing list of authors. The source code consist of a little over 4000 files and a little under 1,000,000 lines of code and documentation, mostly C, and some C++ and Fortran. NEMO development started in 1986 in Princeton (USA) by Barnes, Hut and Teuben. See also ZENO (ascl:1102.027) for the version that Barnes maintains.

[ascl:2308.006]
Nemo: Millimeter-wave map filtering and Sunyaev-Zel'dovich galaxy cluster and source detection

Hilton, Matt; Aiola, Simone; Alonso, David; Hasselfield, Matthew; Huffenberger, Kevin; Marriage, Toby; MacCrann, Niall; Naess, Sigurd; Sifón, Cristóbal

Nemo detects millimeter-wave Sunyaev-Zel'dovich galaxy clusters and compact sources. Originally developed for the Atacama Cosmology Telescope project, the code is capable of analyzing the next generation of deep, wide multifrequency millimeter-wave maps that will be produced by experiments such as the Simons Observatory. Nemo provides several modules for analyzing ACT/SO data in addition to the command-line programs provided in the package.

[ascl:2311.005]
NEOexchange: Target and Observation Manager for the Solar System

Lister, Tim A.; Gomez, Edward; Chatelain, Joseph; Greenstreet, Sarah; Constantinescu, Cora; Phillips, Liz; MacFarlane, Julia; Tedeschi, Adam; Kosic, Isabel

The NEOexchange web portal and Target and Observation Manager ingests solar system objects, including Near-Earth Object (NEO) candidates from the Minor Planet Center, schedules observations on the Las Cumbres Observatory global telescope network and reduces, displays, and analyzes the resulting data. NEOexchange produces calibrated photometry from the imaging data and uses Source Extractor (ascl:1010.064) and SCAMP (ascl:1010.063) to perform object detection and astrometric fitting and calviacat (ascl:2207.015) to perform photometric calibration against photometric catalogs. It also has the ability to perform image registration and subtraction using SWARP (ascl:1010.068) and HOTPANTS (ascl:1504.004) and image stacking, alignment, and faint feature detection using gnuastro (ascl:1801.009).

[ascl:2405.002]
nessai: Nested sampling with artificial intelligence

nessai performs nested sampling for Bayesian Inference and incorporates normalizing flows. It is designed for applications where the Bayesian likelihood is computationally expensive. nessai uses PyTorch and also supports the use of bilby (ascl:1901.011).

[ascl:1307.017]
NEST: Noble Element Simulation Technique

Szydagis, M.; Barry, N.; Kazkaz, K.; Mock, J.; Stolp, D.; Sweany, M.; Tripathi, M.; Uvarov, S.; Walsh, N.; Woods, M.

NEST (Noble Element Simulation Technique) offers comprehensive, accurate, and precise simulation of the excitation, ionization, and corresponding scintillation and electroluminescence processes in liquid noble elements, useful for direct dark matter detectors, double beta decay searches, PET scans, and general radiation detection technology. Written in C++, NEST is an add-on module for the Geant4 simulation package that incorporates more detailed physics than is currently available into the simulation of scintillation. NEST is of particular use for low-energy nuclear recoils. All available liquid xenon data on nuclear recoils and electron recoils to date have been taken into consideration in arriving at the current models. NEST also handles the magnitude of the light and charge yields of nuclear recoils, including their electric field dependence, thereby shedding light on the possibility of detection or exclusion of a low-mass dark matter WIMP by liquid xenon detectors.

[ascl:1809.012]
nestcheck: Nested sampling calculations analysis

Nestcheck analyzes nested sampling runs and estimates numerical uncertainties on calculations using them. The package can load results from a number of nested sampling software packages, including MultiNest (ascl:1109.006), PolyChord (ascl:1502.011), dynesty (ascl:1809.013) and perfectns (ascl:1809.005), and offers the flexibility to add input functions for other nested sampling software packages. Nestcheck utilities include error analysis, diagnostic tests, and plots for nested sampling calculations.

