Results 3251-3300 of 3598 (3503 ASCL, 95 submitted)
High precision cosmology requires analysis of large scale surveys in 3D spherical coordinates, i.e. Fourier-Bessel decomposition. Current methods are insufficient for future data-sets from wide-field cosmology surveys. 3DEX (3D EXpansions) is a public code for fast Fourier-Bessel decomposition of 3D all-sky surveys which takes advantage of HEALPix for the calculation of tangential modes. For surveys with millions of galaxies, computation time is reduced by a factor 4-12 depending on the desired scales and accuracy. The formulation is also suitable for pre-calculations and external storage of the spherical harmonics, which allows for further speed improvements. The 3DEX code can accommodate data with masked regions of missing data. It can be applied not only to cosmological data, but also to 3D data in spherical coordinates in other scientific fields.
VAPOR is the Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers. VAPOR provides an interactive 3D visualization environment that runs on most UNIX and Windows systems equipped with modern 3D graphics cards. VAPOR provides:
- A visual data discovery environment tailored towards the specialized needs of the astro and geosciences CFD community
- A desktop solution capable of handling terascale size data sets
- Advanced interactive 3D visualization tightly coupled with quantitative data analysis
- Support for multi-variate, time-varying data
- Close coupling with RSI's powerful interpretive data language, IDL
- Support for 3D visualization of WRF-ARW datasets
The FIBRE-pac (FMOS image-based reduction package) is an IRAF-based reduction tool for the fiber multiple-object spectrograph (FMOS) of the Subaru telescope. To reduce FMOS images, a number of special techniques are necessary because each image contains about 200 separate spectra with airglow emission lines variable in spatial and time domains, and with complicated throughput patterns for the airglow masks. In spite of these features, almost all of the reduction processes except for a few steps are carried out automatically by scripts in text format making it easy to check the commands step by step. Wavelength- and flux-calibrated images together with their noise maps are obtained using this reduction package.
FITSH provides a standalone environment for analysis of data acquired by imaging astronomical detectors. The package provides utilities both for the full pipeline of subsequent related data processing steps (including image calibration, astrometry, source identification, photometry, differential analysis, low-level arithmetic operations, multiple image combinations, spatial transformations and interpolations, etc.) and for aiding the interpretation of the (mainly photometric and/or astrometric) results. The package also features a consistent implementation of photometry based on image subtraction, point spread function fitting and aperture photometry and provides easy-to-use interfaces for comparisons and for picking the most suitable method for a particular problem. The utilities in the package are built on the top of the commonly used UNIX/POSIX shells (hence the name of the package), therefore both frequently used and well-documented tools for such environments can be exploited and managing massive amount of data is rather convenient.
The development of TIPSY was motivated by the need to quickly display and analyze the results of N-body simulations. Most data visualization packages are designed for the display of gridded data, and hence are unsuitable for use with particle data. Therefore, a special package was built that could easily perform the following functions:
1.) Display particle positions (as points), and velocities (as line segments) from an arbitrary viewpoint;
2.) Zoom in to a chosen position. Due to their extremely clustered nature, structure of interest in an N-body simulation is often so small that it cannot be seen when looking at the simulation as a whole;
3.) Color particles to display scalar fields. Examples of such fields are potential energy, or for SPH particles, density and temperature;
4.) Selection of a subset of the particles for display and analysis. Regions of interest are generally small subsets of the simulation;
5.) Following selected particles from one timestep to another; and,
6.) Finding cumulative properties of a collection of particles. This usually involves just a sum over the particles.
The basic data structure is an array of particle structures. Since TIPSY was built for use with cosmological N-body simulations, there are actually three separate arrays for each of the types of particle used in such simulations: collisionless particles, SPH particles, and star particles. A single timestep is read into these arrays from a disk file. Display is done by finding the x and y coordinates of the particles in the rotated coordinate system, and storing them in arrays. Screen coordinates are calculated from these arrays according to the current zoom factor. Also, a software Z-buffer is maintained to save time if many particles project to the same screen pixel. There are several types of display. An "all plot" displays all particles colored according to their type. A "radial plot" will color particles according to the projection of the velocity along the line-of-sight. A "gas plot" will color gas according to SPH quantities such as density, temperature, neutral hydrogen fraction, etc. Subsets of particles are maintained using boxes." A box structure contains a bounding box, and an array of pointers to particles within the box. All display and analysis functions are performed on the "active box." By default all particles are loaded into box 0, which becomes the active box. If a new timestep is read from disk, all boxes are destroyed. A selection of particles can be followed between timesteps via a "mark" array. Marked particles are displayed in a different color, and the analysis functions can be told to only operate on the marked particles.
