Results 351-400 of 2352 (2312 ASCL, 40 submitted)
The SPICE (Spacecraft Planet Instrument C-matrix [“Camera matrix”] Events) toolkit offers a set of building blocks for constructing tools supporting multi-mission, international space exploration programs and research in planetary science, heliophysics, Earth science, and for observations from terrestrial observatories. It computes many kinds of observation geometry parameters, including the ephemerides, orientations, sizes, and shapes of planets, satellites, comets and asteroids. It can also compute the orientation of a spacecraft, its various moving structures, and an instrument's field-of-view location on a planet's surface or atmosphere. It can determine when a specified geometric event occurs, such as when an object is in shadow or is in transit across another object. The SPICE toolkit is available in FORTRAN 77, ANSI C, IDL, and MATLAB.
SPHYNX addresses subsonic hydrodynamical instabilities and strong shocks; it is Newtonian, grounded on the Euler-Lagrange formulation of the smoothed-particle hydrodynamics technique, and density based. SPHYNX uses an integral approach for estimating gradients, a flexible family of interpolators to suppress pairing instability, and incorporates volume elements to provides better partition of the unity.
SPHRAY, a Smoothed Particle Hydrodynamics (SPH) ray tracer, is designed to solve the 3D, time dependent, radiative transfer (RT) equations for arbitrary density fields. The SPH nature of SPHRAY makes the incorporation of separate hydrodynamics and gravity solvers very natural. SPHRAY relies on a Monte Carlo (MC) ray tracing scheme that does not interpolate the SPH particles onto a grid but instead integrates directly through the SPH kernels. Given initial conditions and a description of the sources of ionizing radiation, the code will calculate the non-equilibrium ionization state (HI, HII, HeI, HeII, HeIII, e) and temperature (internal energy/entropy) of each SPH particle. The sources of radiation can include point like objects, diffuse recombination radiation, and a background field from outside the computational volume. The MC ray tracing implementation allows for the quick introduction of new physics and is parallelization friendly. A quick Axis Aligned Bounding Box (AABB) test taken from computer graphics applications allows for the acceleration of the raytracing component. We present the algorithms used in SPHRAY and verify the code by performing all the test problems detailed in the recent Radiative Transfer Comparison Project of Iliev et. al. The Fortran 90 source code for SPHRAY and example SPH density fields are made available online.
SPHGR (Smoothed-Particle Hydrodynamics Galaxy Reduction) is a python based open-source framework for analyzing smoothed-particle hydrodynamic simulations. Its basic form can run a baryonic group finder to identify galaxies and a halo finder to identify dark matter halos; it can also assign said galaxies to their respective halos, calculate halo & galaxy global properties, and iterate through previous time steps to identify the most-massive progenitors of each halo and galaxy. Data about each individual halo and galaxy is collated and easy to access.
SPHGR supports a wide range of simulations types including N-body, full cosmological volumes, and zoom-in runs. Support for multiple SPH code outputs is provided by pyGadgetReader (ascl:1411.001), mainly Gadget (ascl:0003.001) and TIPSY (ascl:1111.015).
Spheroid determines the size distribution of polarizing interstellar dust grains based on electromagnetic scattering by spheroidal particles. It contains subroutines to treat the case of complex refractive indices, and also includes checks for some limiting cases.
The Spherical Library provides an efficient and accurate mathematical representation of shapes on the celestial sphere, such as sky coverage and footprints. Shapes of arbitrary complexity and size can be dynamically created from simple building blocks, whose exact area is also analytically computed. This methodology is also perfectly suited for censoring problematic parts of datasets, e.g., bad seeing, satellite trails or diffraction spikes of bright stars.
Spheral++ provides a steerable parallel environment for performing coupled hydrodynamical and gravitational numerical simulations. Hydrodynamics and gravity are modeled using particle-based methods (SPH and N-Body). It uses an Adaptive Smoothed Particle Hydrodynamics (ASPH) algorithm, provides a total energy conserving compatible hydro mode, and performs fluid and solid material modeling and damage and fracture modeling in solids.