[ascl:2103.022]
nestle: Nested sampling algorithms for evaluating Bayesian evidence

nestle is a pure Python implementation of nested sampling algorithms for evaluating Bayesian evidence. Nested sampling integrates posterior probability in order to compare models in Bayesian statistics. It is similar to Markov Chain Monte Carlo (MCMC) in that it generates samples that can be used to estimate the posterior probability distribution. Unlike MCMC, the nature of the sampling also allows one to calculate the integral of the distribution. It is also a pretty good method for robustly finding global maxima.

[submitted]
Network Flux Transport Demonstration

We have developed a method to efficiently simulate the dynamics of the magnetic flux in the solar network. We call this method Network Flux Transport (NFT). Implemented using a Spherical Centroidal Voronoi Tessellation (SCVT) based network model, magnetic flux is advected by photospheric plasma velocity fields according to the geometry of the SCVT model. We test NFT by simulating the magnetism of the Solar poles. The poles of the sun above 55 deg latitude are free from flux emergence from active regions or ephemeral regions. As such, they are ideal targets for a simplified simulation that relies on the strengths of the NFT model. This simulation method reproduces the magnetic and spatial distributions for the solar poles over two full solar cycles.

[ascl:1010.085]
Network Tools for Astronomical Data Retrieval

The first step in a science project is the acquisition and understanding of the relevant data. The tools range from simple data transfer methods to more complex browser-emulating scripts. When integrated with a defined sample or catalog, these scripts provide seamless techniques to retrieve and store data of varying types. These tools can be used to leapfrog from website to website to acquire multi-wavelength datasets. This project demonstrates the capability to use multiple data websites, in conjunction, to perform the type of calculations once reserved for on-site datasets.

[ascl:2112.007]
NeutrinoFog: Neutrino fog and floor for direct dark matter searches

NeutrinoFog calculates the neutrino floor based on the derivative of a hypothetical experimental discovery limit as a function of exposure, and leads to a neutrino floor that is only influenced by the systematic uncertainties on the neutrino flux normalizations.

[ascl:2305.024]
Nextflow: DSL for data-driven computational pipelines

Nextflow enables scalable and reproducible scientific workflows using software containers. It allows the adaptation of pipelines written in the most common scripting languages. Its fluent DSL simplifies the implementation and the deployment of complex parallel and reactive workflows on clouds and clusters. Nextflow supports deploying workflows on a variety of execution platforms including local, HPC schedulers, AWS Batch, Google Cloud Life Sciences, and Kubernetes. Additionally, it provides support for workflow dependencies through built-in support for, for example, Conda, Spack, Docker, Podman, Singularity, and Modules.

[ascl:1807.011]
nfield: Stochastic tool for QFT on inflationary backgrounds

nfield uses a stochastic formalism to compute the IR correlation functions of quantum fields during cosmic inflation in n-field dimensions. This is a necessary 1-loop resummation of the correlation functions to render them finite. The code supports the implementation of n-numbers of coupled test fields (energetically sub-dominant) as well as non-test fields.

[submitted]
nFITSview: A simple and user-friendly FITS image viewer

nFITSview is a simple, user-friendly and open-source FITS image viewer available for Linux and Windows. One of the main concepts of nFITSview is to provide an intuitive user interface which may be helpful both for scientists and for amateur astronomers. nFITSview has different color mapping and manipulation schemes, supports different formats of FITS data files as well as exporting them to different popular image formats. It also supports command-line exporting (with some restrictions) of FITS files to other image formats.

The application is written in C++/Qt for achieving better performance, and with every next version the performance aspect is taken into account.

nFITSview uses its own libnfits library (can be used separately as well) for parsing the FITS files.

[ascl:1903.013]
NFWdist: Density, distribution function, quantile function and random generation for the 3D NFW profile

Available in R and Python, the simple analytic scheme NFWdist performs highly efficient and exact sampling of the Navarro, Frenk & White (NFW) profile as a true probability distribution function, with the only variable being the concentration.