This code contains several simple radiative transfer models used for fitting the blue-asymmetric spectral line signature often found in infalling molecular cloud cores. It attempts to provide a direct measure of several physical parameters of the infalling core, including infall velocity, excitation temperature, and line of site optical depth. The code includes 6 radiative transfer models, however the conclusion of the associated paper is that the 5 parameter "hill" model (hill5) is most likely the best match to the physical excitation conditions of real infalling Bonnor-Ebert type clouds.
DarkSUSY, written in Fortran, is a publicly-available advanced numerical package for neutralino dark matter calculations. In DarkSUSY one can compute the neutralino density in the Universe today using precision methods which include resonances, pair production thresholds and coannihilations. Masses and mixings of supersymmetric particles can be computed within DarkSUSY or with the help of external programs such as FeynHiggs, ISASUGRA and SUSPECT. Accelerator bounds can be checked to identify viable dark matter candidates. DarkSUSY also computes a large variety of astrophysical signals from neutralino dark matter, such as direct detection in low-background counting experiments and indirect detection through antiprotons, antideuterons, gamma-rays and positrons from the Galactic halo or high-energy neutrinos from the center of the Earth or of the Sun.
The iGalFit suite of IDL routines interactively runs GALFIT whereby the various surface brightness profiles (and their associated parameters) are represented by regions, which the user is expected to place. The regions may be saved and/or loaded from the ASCII format used by ds9 or in the Hierarchical Data Format (version 5). The software has been tested to run stably on Mac OS X and Linux with IDL 7.0.4. In addition to its primary purpose of modeling galaxy images with GALFIT, this package has several ancillary uses, including a flexible image display routines, several basic photometry functions, and qualitatively assessing Source Extractor.
SHTOOLS performs (among others) spherical harmonic transforms and reconstructions, rotations of spherical harmonic coefficients, and multitaper spectral analyses on the sphere. The package accommodates any standard normalization of the spherical harmonic functions ("geodesy" 4π normalized, Schmidt semi-normalized, orthonormalized, and unnormalized), and either real or complex spherical harmonics can be employed. Spherical harmonic transforms are calculated by exact quadrature rules using either (1) the sampling theorem of Driscoll and Healy (1994) where data are equally sampled (or spaced) in latitude and longitude, or (2) Gauss-Legendre quadrature. A least squares inversion routine for irregularly sampled data is included as well. The Condon-Shortley phase factor of (-1)m can be used or excluded with the associated Legendre functions. The spherical harmonic transforms are accurate to approximately degree 2800, corresponding to a spatial resolution of better than 4 arc minutes. Routines are included for performing localized multitaper spectral analyses and standard gravity calculations, such as computation of the geoid, and the determination of the potential associated with finite-amplitude topography. The routines are fast. Spherical harmonic transforms and reconstructions take on the order of 1 second for bandwidths less than 600 and about 3 minutes for bandwidths close to 2800.
The current version of the Zurich Extragalactic Bayesian Redshift Analyzer (ZEBRA) combines and extends several of the classical approaches to produce accurate photometric redshifts down to faint magnitudes. In particular, ZEBRA uses the template-fitting approach to produce Maximum Likelihood and Bayesian redshift estimates based on: (1.) An automatic iterative technique to correct the original set of galaxy templates to best represent the SEDs of real galaxies at different redshifts; (2.) A training set of spectroscopic redshifts for a small fraction of the photometric sample; and (3.) An iterative technique for Bayesian redshift estimates, which extracts the full two-dimensional redshift and template probability function for each galaxy.