We describe a fast tree algorithm for gravitational N-body simulation on SIMD parallel computers. The tree construction uses fast, parallel sorts. The sorted lists are recursively divided along their x, y and z coordinates. This data structure is a completely balanced tree (i.e., each particle is paired with exactly one other particle) and maintains good spatial locality. An implementation of this tree-building algorithm on a 16k processor Maspar MP-1 performs well and constitutes only a small fraction (approximately 15%) of the entire cycle of finding the accelerations. Each node in the tree is treated as a monopole. The tree search and the summation of accelerations also perform well. During the tree search, node data that is needed from another processor is simply fetched. Roughly 55% of the tree search time is spent in communications between processors. We apply the code to two problems of astrophysical interest. The first is a simulation of the close passage of two gravitationally, interacting, disk galaxies using 65,636 particles. We also simulate the formation of structure in an expanding, model universe using 1,048,576 particles. Our code attains speeds comparable to one head of a Cray Y-MP, so single instruction, multiple data (SIMD) type computers can be used for these simulations. The cost/performance ratio for SIMD machines like the Maspar MP-1 make them an extremely attractive alternative to either vector processors or large multiple instruction, multiple data (MIMD) type parallel computers. With further optimizations (e.g., more careful load balancing), speeds in excess of today's vector processing computers should be possible.
Spextool (Spectral EXtraction tool) is an IDL-based data reduction package for SpeX, a medium resolution near-infrared spectrograph on the NASA IRTF. It performs all of the steps necessary to produce spectra ready for analysis and publication including non-linearity corrections, flat fielding, wavelength calibration, telluric correction, flux calibration, and order merging.
SPEX provides a uniform interface suitable for the X-ray spectral analysis of a number of solar (or other) instruments in the X and Gamma Ray energy ranges. Part of the SolarSoft (ascl:1208.013) library, this package is suitable for any datastream which can be placed in the form of response vs interval where the response is usually a counting rate (spectrum) and the interval is normally an accumulation over time. Together with an algorithm which can be used to relate a model input spectrum to the observed response, generally a response matrix, the dataset is amenable to analysis with this package. Currently the data from a large number of instruments, including SMM (HXRBS, GRS Gamma, GRS X1, and GRS X2), Yohkoh (HXT, HXS, GRS, and SXT,) CGRO (BATSE SPEC and BATSE LAD), WIND (TGRS), HIREX, and NEAR (PIN). SPEX's next generation software is available in OSPEX (ascl:2007.018), an object-oriented package that is also part of and dependent on SolarSoft.
SPEX is optimized for the analysis and interpretation of high-resolution cosmic X-ray spectra. The software is especially suited for fitting spectra obtained by current X-ray observatories like XMM-Newton, Chandra, and Suzaku. SPEX can fit multiple spectra with different model components simultaneously and handles highly complex models with many free parameters.
spex_to_xspec takes the output from the collisional ionisation equilibrium model in the SPEX spectral modelling and fitting package (ascl:1308.014), and converts it into a form usable by the XSPEC spectral fitting package (ascl:9910.005). For a list of temperatures it computes the line strengths and continuum spectra using SPEX. These are collated and written into an APEC-format table model which can be loaded into Xspec. By allowing SPEX models to be loaded into XSPEC, the program allows easy comparison between the results of the SPEX and APEC codes.
SPEGID (Single-Pulse Event Group IDentification) identifies astrophysical pulse candidates as trial single-pulse event groups (SPEGs) by first applying Density Based Spatial Clustering of Applications with Noise (DBSCAN) on trial single-pulse events and then merging the clusters that fall within the expected DM (Dispersion Measure) and time span of astrophysical pulses. SPEGID also calculates the peak score for each SPEG in the S/N versus DM space to identify the expected peak-like shape in the signal-to-noise (S/N) ratio versus DM curve of astrophysical pulses. Additionally, SPEGID groups SPEGs that appear at a consistent DM and therefore are likely emitted from the same source. After running SPEGID, periocity.py can be used to find (or verify) the underlying periodicity among a group of SPEGs (i.e., astrophysical pulse candidates).