[ascl:1508.008]
NGMIX: Gaussian mixture models for 2D images

NGMIX implements Gaussian mixture models for 2D images. Both the PSF profile and the galaxy are modeled using mixtures of Gaussians. Convolutions are thus performed analytically, resulting in fast model generation as compared to methods that perform the convolution in Fourier space. For the galaxy model, NGMIX supports exponential disks and de Vaucouleurs and Sérsic profiles; these are implemented approximately as a sum of Gaussians using the fits from Hogg & Lang (2013). Additionally, any number of Gaussians can be fit, either completely free or constrained to be cocentric and co-elliptical.

[ascl:2302.001]
nicaea: NumerIcal Cosmology And lEnsing cAlculations

nicaea calculates cosmology and weak-lensing quantities and functions from theoretical models of the large-scale structure. Written in C, it can compute the Hubble parameter, distances, and geometry for background cosmology, and linear perturbations, including growth factor, transfer function, cluster mass function, and linear 3D power spectra. It also calculates fitting formulae for non-linear power spectra, emulators, and halo model for Non-linear evolution, and the HOD model for galaxy clustering. In addition, nicaea can compute quantities for cosmic shear such as the convergence power spectrum, second-order correlation functions and derived second-order quantities, and third-order aperture mass moment; it can also calculate CMB anisotropies via CAMB (ascl:1102.026).

[ascl:1608.016]
NICIL: Non-Ideal magnetohydrodynamics Coefficients and Ionisation Library

NICIL (Non-Ideal magnetohydrodynamics Coefficients and Ionisation Library) calculates the ionization values and the coefficients of the non-ideal magnetohydrodynamics terms of Ohmic resistivity, the Hall effect, and ambipolar diffusion. Written as a standalone Fortran90 module that can be implemented in existing codes, NICIL is fully parameterizable, allowing the user to choose which processes to include and decide the values of the free parameters. The module includes both cosmic ray and thermal ionization; the former includes two ion species and three species of dust grains (positively charged, negatively charged and neutral), and the latter includes five elements which can be doubly ionized.

[ascl:1508.002]
NICOLE: NLTE Stokes Synthesis/Inversion Code

NICOLE, written in Fortran 90, seeks the model atmosphere that provides the best fit to the Stokes profiles (in a least-squares sense) of an arbitrary number of simultaneously-observed spectral lines from solar/stellar atmospheres. The inversion core used for the development of NICOLE is the LORIEN engine (the Lovely Reusable Inversion ENgine), which combines the SVD technique with the Levenberg-Marquardt minimization method to solve the inverse problem.

[ascl:1302.013]
NIFTY: A versatile Python library for signal inference

Selig, Marco; Bell, Michael R.; Junklewitz, Henrik; Oppermann, Niels; Reinecke, Martin; Greiner, Maksim; Pachajoa, Carlos; Ensslin, Torsten A.

NIFTY (Numerical Information Field TheorY) is a versatile library enables the development of signal inference algorithms that operate regardless of the underlying spatial grid and its resolution. Its object-oriented framework is written in Python, although it accesses libraries written in Cython, C++, and C for efficiency. NIFTY offers a toolkit that abstracts discretized representations of continuous spaces, fields in these spaces, and operators acting on fields into classes. Thereby, the correct normalization of operations on fields is taken care of automatically. This allows for an abstract formulation and programming of inference algorithms, including those derived within information field theory. Thus, NIFTY permits rapid prototyping of algorithms in 1D and then the application of the developed code in higher-dimensional settings of real world problems. NIFTY operates on point sets, n-dimensional regular grids, spherical spaces, their harmonic counterparts, and product spaces constructed as combinations of those.