STIFF converts scientific FITS images to the more popular TIFF format for illustration purposes. Most FITS readers and converters do not do a proper job at converting FITS image data to 8 bits. 8-bit images stored in JPEG, PNG or TIFF files have the intensities implicitly stored in a non-linear way. Most current FITS image viewers and converters provide the user an incorrect translation of the FITS image content by simply rescaling linearly input pixel values. A first consequence is that the people working on astronomical images usually have to apply narrow intensity cuts or square-root or logarithmic intensity transformations to actually see something on their deep-sky images. A less obvious consequence is that colors obtained by combining images processed this way are not consistent across such a large range of surface brightnesses. Though with other software the user is generally afforded a choice of nonlinear transformations to apply in order to make the faint stuff stand out more clearly in the images, with the limited selection of choices provides, colors will not be accurately rendered, and some manual tweaking will be necessary. The purpose of STIFF is to produce beautiful pictures in an automatic and consistent way.
The GammaLib is a versatile toolbox for the high-level analysis of astronomical gamma-ray data. It is implemented as a C++ library that is fully scriptable in the Python scripting language. The library provides core functionalities such as data input and output, interfaces for parameter specifications, and a reporting and logging interface. It implements instruments specific functionalities such as instrument response functions and data formats. Instrument specific functionalities share a common interface to allow for extension of the GammaLib to include new gamma-ray instruments. The GammaLib provides an abstract data analysis framework that enables simultaneous multi-mission analysis.
Glnemo2 is an interactive 3D visualization program developed in C++ using the OpenGL library and Nokia QT 4.X API. It displays in 3D the particles positions of the different components of an nbody snapshot. It quickly gives a lot of information about the data (shape, density area, formation of structures such as spirals, bars, or peanuts). It allows for in/out zooms, rotations, changes of scale, translations, selection of different groups of particles and plots in different blending colors. It can color particles according to their density or temperature, play with the density threshold, trace orbits, display different time steps, take automatic screenshots to make movies, select particles using the mouse, and fly over a simulation using a given camera path. All these features are accessible from a very intuitive graphic user interface.
Glnemo2 supports a wide range of input file formats (Nemo, Gadget 1 and 2, phiGrape, Ramses, list of files, realtime gyrfalcON simulation) which are automatically detected at loading time without user intervention. Glnemo2 uses a plugin mechanism to load the data, so that it is easy to add a new file reader. It's powered by a 3D engine which uses the latest OpenGL technology, such as shaders (glsl), vertex buffer object, frame buffer object, and takes in account the power of the graphic card used in order to accelerate the rendering. With a fast GPU, millions of particles can be rendered in real time. Glnemo2 runs on Linux, Windows (using minGW compiler), and MaxOSX, thanks to the QT4API.
AAOGlimpse is an experimental display program that uses OpenGL to display FITS data (and even JPEG images) as 3D surfaces that can be rotated and viewed from different angles, all in real-time. It is WCS-compliant and designed to handle three-dimensional data. Each plane in a data cube is surfaced in the same way, and the program allows the user to travel through a cube by 'peeling off' successive planes, or to look into a cube by suppressing the display of data below a given cutoff value. It can blink images and can superimpose images and contour maps from different sources using their world coordinate data. A limited socket interface allows communication with other programs.
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.
Pacerman, written in IDL, is a new method to calculate Faraday rotation measure maps from multi-frequency polarisation angle data. In order to solve the so called n-pi-ambiguity problem which arises from the observationally ambiguity of the polarisation angle which is only determined up to additions of n times pi, where n is an integer, we suggest using a global scheme. Instead of solving the n-pi-ambiguity for each data point independently, our algorithm, which we chose to call Pacerman solves the n-pi-ambiguity for a high signal-to-noise region "democratically" and uses this information to assist computations in adjacent low signal-to-noise areas.
Starlink has many applications within it to meet a variety of needs; it includes:
Many problems in astronomy and astrophysics require a computation of the spherical harmonic transforms. This is in particular the case whenever data to be analyzed are distributed over the sphere or a set of corresponding mock data sets has to be generated. In many of those contexts, rapidly improving resolutions of both the data and simulations puts increasingly bigger emphasis on our ability to calculate the transforms quickly and reliably.
The scalable spherical harmonic transform library S2HAT consists of a set of flexible, massively parallel, and scalable routines for calculating diverse (scalar, spin-weighted, etc) spherical harmonic transforms for a class of isolatitude sky grids or pixelizations. The library routines implement the standard algorithm with the complexity of O(n^3/2), where n is a number of pixels/grid points on the sphere, however, owing to their efficient parallelization and advanced numerical implementation, they achieve very competitive performance and near perfect scalability. S2HAT is written in Fortran 90 with a C interface. This software is a derivative of the spherical harmonic transforms included in the HEALPix package and is based on both serial and MPI routines of its version 2.01, however, since version 2.5 this software is fully autonomous of HEALPix and can be compiled and run without the HEALPix library.
