Results 1951-2000 of 2164 (2122 ASCL, 42 submitted)
TEA (Thermal Equilibrium Abundances) calculates gaseous molecular abundances under thermochemical equilibrium conditions. Given a single T,P point or a list of T,P pairs (the thermal profile of an atmosphere) and elemental abundances, TEA calculates mole fractions of the desired molecular species. TEA uses 84 elemental species and thermodynamical data for more then 600 gaseous molecular species, and can adopt any initial elemental abundances.
TelFit calculates the best-fit telluric absorption spectrum in high-resolution optical and near-IR spectra. The best-fit model can then be divided out to remove the telluric contamination. Written in Python, TelFit is essentially a wrapper to LBLRTM, the Line-By-Line Radiative Transfer Model, and simplifies the process of generating a telluric model.
Tempo analyzes pulsar timing data. Pulse times of arrival (TOAs), pulsar model parameters, and coded instructions are read from one or more input files. The TOAs are fitted by a pulse timing model incorporating transformation to the solar-system barycenter, pulsar rotation and spin-down and, where necessary, one of several binary models. Program output includes parameter values and uncertainties, residual pulse arrival times, chi-squared statistics, and the covariance matrix of the model. In prediction mode, ephemerides of pulse phase behavior (in the form of polynomial expansions) are calculated from input timing models. Tempo is the basis for the Tempo2 (ascl:1210.015) code.
Tempo2 is a pulsar timing package developed to be used both for general pulsar timing applications and also for pulsar timing array research in which data-sets from multiple pulsars need to be processed simultaneously. It was initially developed by George Hobbs and Russell Edwards as part of the Parkes Pulsar Timing Array project. Tempo2 is based on the original Tempo (ascl:1509.002) code and can be used (from the command-line) in a similar fashion. It is very versatile and can be extended by plugins.
tf_unet mitigates radio frequency interference (RFI) signals in radio data using a special type of Convolutional Neural Network, the U-Net, that enables the classification of clean signal and RFI signatures in 2D time-ordered data acquired from a radio telescope. The code is not tied to a specific segmentation and can be used, for example, to detect radio frequency interference (RFI) in radio astronomy or galaxies and stars in widefield imaging data. This U-Net implementation can outperform classical RFI mitigation algorithms.
TFIT measures galaxy photometry using prior knowledge of sources in a deep, high‐resolution image (HRI) to improve photometric measurements of objects in a corresponding low‐resolution image (LRI) of the same field, usually at a different wavelength. For background‐limited data, this technique produces optimally weighted photometry that maximizes signal‐to‐noise ratio (S/N). For objects not significantly detected in the low‐resolution image, it provides useful and quantitative information for setting upper limits.
This code is no longer updated and has been superseded by T-PHOT (ascl:1609.001).
TGCat is an archive of Chandra transmission grating spectra and a suite of software for processing such data. Users can browse and categorize Chandra gratings observations quickly and easily, generate custom plots of resulting response corrected spectra on-line without the need for special software and download analysis ready products from multiple observations in one convenient operation. Data processing for the catalog is done with a suite of ISIS/S-Lang scripts; the software is available for download. These ISIS scripts wrap and call CIAO tools for reprocessing from "Level 1" (acis_process_events or hrc_process_events) through "Level 2" (binned spectra, via tg_resolve_events and tgextract), compute responses (grating "RMFs" and "ARFs", via mkgrmf and mkgarf), and make summary plots.
THALASSA (Tool for High-Accuracy, Long-term Analyses for SSA) propagates orbits for bodies in the Earth-Moon-Sun system. Written in Fortran, it integrates either Newtonian equations in Cartesian coordinates or regularized equations of motion with the LSODAR (Livermore Solver for Ordinary Differential equations with Automatic Root-finding). THALASSA is a command-line tool; the repository also includes some Python3 scripts to perform batch propagations.
The Cannon is a data-driven method for determining stellar labels (physical parameters and chemical abundances) from stellar spectra in the context of vast spectroscopic surveys. It fits for the spectral model given training spectra and labels, with the polynomial order for the spectral model decided by the user, infers labels for the test spectra, and provides diagnostic output for monitoring and evaluating the process. It offers SNR-independent continuum normalization, performs well at lower signal-to-noise, and is very accurate.