SPECX is a general purpose line data reduction system. It can read and write FITS data cubes but has specialist support for the GSD format data from the James Clerk Maxwell Telescope. It includes commands to store and retrieve intermediate spectra in storage registers and perform the fitting and removal of polynomial, harmonic and Gaussian baselines.
SPECX can filter and edit spectra and list and display spectra on a graphics terminal. It is able to perform Fourier transform and power spectrum calculations, process up to eight spectra (quadrants) simultaneously with either the same or different center, and assemble a number of reduced individual spectra into a map file and contour or greyscale any plane or planes of the resulting cube.
Two versions of SPECX are distributed. Version 6.x is the VMS and Unix version and is distributed as part of the Starlink software collection. Version 7.x is a complete rewrite of SPECX distributed for Windows.
SpecViz interactively visualizes and analyzes 1D astronomical spectra. It reads data from FITS and ASCII tables and allows spectra to be easily plotted and examined. It supports instrument-specific data quality handling, flexible spectral units conversions, custom plotting attributes, plot annotations, tiled plots, among other features. SpecViz includes a measurement tool for spectral lines for performing and recording measurements and a model fitting capability for creating simple (e.g., single Gaussian) or multi-component models (e.g., multiple Gaussians for emission and absorption lines in addition to regions of flat continua). SpecViz is built on top of the Specutils (ascl:1902.012) Astropy-affiliated python library, providing a visual, interactive interface to the analysis capabilities in that library.
Specview is a tool for 1-D spectral visualization and analysis of astronomical spectrograms. Written in Java, it is capable of reading all the Hubble Space Telescope spectral data formats as well as data from several other instruments (such as IUE, FUSE, ISO, FORS and SDSS), preview spectra from MAST, and data from generic FITS and ASCII tables. It can read data from Virtual Observatory servers, and read and write spectrogram data in Virtual Observatory SED format. It can also read files in the SPC Galactic format used in the chemistry field. Once ingested, data can be plotted and examined with a large selection of custom settings. Specview supports instrument-specific data quality handling, flexible spectral units conversions, custom plotting attributes, plot annotations, tiled plots, hardcopy to JPEG files and PostScript file or printer, etc. Specview can be used to build wide-band SEDs, overplotting or combining data from the same astronomical source taken with different instruments and/or spectral bands. Data can be further processed with averaging, splicing, detrending, and Fourier filtering tools. Specview has a spectral model fitting capability that enables the user to work with multi-component models (including user-defined models) and fit models to data.
Specutils provides a basic interface for the loading, manipulation, and common forms of analysis of spectroscopic data. Its generic data containers and accompanying modules can be used to build a particular scientific workflow or higher-level analysis tool. It is an AstroPy (ascl:1304.002) affiliated package, and SpecViz (ascl:1902.011), which is built on top of Specutils, provides a visual, interactive interface to its analysis capabilities.
SPECTRUM ((C) Richard O. Gray, 1992-2008) is a stellar spectral synthesis program which runs on a number of platforms, including most flavors of UNIX and LINUX. It will also run under Windwos 9x/ME/NT/2000/XP using the Cygwin tools or the distributed Windows binaries. The code for SPECTRUM has been written in the "C" language. SPECTRUM computes the LTE synthetic spectrum given a stellar atmosphere model. SPECTRUM can use as input the fully blanketed stellar atmosphere models of Robert Kurucz including the new models of Castelli and Kurucz, but any other stellar atmosphere model which can be cast into the format of Kurucz's models can be used as well. SPECTRUM can be programmed with "command-line switches" to give a number of different outputs. In the default mode, SPECTRUM computes the stellar-disk-integrated normalized-intensity spectrum, but in addition, SPECTRUM will compute the absolute monochromatic flux from the stellar atmosphere or the specific intensity from any point on the stellar surface.