The pS2HAT routines allow efficient, parallel calculation of the so-called 'pure' polarized multipoles. The computed multipole coefficients are equal to the standard pseudo-multipoles calculated for the apodized sky maps of the Stokes parameters Q and U subsequently corrected by so-called counterterms. If the applied apodizations fullfill certain boundary conditions, these multipoles correspond to the pure multipoles. Pure multipoles of one type, i.e., either E or B, are ensured not to contain contributions from the other one, at least to within numerical artifacts. They can be therefore further used in the estimation of the sky power spectra via the pseudo power spectrum technique, which has to however correctly account for the applied apodization on the one hand, and the presence of the counterterms, on the other.
In addition, the package contains the routines permitting calculation of the spin-weighted apodizations, given an input scalar, i.e., spin-0 window. The former are needed to compute the counterterms. It also provides routines for maps and window manipulations. The routines are written in C and based on the S2HAT library, which is used to perform all required spherical harmonic transforms as well as all inter-processor communication. They are therefore parallelized using MPI and follow the distributed-memory computational model. The data distribution patterns, pixelization choices, conventions etc are all as those assumed/allowed by the S2HAT library.
atlant is a public numerical code for fast calculations of cosmological recombination of primordial hydrogen-helium plasma is presented. This code is based on the three-level approximation (TLA) model of recombination and allows us to take into account some "fine'' physical effects of cosmological recombination simultaneously with using fudge factors.
REBOUND is a multi-purpose N-body code which is freely available under an open-source license. It was designed for collisional dynamics such as planetary rings but can also solve the classical N-body problem. It is highly modular and can be customized easily to work on a wide variety of different problems in astrophysics and beyond.
REBOUND comes with symplectic integrators WHFast, WHFastHelio, SEI, and LEAPFROG. It supports open, periodic and shearing-sheet boundary conditions. REBOUND can use a Barnes-Hut tree to calculate both self-gravity and collisions. These modules are fully parallelized with MPI as well as OpenMP. The former makes use of a static domain decomposition and a distributed essential tree. Two new collision detection modules based on a plane-sweep algorithm are also implemented. The performance of the plane-sweep algorithm is superior to a tree code for simulations in which one dimension is much longer than the other two and in simulations which are quasi-two dimensional with less than one million particles.
POWMES is a F90 program to measure very accurately the power spectrum in a N-body simulation, using Taylor expansion of some order on the cosine and sine transforms. It can read GADGET format and requires FFTW2 to be installed.
MADmap produces maximum-likelihood images of the sky from time-ordered data which include correlated noise, such as those gathered by Cosmic Microwave Background (CMB) experiments. It works efficiently on platforms ranging from small workstations to the most massively parallel supercomputers. Map-making is a critical step in the analysis of all CMB data sets, and the maximum-likelihood approach is the most accurate and widely applicable algorithm; however, it is a computationally challenging task. This challenge will only increase with the next generation of ground-based, balloon-borne and satellite CMB polarization experiments. The faintness of the B-mode signal that these experiments seek to measure requires them to gather enormous data sets. MADmap has the ability to address problems typically encountered in the analysis of realistic CMB data sets. The massively parallel and distributed implementation is detailed and scaling complexities are given for the resources required. MADmap is capable of analyzing the largest data sets now being collected on computing resources currently available.
CosmoNest is an algorithm for cosmological model selection. Given a model, defined by a set of parameters to be varied and their prior ranges, and data, the algorithm computes the evidence (the marginalized likelihood of the model in light of the data). The Bayes factor, which is proportional to the relative evidence of two models, can then be used for model comparison, i.e. to decide whether a model is an adequate description of data, or whether the data require a more complex model.
For convenience, CosmoNest, programmed in Fortran, is presented here as an optional add-on to CosmoMC (ascl:1106.025), which is widely used by the cosmological community to perform parameter fitting within a model using a Markov-Chain Monte-Carlo (MCMC) engine. For this reason it can be run very easily by anyone who is able to compile and run CosmoMC. CosmoNest implements a different sampling strategy, geared for computing the evidence very accurately and efficiently. It also provides posteriors for parameter fitting as a by-product.