We present the DTFE public software, a code for reconstructing fields from a discrete set of samples/measurements using the maximum of information contained in the point distribution. The code is written in C++ using the CGAL library and is parallelized using OpenMP. The software was designed for the analysis of cosmological data but can be used in other fields where one must interpolate quantities given at a discrete point set. The software comes with a wide suite of options to facilitate the analysis of 2- and 3-dimensional data and of both numerical simulations and galaxy redshift surveys. For comparison purposes, the code also implements the TSC and SPH grid interpolation methods. The code comes with an extensive user guide detailing the program options, examples and the inner workings of the code.
The Exo-Striker analyzes exoplanet orbitals, performs N-body simulations, and models the RV stellar reflex motion caused by dynamically interacting planets in multi-planetary systems. It offers a broad range of tools for detailed analysis of transit and Doppler data, including power spectrum analysis for Doppler and transit data; Keplerian and dynamical modeling of multi-planet systems; MCMC and nested sampling; Gaussian Processes modeling; and a long-term stability check of multi-planet systems. The Exo-Striker can also analyze Mean Motion Resonance (MMR) analysis, create fast fully interactive plots, and export ready-to-use LaTeX tables with best-fit parameters, errors, and statistics. It combines Fortran efficiency and Python flexibility and is cross-platform compatible (MAC OS, Linux, Windows). The tool relies on a number of open-source packages, including RVmod engine, emcee (ascl:1303.002), batman (ascl:1510.002), celerite (ascl:1709.008), and dynesty (ascl:1809.013).
The Hammer can classify spectra in a variety of formats with targets spanning the MK spectral sequence. It processes a list of input spectra by automatically estimating each object's spectral type and measuring activity and metallicity tracers in late type stars. Once automatic processing is complete, an interactive interface allows the user to manually tweak the final assigned spectral type through visual comparison with a set of templates.
Given sparse or low-quality radial-velocity measurements of a star, there are often many qualitatively different stellar or exoplanet companion orbit models that are consistent with the data. The consequent multimodality of the likelihood function leads to extremely challenging search, optimization, and MCMC posterior sampling over the orbital parameters. The Joker is a custom-built Monte Carlo sampler that can produce a posterior sampling for orbital parameters given sparse or noisy radial-velocity measurements, even when the likelihood function is poorly behaved. The method produces correct samplings in orbital parameters for data that include as few as three epochs. The Joker can therefore be used to produce proper samplings of multimodal pdfs, which are still highly informative and can be used in hierarchical (population) modeling.
The Starfish Diagram is a statistical visualization tool that simultaneously displays the properties of an individual and its parent sample through a series of histograms. The code is useful for large datasets for which one needs to understand the standing or significance of a single entry.
The Tractor optimizes or samples from models of astronomical objects. The approach is generative: given astronomical sources and a description of the image properties, the code produces pixel-space estimates or predictions of what will be observed in the images. This estimate can be used to produce a likelihood for the observed data given the model: assuming the model space actually includes the truth (it doesn’t, in detail), then if we had the optimal model parameters, the predicted image would differ from the actually observed image only by noise. Given a noise model of the instrument and assuming pixelwise independent noise, the log-likelihood is the negative chi-squared difference: (image - model) / noise.
the-wizz clusters redshift estimates for any photometric unknown sample in a survey. The software is composed of two main parts: a pair finder and a pdf maker. The pair finder finds spatial pairs and stores the indices of all closer pairs around target reference objects in an output HDF5 data file. Users then query this data file using the indices of their unknown sample to produce an output clustering-z.
THELI is an easy-to-use, end-to-end pipeline for the reduction of any optical, near-IR and mid-IR imaging data. It combines a variety of processing algorithms and third party software into a single, homogeneous tool. Over 90 optical and infrared instruments at observatories world-wide are pre-configured; more can be added by the user. The code's online appendix contains three walk-through examples using public data (optical, near-IR and mid-IR) and additional online documentation is available for training and troubleshooting.