SPECTRE's chief purpose is the manipulation of single-order spectra, and it performs many of the tasks contained in such IRAF routines as "splot" and "rv". It is not meant to replace the much more general capabilities of IRAF, but does some functions in a manner that some might find useful. A brief list of SPECTRE tasks are: spectrum smoothing; equivalent width calculation; continuum rectification; noise spike excision; and spectrum comparison. SPECTRE was written to manipulate coude spectra, and thus is probably most useful for working on high dispersion spectra. Echelle spectra can be gathered from various observatories, reduced to singly-dimensioned spectra using IRAF, then written out as FITS files, thus becoming accessible to SPECTRE. Three different spectra may be manipulated and displayed simultaneously. SPECTRE, written in standard FORTRAN77, can be used only with the SM graphics package.
Spectral-cube provides an easy way to read, manipulate, analyze, and write data cubes with two positional dimensions and one spectral dimension, optionally with Stokes parameters. It is a versatile data container for building custom analysis routines. It provides a uniform interface to spectral cubes, robust to the wide range of conventions of axis order, spatial projections, and spectral units that exist in the wild, and allows easy extraction of cube sub-regions using physical coordinates. It has the ability to create, combine, and apply masks to datasets and is designed to work with datasets too large to load into memory, and provide basic summary statistic methods like moments and array aggregates.
Spectra calculates the power spectrum of a time series equally spaced or not based on the Spectral Correlation Coefficient (Ferraz-Mello 1981, Astron. Journal 86 (4), 619). It is very efficient for detection of low frequencies.
Studies of astrophysical non-LTE media require the combination of atomic and molecular spectroscopic and collisional data often described differently in various databases. SPECTCOL is a tool that implements VAMDC standards, retrieve relevant information from different databases such as CDMS, HITRAN, BASECOL, and can upload local files. All transfer of data between the client and the databases use the VAMDC-XSAMS schema. The spectroscopic and collisional information is combined and useful outputs (ascii or xsams) are provided for the study of the interstellar medium.
Specstack creates stacked spectra using a simple algorithm with sigma-clipping to combine the spectra of galaxies in the rest-frame into a single averaged spectrum. Though written originally for galaxy spectra, it also works for other types of objects. It is written in Python and is started from the command-line.
SpecPro is an interactive program for viewing and analyzing spectra, particularly in the context of modern imaging surveys. In addition to displaying the 1D and 2D spectrum, SpecPro can simultaneously display available stamp images as well as the spectral energy distribution of a source. This extra information can help significantly in assessing a spectrum.
Specdre performs spectroscopy data reduction and analysis. General features of the package include data cube manipulation, arc line calibration, resampling and spectral fitting. Particular care is taken with error propagation, including tracking covariance. SPECDRE is distributed as part of the Starlink software collection (ascl:1110.012).
The DEEP2 DEIMOS Data Reduction Pipeline ("spec2d") is an IDL-based, automated software package designed to reduce Keck/DEIMOS multi-slit spectroscopic observations, collected as part of the DEEP2 Galaxy Redshift Survey. The pipeline is best suited for handling data taken with the 1200 line/mm grating tilted towards the red (lambda_c ~ 7800Å). The spec2d reduction package takes the raw DEIMOS data as its input and produces a variety of outputs including 2-d slit spectra and 1-d object spectra.
SpDust is an IDL program that evaluates the spinning dust emissivity for user-provided environmental conditions. A new version of the code became available in March, 2010.