This code is an extension of CMBFAST4.5.1 to compute the ISW-correlation power spectrum and the 2-point angular ISW-correlation function for a given galaxy window function. It includes dark energy models specified by a constant equation of state (w) or a linear parameterization in the scale factor (w0,wa) and a constant sound speed (c2de). The ISW computation is limited to flat geometry. Differently from the original CMBFAST4.5 version dark energy perturbations are implemented for a general dark energy fluid specified by w(z) and c2de in synchronous gauge. For time varying dark energy models it is suggested not to cross the w=-1 line, as Dr. Wenkman says: "never cross the streams", bad things can happen.
Univiewer is a visualisation program for HEALPix maps. It is written in C++ and uses OpenGL and the wxWidgets library for cross-platform portability. Using it you can:
- Rotate and zoom maps on the sphere in 3D
- Create high-resolution views of square patches of the map
- Change maximum and minimum values of the colourmap interactively
- Calculate the power spectrum of the full-sky map or a patch
- Display any column of a HEALPix map FITS file on the sphere
Since Univiewer uses OpenGL for 3D graphics, its performance is dependent your video card. It has been tested successfully on computers with as little as 8Mb video memory, but it is recommended to have at least 32Mb to get good performance.
In the 3D view, a HEALPix map is projected onto a ECP pixelation to create a texture which is wrapped around the sphere. In calculating the power spectrum, the spherical harmonic transforms are computed using the same ECP pixelation. This inevitably leads to some discrepancies at small scales due to repixelation effects, but they are reasonably small.
This is an implementation of a fairly simple-minded luminosity distance fitter, intended for use with supernova data. The calculational technique is based on evaluating the $chi^2$ of the model fit on a grid and marginalization over various nuisance parameters. Of course, the nature of these things is that this code has gotten steadily more complex, so perhaps the simple moniker is no longer justified.
SiFTO is an empirical method for modeling Type Ia supernova (SN Ia) light curves by manipulating a spectral template. We make use of high-redshift SN data when training the model, allowing us to extend it bluer than rest-frame U. This increases the utility of our high-redshift SN observations by allowing us to use more of the available data. We find that when the shape of the light curve is described using a stretch prescription, applying the same stretch at all wavelengths is not an adequate description. SiFTO therefore uses a generalization of stretch which applies different stretch factors as a function of both the wavelength of the observed filter and the stretch in the rest-frame B band. SiFTO has been compared to other published light-curve models by applying them to the same set of SN photometry, and it's been demonstrated that SiFTO and SALT2 perform better than the alternatives when judged by the scatter around the best-fit luminosity distance relationship. When SiFTO and SALT2 are trained on the same data set the cosmological results agree.
This module is a plug-in for CosmoMC and requires that software. Though programmed to analyze SNLS3 SN data, it can also be used for other SN data provided the inputs are put in the right form. In fact, this is probably a good idea, since the default treatment that comes with CosmoMC is flawed. Note that this requires fitting two additional SN nuisance parameters (alpha and beta), but this is significantly faster than attempting to marginalize over them internally.
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.
PySpecKit is a Python spectroscopic analysis and reduction toolkit meant to be generally applicable to optical, infrared, and radio spectra. It is capable of reading FITS-standard and many non-standard file types including CLASS spectra. It contains procedures for line fitting including gaussian and voigt profile fitters, and baseline-subtraction routines. It is capable of more advanced line fitting using arbitrary model grids. Fitting can be done both in batch mode and interactively. PySpecKit also produces publication-quality plots with TeX axis labels and annotations. It is designed to be extensible, allowing user-written reader, writer, and fitting routines to be "plugged in." It is actively under development and currently in the 'alpha' phase, with plans for a beta release.
The goal of the development of the Aarhus Adiabatic Oscillation Package was to have a simple and efficient tool for the computation of adiabatic oscillation frequencies and eigenfunctions for general stellar models, emphasizing also the accuracy of the results. The Fortran code offers considerable flexibility in the choice of integration method as well as ability to determine all frequencies of a given model, in a given range of degree and frequency. Development of the Aarhus adiabatic pulsation code started around 1978. Although the main features have been stable for more than a decade, development of the code is continuing, concerning numerical properties and output. The code has been provided as a generally available package and has seen substantial use at a number of installations. Further development of the package, including bringing the documentation closer to being up to date, is planned as part of the HELAS Coordination Action.