THERMINATOR is a Monte Carlo event generator dedicated to studies of the statistical production of particles in relativistic heavy-ion collisions. The increased functionality of the code contains the following features: The input of any shape of the freeze-out hypersurface and the expansion velocity field, including the 3+1 dimensional profiles, in particular those generated externally with various hydrodynamic codes. The hypersufraces may have variable thermal parameters, which allows for studies departing significantly from the mid-rapidity region, where the baryon chemical potential becomes large. We include a library of standard sets of hypersurfaces and velocity profiles describing the RHIC Au+Au data at sqrt(s_(NN)) = 200 GeV for various centralities, as well as those anticipated for the LHC Pb+Pb collisions at sqrt(s_(NN)) = 5.5 TeV. A separate code, FEMTO-THERMINATOR, is provided to carry out the analysis of femtoscopic correlations which are an important source of information concerning the size and expansion of the system. We also include several useful scripts that carry out auxiliary tasks, such as obtaining an estimate of the number of elastic collisions after the freeze-out, counting of particles flowing back into the fireball and violating causality (typically very few), or visualizing various results: the particle p_T-spectra, the elliptic flow coefficients, and the HBT correlation radii. We also investigate the problem of the back-flow of particles into the hydrodynamic region, as well as estimate the elastic rescattering in terms of trajectory crossings. The package is written in C++ and uses the CERN ROOT environment.
Thindisk computes the line emission from a geometrically thin protoplanetary disk. It creates a datacube in FITS format that can be processed with a data reduction package (such as GILDAS, ascl:1305.010) to produce synthetic images and visibilities. These synthetic data can be compared with observations to determine the properties (e.g. central mass or inclination) of an observed disk. The disk is assumed to be in Keplerian rotation at a radius lower than the centrifugal radius (which can be set to a large value, for a purely Keplerian disk), and in infall with rotation beyond the centrifugal radius.
THOR solves the three-dimensional nonhydrostatic Euler equations. The code implements an icosahedral grid for the poles where converging meridians lead to increasingly smaller time steps; irregularities in the grid are smoothed using spring dynamics. THOR is designed to run on graphics processing units (GPUs) and is part of the open-source Exoclimes Simulation Platform.
Thrust is a parallel algorithms library which resembles the C++ Standard Template Library (STL). Thrust's high-level interface greatly enhances programmer productivity while enabling performance portability between GPUs and multicore CPUs. Interoperability with established technologies (such as CUDA, TBB, and OpenMP) facilitates integration with existing software.
TIDEV (Tidal Evolution package) calculates the evolution of rotation for tidally interacting bodies using Efroimsky-Makarov-Williams (EMW) formalism. The package integrates tidal evolution equations and computes the rotational and dynamical evolution of a planet under tidal and triaxial torques. TIDEV accounts for the perturbative effects due to the presence of the other planets in the system, especially the secular variations of the eccentricity. Bulk parameters include the mass and radius of the planet (and those of the other planets involved in the integration), the size and mass of the host star, the Maxwell time and Andrade's parameter. TIDEV also calculates the time scale that a planet takes to be tidally locked as well as the periods of rotation reached at the end of the spin-orbit evolution.
Time Utilities are software tools that, in principal, allow one to calculate BJD to a precision of 1 μs for any target from anywhere on Earth or from any spacecraft. As the quality and quantity of astrophysical data continue to improve, the precision with which certain astrophysical events can be timed becomes limited not by the data themselves, but by the manner, standard, and uniformity with which time itself is referenced. While some areas of astronomy (most notably pulsar studies) have required absolute time stamps with precisions of considerably better than 1 minute for many decades, recently new areas have crossed into this regime. In particular, in the exoplanet community, we have found that the (typically unspecified) time standards adopted by various groups can differ by as much as a minute. Left uncorrected, this ambiguity may be mistaken for transit timing variations and bias eccentricity measurements. We recommend using BJD_TDB, the Barycentric Julian Date in the Barycentric Dynamical Time standard for any astrophysical event. The BJD_TDB is the most practical absolute time stamp for extraterrestrial phenomena, and is ultimately limited by the properties of the target system. We compile a general summary of factors that must be considered in order to achieve timing precisions ranging from 15 minutes to 1 μs, and provide software for download and online webapps for use.