SpcAudace processes long slit spectra with automated pipelines and performs astrophysical analysis of the latter data. These powerful pipelines do all the required steps in one pass: standard preprocessing, masking of bad pixels, geometric corrections, registration, optimized spectrum extraction, wavelength calibration and instrumental response computation and correction. Both high and low resolution long slit spectra are managed for stellar and non-stellar targets. Many types of publication-quality figures can be easily produced: pdf and png plots or annotated time series plots. Astrophysical quantities can be derived from individual or large amount of spectra with advanced functions: from line profile characteristics to equivalent width and periodogram. More than 300 documented functions are available and can be used into TCL scripts for automation. SpcAudace is based on Audela open source software.
SPARTA is a post-processing framework for particle-based cosmological simulations. The code is written in pure, MPI-parallelized C and is optimized for high performance. The main purpose of SPARTA is to understand the formation of structure in a dynamical sense, namely by analyzing the trajectories (or orbits) of dark matter particles around their halos. Within this framework, the user can add analysis modules that operate on individual trajectories or entire halos. The initial goal of SPARTA was to compute the splashback radius of halos, but numerous other applications have been implemented as well, including spherical overdensity calculations and tracking subhalos via their constituent particles.
SPARTA analyzes periodically-variable spectroscopic observations. Intended for common astronomical uses, SPARTA facilitates analysis of single- and double-lined binaries, high-precision radial velocity extraction, and periodicity searches in complex, high dimensional data. It includes two modules, UNICOR and USuRPER. UNICOR analyzes spectra using 1-d CCF. It includes maximum-likelihood analysis of multi-order spectra and detection of systematic shifts. USuRPER (Unit Sphere Representation PERiodogram) is a phase-distance correlation (PDC) based periodogram and is designed for very high-dimensional data such as spectra.
SparsePZ uses sparse basis representation to fully represent individual photometric redshift probability density functions (PDFs). This approach requires approximately half the parameters for the same multi-Gaussian fitting accuracy, and has the additional advantage that an entire PDF can be stored by using a 4-byte integer per basis function. Only 10-20 points per galaxy are needed to reconstruct both the individual PDFs and the ensemble redshift distribution, N(z), to an accuracy of 99.9 per cent when compared to the one built using the original PDFs computed with a resolution of δz = 0.01, reducing the required storage of 200 original values by a factor of 10-20. This basis representation can be directly extended to a cosmological analysis, thereby increasing computational performance without losing resolution or accuracy.
SPARK (Software Package for Astronomical Reduction with KMOS) reduces data from the K-band Multi Object Spectrograph (KMOS) for the VLT. In many cases, science data can be processed using a single recipe; alternately, all functions this recipe provides can be performed using other recipes provided as tools. Among the functions the recipes provide are sky subtraction, cube reconstruction with the application of flexure corrections, dividing out the telluric spectrum, applying an illumination correction, aligning the cubes, and then combinging them. The result is a set of files which contain the combined datacube and associated noise cube for each of the 24 integral field unit (IFUs). The pipeline includes simple error propagation.
The Seismic Propagation through Active Regions and Convection (SPARC) code was developed by S. Hanasoge. The acoustic wavefield in SPARC is simulated by numerically solving the linearised 3-D Euler equations in Cartesian geometry (e.g., see Hanasoge, Duvall and Couvidat (2007)). Spatial derivatives are calculated using sixth-order compact finite differences (Lele,1992) and time evolution is achieved through the repeated application of an optimized second-order five-stage Runge-Kutta scheme (Hu, 1996). Periodic horizontal boundaries are used.
SPAMCART generates synthetic spectral energy distributions and intensity maps from smoothed particle hydrodynamics simulation snapshots. It follows discrete luminosity packets as they propagate through a density field, and computes the radiative equilibrium temperature of the ambient dust from their trajectories. The sources can be extended and/or embedded, and discrete and/or diffuse. The density is not mapped on to a grid, and therefore the calculation is performed at exactly the same resolution as the hydrodynamics. The code strictly adheres to Kirchhoff's law of radiation. The algorithm is based on the Lucy Monte Carlo radiative transfer method and is fairly simple to implement, as it uses data structures that are already constructed for other purposes in modern particle codes
SPAM is a extension to AIPS for reducing high-resolution, low-frequency radio interferometric observations. Direction-dependent ionospheric calibration and image-plane ripple suppression are among the features that help to make high-quality sub-GHz images. Data reductions are captured in well-tested Python scripts that execute AIPS tasks directly (mostly during initial data reduction steps), call high-level functions that make multiple AIPS or ParselTongue calls, and require few manual operations.