SKIRT is a radiative transfer code based on the Monte Carlo technique. The name SKIRT, acronym for Stellar Kinematics Including Radiative Transfer, reflects the original motivation for its creation: it has been developed to study the effects of dust absorption and scattering on the observed kinematics of dusty galaxies. In a second stage, the SKIRT code was extended with a module to self-consistently calculate the dust emission spectrum under the assumption of local thermal equilibrium. This LTE version of SKIRT has been used to model the dust extinction and emission of various types of galaxies, as well as circumstellar discs and clumpy tori around active galactic nuclei. A new, extended version of SKIRT code can perform efficient 3D radiative transfer calculations including a self-consistent calculation of the dust temperature distribution and the associated FIR/submm emission with a full incorporation of the emission of transiently heated grains and PAH molecules.
A big challenge in solar and stellar physics in the coming years will be to decipher the magnetism of the solar outer atmosphere (chromosphere and corona) along with its dynamic coupling with the magnetic fields of the underlying photosphere. To this end, it is important to develop rigorous diagnostic tools for the physical interpretation of spectropolarimetric observations in suitably chosen spectral lines. HAZEL is a computer program for the synthesis and inversion of Stokes profiles caused by the joint action of atomic level polarization and the Hanle and Zeeman effects in some spectral lines of diagnostic interest, such as those of the He I 1083.0 nm and 587.6 nm (or D3) multiplets. It is based on the quantum theory of spectral line polarization, which takes into account in a rigorous way all the relevant physical mechanisms and ingredients (optical pumping, atomic level polarization, level crossings and repulsions, Zeeman, Paschen-Back and Hanle effects). The influence of radiative transfer on the emergent spectral line radiation is taken into account through a suitable slab model. The user can either calculate the emergent intensity and polarization for any given magnetic field vector or infer the dynamical and magnetic properties from the observed Stokes profiles via an efficient inversion algorithm based on global optimization methods.
PolSpice (aka Spice) is a tool to statistically analyze Cosmic Microwave Background (CMB) data, as well as any other diffuse data pixelized on the sphere.
This Fortran90 program measures the 2 point auto (or cross-) correlation functions w(θ) and the angular auto- (or cross-) power spectra C(l) from one or (two) sky map(s) of Stokes parameters (intensity I and linear polarisation Q and U). It is based on the fast Spherical Harmonic Transforms allowed by isolatitude pixelisations such as Healpix [for Npix pixels over the whole sky, and a C(l) computed up to l=lmax, PolSpice complexity scales like Npix1/2 lmax2 instead of Npix lmax2]. It corrects for the effects of the masks and can deal with inhomogeneous weights given to the pixels of the map. In the case of polarised data, the mixing of the E and B modes due to the cut sky and pixel weights can be corrected for to provide an unbiased estimate of the "magnetic" (B) component of the polarisation power spectrum. Most of the code is parallelized for shared memory (SMP) architecture using OpenMP.
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.
SuperBayeS is a package for fast and efficient sampling of supersymmetric theories. It uses Bayesian techniques to explore multidimensional SUSY parameter spaces and to compare SUSY predictions with observable quantities, including sparticle masses, collider observables, dark matter abundance, direct detection cross sections, indirect detection quantities etc. Scanning can be performed using Markov Chain Monte Carlo (MCMC) technology or even more efficiently by employing a new scanning technique called MultiNest (ascl:1109.006). which implements the nested sampling algorithm. Using MultiNest, a full 8-dimensional scan of the CMSSM takes about 12 hours on 10 2.4GHz CPUs. There is also an option for old-style fixed-grid scanning. A discussion forum for SuperBayeS is available.
The package combines SoftSusy, DarkSusy, FeynHiggs, Bdecay, MultiNest and MicrOMEGAs. Some of the routines and the plotting tools are based on CosmoMC (ascl:1106.025).
SuperBayeS comes with SuperEGO, a MATLAB graphical user interface tool for interactive plotting of the results. SuperEGO has been developed by Rachid Lemrani and is based on CosmoloGUI by Sarah Bridle.