Time-domain astronomy sandbox consists in a series of classes to simulate and process time-domain astronomy data products in Python. The code was originally developed to model Fast Radio Burst (FRB) and Radio Frequency Interference (RFI), and evaluate different RFI mitigation methods and their effect on FRB search.
Tiny Tim generates simulated Hubble Space Telescope point spread functions (PSFs). It is written in C and distributed as source code and runs on a wide variety of UNIX and VMS systems. Tiny Tim includes mirror zonal errors, time dependent aberrations (for the pre-repair instruments), field dependent obscuration patterns (for WF/PC-1 and WFPC2), and filter passband effects. It can produce a normally sampled or subsampled PSF. Output is a FITS image file.
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.
Tilted Ring Fitting Code (TiRiFiC) is a prototype computer program to construct simulated (high-resolution) astronomical spectroscopic 3d-observations (data cubes) of simple kinematical and morphological models of rotating (galactic) disks. It is possible to automatically optimize the parameterizations of constructed model disks to fit spectroscopic (3d-) observations via a χ2 minimization. TiRiFiC is currently implemented as an add-on to the Groningen Image Processing System (GIPSY) software package and attempts to provide a method to automatically fit an extended tilted-ring model directly to a data cube.
TITAN is a general-purpose radiation hydrodynamics code developed at the Laboratory for Computational Astrophysics (NCSA, University of Illinois at Urbana-Champaign). TITAN solves the coupled sets of radiation transfer and fluid dynamics equations on an adaptive mesh in one spatial dimension.
TLS is an optimized transit-fitting algorithm to search for periodic transits of small planets. In contrast to BLS: Box Least Squares (ascl:1607.008), which searches for rectangular signals in stellar light curves, TLS searches for transit-like features with stellar limb-darkening and including the effects of planetary ingress and egress. TLS also analyses the entire, unbinned data of the phase-folded light curve. TLS yields a ~10% higher detection efficiency (and similar false alarm rates) compared to BLS though has a higher computational load. This load is partly compensated for by applying an optimized period sampling and transit duration sampling constrained to the physically plausible range.
TLUSTY is a user-oriented package written in FORTRAN77 for modeling stellar atmospheres and accretion disks and wide range of spectroscopic diagnostics. In the program's maximum configuration, the user may start from scratch and calculate a model atmosphere of a chosen degree of complexity, and end with a synthetic spectrum in a wavelength region of interest for an arbitrary stellar rotation and an arbitrary instrumental profile. The user may also model the vertical structure of annuli of an accretion disk.
TM (Torus Mapper) produces models for orbits in action-angle coordinates in axisymmetric potentials using torus mapping, a non-perturbative technique for creating orbital tori for specified values of the action integrals. It can compute a star's position at any time given an orbital torus and a star’s position at a reference time, and also provides a way to choose initial conditions for N-body simulations of realistic disc galaxies that start in perfect equilibrium. TM provides some advantages over use of a standard time-stepper to create orbits.
The Tübingen NLTE Model-Atmosphere Package (TMAP) is a tool to calculate stellar atmospheres in spherical or plane-parallel geometry in hydrostatic and radiative equilibrium allowing departures from local thermodynamic equilibrium (LTE) for the population of atomic levels. It is based on the Accelerated Lambda Iteration (ALI) method and is able to account for line blanketing by metals. All elements from hydrogen to nickel may be included in the calculation with model atoms which are tailored for the aims of the user.
The IDL package reduces and analyzes radio astronomy data. It translates SDFITS files into TMBIDL format, and can average and display spectra, remove baselines, and fit Gaussian models.
TMCalc is a C code developed as an extension to ARES. Using the line list given, the code can be used as a precise and fast indicator of the spectroscopic temperature and metallicity for dwarf FKG stars with effective temperatures ranging from 4500 K to 6500 K and with [Fe/H] ranging from -0.8 dex to 0.4 dex.