[ascl:1903.008]
NIFTy5: Numerical Information Field Theory v5

Arras, Philipp; Baltac, Mihai; Ensslin, Torsten A.; Frank, Philipp; Hutschenreuter, Sebastian; Knollmueller, Jakob; Leike, Reimar; Newrzella, Max-Niklas; Platz, Lukas; Reinecke, Martin; Stadler, Julia

NIFTy (Numerical Information Field Theory) facilitates the construction of Bayesian field reconstruction algorithms for fields being defined over multidimensional domains. A NIFTy algorithm can be developed for 1D field inference and then be used in 2D or 3D, on the sphere, or on product spaces thereof. NIFTy5 is a complete redesign of the previous framework (ascl:1302.013), and requires only the specification of a probabilistic generative model for all involved fields and the data in order to be able to recover the former from the latter. This is achieved via Metric Gaussian Variational Inference, which also provides posterior samples for all unknown quantities jointly.

[ascl:1106.016]
Nightfall: Animated Views of Eclipsing Binary Stars

Nightfall is an astronomy application for fun, education, and science. It can produce animated views of eclipsing binary stars, calculate synthetic lightcurves and radial velocity curves, and eventually determine the best-fit model for a given set of observational data of an eclipsing binary star system.

Nightfall comes with a user guide and a set of observational data for several eclipsing binary star systems.

[ascl:1501.002]
NIGO: Numerical Integrator of Galactic Orbits

NIGO (Numerical Integrator of Galactic Orbits) predicts the orbital evolution of test particles moving within a fully-analytical gravitational potential generated by a multi-component galaxy. The code can simulate the orbits of stars in elliptical and disc galaxies, including non-axisymmetric components represented by a spiral pattern and/or rotating bar(s).

[ascl:2101.011]
Nigraha: Find and evaluate planet candidates from TESS light curves

Nigraha identifies and evaluates planet candidates from TESS light curves. Using a combination of high signal to noise ratio (SNR) shallow transits, supervised machine learning, and detailed vetting, the neural network-based pipeline identifies planet candidates missed by prior searches. The pipeline runs in four stages. It first performs period finding using the Transit Least Squares (TLS) package and runs sector by sector to build a per-sector catalog. It then transforms the flux values in .fits lightcurve files to global/local views and write out the output in .tfRecords files, builds a model on training data, and saves a checkpoint. Finally, it loads a previously saved model to generate predictions for new sectors. Nigraha provides helper scripts to generate candidates in new sectors, thus allowing others to perform their own analyses.

[ascl:2111.010]
Nii: Multidimensional posterior distributions framework

Nii implements an automatic parallel tempering Markov chain Monte Carlo (APT-MCMC) framework for sampling multidimensional posterior distributions and provides an observation simulation platform for the differential astrometric measurement of exoplanets. Although this code specifically focuses on the orbital parameter retrieval problem of differential astrometry, Nii can be applied to other scientific problems with different posterior distributions and offers many control parameters in the APT part to facilitate the adjustment of the MCMC sampling strategy; these include the number of parallel chains, the β values of different chains, the dynamic range of the sampling step sizes, and frequency of adjusting the step sizes.

[ascl:2203.003]
NIMBLE: Non-parametrIc jeans Modeling with B-spLinEs

NIMBLE (Non-parametrIc jeans Modeling with B-spLinEs) inferrs the cumulative mass distribution of a gravitating system from full 6D phase space coordinates of its tracers via spherical Jeans modeling. It models the Milky Way's dark matter halo using Gaia and Dark Energy Spectroscopic Instrument Milky Way Survey (DESI MWS) data. NIMBLE includes a basic inverse modeling Jeans routine that assumes perfect and complete data is available and a more complex forward modeling Jeans routine that deconvolves observational effects (uncertainties and limited survey volume) characteristic of Gaia and the DESI-MWS. It also includes tools for generating simple equilibrium model galaxies using Agama (ascl:1805.008) and imposing mock Gaia+DESI errors on 6D phase space input data.

[ascl:2107.008]
nimbus: A Bayesian inference framework to constrain kilonova models

nimbus is a hierarchical Bayesian framework to infer the intrinsic luminosity parameters of kilonovae (KNe) associated with gravitational-wave (GW) events, based purely on non-detections. This framework makes use of GW 3-D distance information and electromagnetic upper limits from a given survey for multiple events, and self-consistently accounts for finite sky-coverage and probability of astrophysical origin.