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.
CMBquick is a package for Mathematica in which tools are provided to compute the spectrum and bispectrum of Cosmic Microwave Background (CMB). It is unavoidably slow, but the main goal is not to design a tool which can be used for systematic exploration of parameters in cosmology, but rather a toy CMB code which is transparent and easily modified. Considering this, the name chosen is nothing but a joke which refers to the widely spread and used softwares CMBFAST, CAMB or CMBeasy (ascl:1007.004), which should be used for serious and heavy first order CMB computations, and which are indeed very fast.
The package CMBquick is unavoidably slow when it comes to compute the multipoles Cls, and most of it is due to the access time for variables which in Mathematica is approximately ten times slower than in C or Fortran. CMBquick is thus approximately 10 times slower than CAMB and cannot be used for the same reasons. It uses the same method as CAMB for computing the CMB spectrum, which is based on the line of sight approach. However the integration is performed in a different gauge with different time steps and k-spacing. It benefits from the power of Mathematica on numerical resolution of stiff differential systems, and the transfer functions can be obtained with exquisite accuracy.
The purpose of CMBquick is thus twofold. First, CMBquick is a slow but precise and pedagogical, tool which can be used to explore and modify the physical content of the linear and non-linear dynamics. Second, it is a tool which can help developing templates for nonlinear computations, which could then be hard coded once their correctness is checked. The number of equations for non-linear dynamics is quite sizable and CMBquick makes it easy (but slow) to manipulate the non-linear equations, to solve them precisely, and to plot them.
PyModelFit provides a pythonic, object-oriented framework that simplifies the task of designing numerical models to fit data. This is a very broad task, and hence the current functionality of PyModelFit focuses on the simpler tasks of 1D curve-fitting, including a GUI interface to simplify interactive work (using Enthought Traits). For more complicated modeling, PyModelFit also provides a wide range of classes and a framework to support more general model/data types (2D to Scalar, 3D to Scalar, 3D to 3D, and so on).
GalactICS generates N-body realizations of axisymmetric galaxy models consisting of disk, bulge and halo. Some of the code is in Fortran 77, using lines longer than 72 characters in some cases. The -e flag in the makefile allow for this for a Solaris f77 compiler. Other programs are written in C. Again, the linking between these routines works on Solaris systems, but may need to be adjusted for other architectures. We have found that linking using f77 instead of ld will often automatically load the appropriate libraries.
The graphics output by some of the programs (dbh, plotforce, diskdf, plothalo) uses the PGPLOT library. Alternatively, remove all calls to routines with names starting with "PG", as well as the -lpgplot flag in the Makefile, and the programs should still run fine.
We present a method to numerically estimate the densities of a discretely sampled data based on a binary space partitioning tree. We start with a root node containing all the particles and then recursively divide each node into two nodes each containing roughly equal number of particles, until each of the nodes contains only one particle. The volume of such a leaf node provides an estimate of the local density and its shape provides an estimate of the variance. We implement an entropy-based node splitting criterion that results in a significant improvement in the estimation of densities compared to earlier work. The method is completely metric free and can be applied to arbitrary number of dimensions. We use this method to determine the appropriate metric at each point in space and then use kernel-based methods for calculating the density. The kernel-smoothed estimates were found to be more accurate and have lower dispersion. We apply this method to determine the phase-space densities of dark matter haloes obtained from cosmological N-body simulations. We find that contrary to earlier studies, the volume distribution function v(f) of phase-space density f does not have a constant slope but rather a small hump at high phase-space densities. We demonstrate that a model in which a halo is made up by a superposition of Hernquist spheres is not capable in explaining the shape of v(f) versus f relation, whereas a model which takes into account the contribution of the main halo separately roughly reproduces the behaviour as seen in simulations. The use of the presented method is not limited to calculation of phase-space densities, but can be used as a general purpose data-mining tool and due to its speed and accuracy it is ideally suited for analysis of large multidimensional data sets.