TomograPy is an open-source software freely available on the Python Package Index that can perform fast tomographic inversions that scale linearly with the number of measurements, linearly with the length of the reconstruction cube (and not the number of voxels) and linearly with the number of cores and can use data from different sources and with a variety of physical models. For performance, TomograPy uses a parallelized-projection algorithm. It relies on the World Coordinate System standard to manage various data sources. A variety of inversion algorithms are provided to perform the tomographic-map estimation. A test suite is provided along with the code to ensure software quality. Since it makes use of the Siddon algorithm it is restricted to rectangular parallelepiped voxels but the spherical geometry of the corona can be handled through proper use of priors.
TOPCAT is an interactive graphical viewer and editor for tabular data. Its aim is to provide most of the facilities that astronomers need for analysis and manipulation of source catalogues and other tables, though it can be used for non-astronomical data as well. It understands a number of different astronomically important formats (including FITS and VOTable) and more formats can be added.
It offers a variety of ways to view and analyse tables, including a browser for the cell data themselves, viewers for information about table and column metadata, and facilities for 1-, 2-, 3- and higher-dimensional visualisation, calculating statistics and joining tables using flexible matching algorithms. Using a powerful and extensible Java-based expression language new columns can be defined and row subsets selected for separate analysis. Table data and metadata can be edited and the resulting modified table can be written out in a wide range of output formats.
It is a stand-alone application which works quite happily with no network connection. However, because it uses Virtual Observatory (VO) standards, it can cooperate smoothly with other tools in the VO world and beyond, such as VODesktop, Aladin and ds9. Between 2006 and 2009 TOPCAT was developed within the AstroGrid project, and is offered as part of a standard suite of applications on the AstroGrid web site, where you can find information on several other VO tools.
The program is written in pure Java and available under the GNU General Public Licence. It has been developed in the UK within the Starlink and AstroGrid projects, and under PPARC and STFC grants. Its underlying table processing facilities are provided by STIL.
TORUS is a flexible radiation transfer and radiation-hydrodynamics code. The code has a basic infrastructure that includes the AMR mesh scheme that is used by several physics modules including atomic line transfer in a moving medium, molecular line transfer, photoionization, radiation hydrodynamics and radiative equilibrium. TORUS is useful for a variety of problems, including magnetospheric accretion onto T Tauri stars, spiral nebulae around Wolf-Rayet stars, discs around Herbig AeBe stars, structured winds of O supergiants and Raman-scattered line formation in symbiotic binaries, and dust emission and molecular line formation in star forming clusters. The code is written in Fortran 2003 and is compiled using a standard Gnu makefile. The code is parallelized using both MPI and OMP, and can use these parallel sections either separately or in a hybrid mode.
Toyz is a python web framework that allows scientists to interact with large images and data sets stored on a remote server. A web application is run on the server containing the data and clients are run from web browsers on the user's computer. Toyz displays large FITS images also also renders any image format supported by Pillow (a fork of the Python Imaging Library), contains a GUI to interact with linked plots, and offers a customizable framework that allows students and researchers to create their own work spaces inside a Toyz environment. Astro-Toyz extends the features of the Toyz image viewer, allowing users to view world coordinates and align images based on their WCS.
TP2VIS creates visibilities from a single dish cube; the TP visibilities can be combined with the interferometric visibilities in a joint deconvolution using, for example, CASA's tclean() method. TP2VIS requires CASA 5.4 (ascl:1107.013) or above.
TPI computes the gravitational dynamics of particles orbiting a supermassive black hole (SBH). A distinction is made to two types of particles: test particles and field particles. Field particles are assumed to move in quasi-static Keplerian orbits around the SBH that precess due to the enclosed mass (Newtonian 'mass precession') and relativistic effects. Otherwise, field-particle-field-particle interactions are neglected. Test particles are integrated in the time-dependent potential of the field particles and the SBH. Relativistic effects are included in the equations of motion (including the effects of SBH spin), and test-particle-test-particle interactions are neglected.
Visibilities from radio interferometers have not traditionally been used to study the fast transient sky. Millisecond transients (e.g., fast radio bursts) and periodic sources (e.g., pulsars) have been studied with single-dish radio telescopes and a software stack developed over the past few decades. tpipe is an initial attempt to develop the fast transient algorithms for visibility data. Functions exist for analysis of visibilties, such as reading data, flagging data, applying interferometric gain calibration, and imaging. These functions are given equal footing as time-domain techniques like filters and dedispersion.
tpipe has been largely superseded by rtpipe (ascl:1706.002).