SPAM searches for imprints of Hu-Sawicki f(R) gravity on the rotation curves of the SPARC (Spitzer Photometry and Accurate Rotation Curves) sample using the MCMC sampler emcee (ascl:1303.002). The code provides attributes for inspecting the MCMC chains and translating names of parameters to indices. The SPAM package also contains plotting scripts.
SpaghettiLens allows citizen scientists to model gravitational lenses collaboratively; the software should also be easily adaptable to any other, reasonably similar problem. It lets volunteers execute a computer intensive task that cannot be easily executed client side and relies on citizen scientists collaborating. SpaghettiLens makes survey data available to citizen scientists, manages the model configurations generated by the volunteers, stores the resulting model configuration, and delivers the actual model. A model can be shared and discussed with other volunteers and revised, and new child models can be created, resulting in a branching version tree of models that explore different possibilities. Scientists can choose a collection of models; discussion among volunteers and scientists prune the tree to determine which models will receive further analysis.
SpacePy provides data analysis and visualization tools for the space science community. Written in Python, it builds on the capabilities of the NumPy and MatPlotLib packages to make basic data analysis, modeling and visualization easier. It contains modules for handling many complex time formats, obtaining data from the OMNI database, and accessing the powerful Onera library. It contains a library of commonly used empirical relationships, performs association analysis, coordinate transformations, radiation belt modeling, and CDF reading, and creates publication quality plots.
The Solar Position Algorithm (SPA) calculates the solar zenith and azimuth angles in the period from the year -2000 to 6000, with uncertainties of +/- 0.0003 degrees based on the date, time, and location on Earth. SPA is implemented in C; in addition to being available for download, an online calculator using this code is available at http://www.nrel.gov/midc/solpos/spa.html.
SP_Ace (Stellar Parameters And Chemical abundances Estimator) estimates the stellar parameters Teff, log g, [M/H], and elemental abundances. It employs 1D stellar atmosphere models in Local Thermodynamic Equilibrium (LTE). The code is highly automated and suitable for analyzing the spectra of large spectroscopic surveys with low or medium spectral resolution (R = 2000-20 000). A web service for calculating these values with the software is also available.
Spin-Orbit Tomography (SOT) is a retrieval technique of a two-dimensional map of an Exo-Earth from time-series data of integrated reflection light. The software provides code for the Bayesian version of the static SOT and dynamic mapping (time-varying mapping) with full Bayesian modeling, and tutorials for L2 and Bayesian SOT are available in jupyter notebooks.
SOPT (Sparse OPTimisation) is a C implementation of the Sparsity Averaging Reweighted Analysis (SARA) algorithm. The approach relies on the observation that natural images exhibit strong average sparsity; average sparsity outperforms state-of-the-art priors that promote sparsity in a single orthonormal basis or redundant frame, or that promote gradient sparsity.
SOPIE (Sequential Off-Pulse Interval Estimation) provides functions to non-parametrically estimate the off-pulse interval of a source function originating from a pulsar. The technique is based on a sequential application of P-values obtained from goodness-of-fit tests for the uniform distribution, such as the Kolmogorov-Smirnov, Cramér-von Mises, Anderson-Darling and Rayleigh goodness-of-fit tests.
SOPHISM models astronomical instrumentation from the entrance of the telescope to data acquisition at the detector, along with software blocks dealing with, for example, demodulation, inversion, and compression. The code performs most analyses done with light in astronomy, such as differential photometry, spectroscopy, and polarimetry. The simulator offers flexibility and implementation of new effects and subsystems, making it user-adaptable for a wide variety of instruments. SOPHISM can be used for all stages of instrument definition, design, operation, and lifetime tracking evaluation.