I introduce a new code for fast calculation of the Lomb-Scargle periodogram, that leverages the computing power of graphics processing units (GPUs). After establishing a background to the newly emergent field of GPU computing, I discuss the code design and narrate key parts of its source. Benchmarking calculations indicate no significant differences in accuracy compared to an equivalent CPU-based code. However, the differences in performance are pronounced; running on a low-end GPU, the code can match 8 CPU cores, and on a high-end GPU it is faster by a factor approaching thirty. Applications of the code include analysis of long photometric time series obtained by ongoing satellite missions and upcoming ground-based monitoring facilities; and Monte-Carlo simulation of periodogram statistical properties.
Flux-averaging justifies the use of the distance-redshift relation for a smooth universe in the analysis of type Ia supernova (SN Ia) data. Flux-averaging of SN Ia data is required to yield cosmological parameter constraints that are free of the bias induced by weak gravitational lensing. SN Ia data are converted into flux. For a given cosmological model, the distance dependence of the data is removed, then the data are binned in redshift, and placed at the average redshift in each redshift bin. The likelihood of the given cosmological model is then computed using "flux statistics''. These Fortran codes compute the likelihood of an arbitrary cosmological model [with given H(z)/H_0] using flux-averaged Type Ia supernova data.
WCSTools is a package of programs and a library of utility subroutines for setting and using the world coordinate systems (WCS) in the headers of the most common astronomical image formats, FITS and IRAF .imh, to relate image pixels to sky coordinates. In addition to dealing with image WCS information, WCSTools has extensive catalog search, image header manipulation, and coordinate and time conversion tasks. This software is all written in very portable C, so it should compile and run on any computer with a C compiler.
aXe is a spectroscopic data extraction software package that was designed to handle large format spectroscopic slitless images such as those from the Wide Field Camera 3 (WFC3) and the Advanced Camera for Surveys (ACS) on HST. aXe is a PyRAF/IRAF package that consists of several tasks and is distributed as part of the Space Telescope Data Analysis System (STSDAS). The various aXe tasks perform specific parts of the extraction and calibration process and are successively used to produce extracted spectra.
We describe the InfraRed Data Reduction (IRDR) software package, a small ANSI C library of fast image processing routines for automated pipeline reduction of infrared (dithered) observations. We developed the software to satisfy certain design requirements not met in existing packages (e.g., full weight map handling) and to optimize the software for large data sets (non-interactive tasks that are CPU and disk efficient). The software includes stand-alone C programs for tasks such as running sky frame subtraction with object masking, image registration and coaddition with weight maps, dither offset measurement using cross-correlation, and object mask dilation. Although we currently use the software to process data taken with CIRSI (a near-IR mosaic imager), the software is modular and concise and should be easy to adapt/reuse for other work.
GIPSY is an acronym of Groningen Image Processing SYstem. It is a highly interactive software system for the reduction and display of astronomical data. It supports multi-tasking using a versatile user interface, it has an advanced data structure, a powerful script language and good display facilities based on the X Window system.
GIPSY consists of a number of components which can be divided into a number of classes: 1.) The user interfaces. Currently two user interfaces are available; one for interactive work and one for batch processing. 2.) The data structure. 3.) The display utilities. 4.) The application programs. These are the majority of programs.
GIPSY was designed originally for the reduction of interferometric data from the Westerbork Synthesis Radio Telescope, but in its history of more than 20 years it has grown to a system capable of handling data from many different instruments (e.g. TAURUS, IRAS etc.).
SkyCat is a tool that combines visualization of images and access to catalogs and archive data for astronomy. The tool, developed in Tcl/Tk, was originally conceived as a demo of the capabilities of the class library that was developed for the VLT. The Skycat sources currently consist of five packages:
• Tclutil - Generic Tcl and C++ utilities
• Astrotcl - Astronomical Tcl and C++ utilities
• RTD - Real-time Display classes and widgets
• Catlib - Catalog library and widgets
• Skycat - Skycat application and library package
All of the required packages are always included in the tarfile.
A radiative transfer code designed to solve the radiative transfer and statistical equilibrium equations in spherical geometry. It has been designed for application to W-R stars, O stars, and Luminous Blue-Variables. CMFGEN allows fundamental parameters such as effective temperatures, stellar radii and stellar luminosities to be determined. It can provide constraints on mass-loss rates, and allow abundance determinations for a wide range of atomic species. Further it can provide accurate energy distributions, and hence ionizing fluxes, which can be used as input for codes which model the spectra of HII regions and ring nebular.
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