[ascl:2210.003]
NIRDust: Near Infrared Dust finder for Type2 AGN K-band spectra

NIRDust uses K-band (2.2 micrometers) spectra to measure the temperature of the dust heated by an Active Galactic Nuclei (AGN) accretion disk. The package provides several functionalities to pre-process spectra and fit the hot dust component of a AGN K-band spectrum with a blackbody function. NIRDust needs a minimum of two spectra to run: a target spectrum, where the dust temperature will be estimated, and a reference spectrum, where the emission is considered to be purely stellar. The reference spectrum will be used by NIRDust to model the stellar emission from the target spectrum.

[ascl:1101.006]
NIRVANA: A Numerical Tool for Astrophysical Gas Dynamics

The NIRVANA code is capable of the simulation of multi-scale self-gravitational magnetohydrodynamics problems in three space dimensions employing the technique of adaptive mesh refinement. The building blocks of NIRVANA are (i) a fully conservative, divergence-free Godunov-type central scheme for the solution of the equations of magnetohydrodynamics; (ii) a block-structured mesh refinement algorithm which automatically adds and removes elementary grid blocks whenever necessary to achieve adequate resolution and; (iii) an adaptive mesh Poisson solver based on multigrid philosophy which incorporates the so-called elliptic matching condition to keep the gradient of the gravitational potential continous at fine/coarse mesh interfaces.

[ascl:2111.004]
NLopt: Nonlinear optimization library

The library NLopt performs nonlinear local and global optimization for functions with and without gradient information. It provides a simple, unified interface and wraps many algorithms for global and local, constrained or unconstrained, optimization, and provides interfaces for many other languages, including C++, Fortran, Python, Matlab or GNU Octave, OCaml, GNU Guile, GNU R, Lua, Rust, and Julia.

[ascl:2402.001]
NMMA: Nuclear Multi Messenger Astronomy framework

Pang, Peter T. H.; Dietrich, Tim; Coughlin, Michael W.; Bulla, Mattia; Tews, Ingo; Almualla, Mouza; Barna, Tyler; Kiendrebeogo, Ramodgwendé Weizmann; Kunert, Nina; Mansingh, Gargi; Reed, Brandon; Sravan, Niharika; Toivonen, Andrew; Antier, Sarah; VandenBerg, Robert O.; Heinzel, Jack; Nedora, Vsevolod; Salehi, Pouyan; Sharma, Ritwik; Somasundaram, Rahul; Van Den Broeck, Chris

NMMA probes nuclear physics and cosmology with multimessenger analysis. This fully featured, Bayesian multi-messenger pipeline targets joint analyses of gravitational-wave and electromagnetic data (focusing on the optical). Using bilby (ascl:1901.011) as the back-end, the software uses a variety of samplers to sampling these data sets. NMMA uses chiral effective field theory based neutron star equation of states when performing inference, and is also capable of estimating the Hubble Constant.

[ascl:2005.010]
NNKCDE: Nearest Neighbor Kernel Conditional Density Estimation

NNKCDE is a simple and easily interpretable Conditional Density Estimation (CDE) method. It computes a kernel density estimate of y using the k nearest neighbors of the evaluation point x. The model has only two tuning parameters: the number of nearest neighbors k and the bandwidth h of the smoothing kernel in y-space. Both tuning parameters are chosen in a principled way by minimizing the CDE loss on validation data.

[ascl:1711.024]
NOD3: Single dish reduction software

NOD3 processes and analyzes maps from single-dish observations affected by scanning effects from clouds, receiver instabilities, or radio-frequency interference. Its “basket-weaving” tool combines orthogonally scanned maps into a final map that is almost free of scanning effects. A restoration tool for dual-beam observations reduces the noise by a factor of about two compared to the NOD2 version. Combining single-dish with interferometer data in the map plane ensures the full recovery of the total flux density.

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