SOPHIA (Simulations Of Photo Hadronic Interactions in Astrophysics) solves problems connected to photohadronic processes in astrophysical environments and can also be used for radiation and background studies at high energy colliders such as LEP2 and HERA, as well as for simulations of photon induced air showers. SOPHIA implements well established phenomenological models, symmetries of hadronic interactions in a way that describes correctly the available exclusive and inclusive photohadronic cross section data obtained at fixed target and collider experiments.
SONG computes the non-linear evolution of the Universe in order to predict cosmological observables such as the bispectrum of the Cosmic Microwave Background (CMB). More precisely, it is a second-order Boltzmann code, as it solves the Einstein and Boltzmann equations up to second order in the cosmological perturbations.
SolarSoft is a set of integrated software libraries, data bases, and system utilities which provide a common programming and data analysis environment for Solar Physics. The SolarSoftWare (SSW) system is built from Yohkoh, SOHO, SDAC and Astronomy libraries and draws upon contributions from many members of those projects. It is primarily an IDL based system, although some instrument teams integrate executables written in other languages. The SSW environment provides a consistent look and feel at widely distributed co-investigator institutions to facilitate data exchange and to stimulate coordinated analysis. Commonalities and overlap in solar data and analysis goals are exploited to permit application of fundamental utilities to the data from many different solar instruments. The use of common libraries, utilities, techniques and interfaces minimizes the learning curve for investigators who are analyzing new solar data sets, correlating results from multiple experiments or performing research away from their home institution.
Although large volumes of solar data are available for investigation and study, the vast majority of these data remain unlabeled and are therefore not amenable to modern supervised machine learning methods. Having a way to accurately and automatically classify spectra into categories related to the degree of solar activity is highly desirable and will assist and speed up future research efforts in solar physics. At the same time, the large volume of raw observational data is a serious bottleneck for machine learning, requiring powerful computational means that are not at the disposal of many laboratories. Additionally, the raw data communication imposes some restrictions on real time data observations and requires considerable bandwidth and energy for the onboard solar observation systems. To cope with the above mentioned issues, we propose a framework to classify solar activity on compressed data. To this end, we used a labeling scheme from a pre-existing vector quantization technique in conjunction with several machine learning algorithms to categorize Mg II spectra measured by NASA’s small explorer satellite IRIS into several groups characterizing solar activity. Our training data set is a human annotated list of 85 IRIS observations containing 29097 frames in total or equivalently 9 million Mg II spectra. The annotated types of Solar activity are: active region, pre-flare activity, Solar flare, Sunspot and quiet Sun. We used the vector quantization to compress these data and to reduce its complexity before training classifiers. From a host of classifiers, we found that the XGBoost classifier produced the most accurate results on the compressed data, yielding over a 95% prediction rate, and outperforming other ML methods like convolution neural networks, K-nearest neighbors, naive Bayes classifiers and support vector machines. A principle finding of this research is that the classification performance on compressed and uncompressed data is comparable under our particular architecture, implying the possibility of large compression rates for relatively low degrees of information loss.
SoFiAX is a web-based platform to merge and interact with the results of parallel execution of SoFiA HI source finding software [ascl:1412.001] and other steps of processing ASKAP Wallaby HI survey data.
SoFiA is a flexible source finding pipeline designed to detect and parameterise sources in 3D spectral-line data cubes. SoFiA combines several powerful source finding and parameterisation algorithms, including wavelet denoising, spatial and spectral smoothing, source mask optimisation, spectral profile fitting, and calculation of the reliability of detections. In addition to source catalogues in different formats, SoFiA can also generate a range of output data cubes and images, including source masks, moment maps, sub-cubes, position-velocity diagrams, and integrated spectra. The pipeline is controlled by simple parameter files and can either be invoked on the command line or interactively through a modern graphical user interface.
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