TPM carries out collisionless (dark matter) cosmological N-body simulations, evolving a system of N particles as they move under their mutual gravitational interaction. It combines aspects of both Tree and Particle-Mesh algorithms. After the global PM forces are calculated, spatially distinct regions above a given density contrast are located; the tree code calculates the gravitational interactions inside these denser objects at higher spatial and temporal resolution. The code is parallel and uses MPI for message passing.
TPZ, a parallel code written in python, produces robust and accurate photometric redshift PDFs by using prediction tree and random forests. The code also produces ancillary information about the sample used, such as prior unbiased errors estimations (giving an estimation of performance) and a ranking of importance of variables as well as a map of performance indicating where extra training data is needed to improve overall performance. It is designed to be easy to use and a tutorial is available.
TRADES (TRAnsits and Dynamics of Exoplanetary Systems) simultaneously fits observed radial velocities and transit times data to determine the orbital parameters of exoplanetary systems from observational data. It uses a dynamical simulator for N-body systems that also fits the available data during the orbital integration and determines the best combination of the orbital parameters using grid search, χ2 minimization, genetic algorithms, particle swarm optimization, and bootstrap analysis.
The Sloan Digital Sky Survey (SDSS) produces large amounts of data daily. transfer, written in Python, provides the effective automation needed for daily data transfer operations and management and operates essentially free of human intervention. This package has been tested and used successfully for several years.
We present an IDL graphical user interface-driven software package designed for the analysis of extrasolar planet transit light curves. The Transit Analysis Package (TAP) software uses Markov Chain Monte Carlo (MCMC) techniques to fit light curves using the analytic model of Mandel and Agol (2002). The package incorporates a wavelet based likelihood function developed by Carter and Winn (2009) which allows the MCMC to assess parameter uncertainties more robustly than classic chi-squared methods by parameterizing uncorrelated "white" and correlated "red" noise. The software is able to simultaneously analyze multiple transits observed in different conditions (instrument, filter, weather, etc). The graphical interface allows for the simple execution and interpretation of Bayesian MCMC analysis tailored to a user's specific data set and has been thoroughly tested on ground-based and Kepler photometry. AutoKep provides a similar GUI for the preparation of Kepler MAST archive data for analysis by TAP or any other analysis software. This paper describes the software release and provides instructions for its use.
Transit Clairvoyance uses Artificial Neural Networks (ANNs) to predict the most likely short period transiters to have additional transiters, which may double the discovery yield of the TESS (Transiting Exoplanet Survey Satellite). Clairvoyance is a simple 2-D interpolant that takes in the number of planets in a system with period less than 13.7 days, as well as the maximum radius amongst them (in Earth radii) and orbital period of the planet with maximum radius (in Earth days) in order to predict the probability of additional transiters in this system with period greater than 13.7 days.
Transit light curves for stellar continua have only one minimum and a "U" shape. By contrast, transit curves for optically thin chromospheric emission lines can have a "W" shape because of stellar limb-brightening. We calculate light curves for an optically thin shell of emission and fit these models to time-resolved observations of Si IV absorption by the planet HD209458b. We find that the best fit Si IV absorption model has R_p,SIV/R_*= 0.34+0.07-0.12, similar to the Roche lobe of the planet. While the large radius is only at the limit of statistical significance, we develop formulae applicable to transits of all optically thin chromospheric emission lines.
Transit calculates the transmission or emission spectrum of a planetary atmosphere with application to extrasolar-planet transit and eclipse observations, respectively. It computes the spectra by solving the one-dimensional line-by-line radiative-transfer equation for an atmospheric model.
A self-organizing map (SOM) can be used to identify planetary candidates from Kepler and K2 datasets with accuracies near 90% in distinguishing known Kepler planets from false positives. TransitSOM classifies a Kepler or K2 lightcurve using a self-organizing map (SOM) created and pre-trained using PyMVPA (ascl:1703.009). It includes functions for users to create their own SOMs.
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