The Astrophysics Source Code Library (ASCL) is a free online registry for source codes of interest to astronomers and astrophysicists and lists codes that have been used in research that has appeared in, or been submitted to, peer-reviewed publications. The ASCL is indexed by the SAO/NASA Astrophysics Data System (ADS) and is citable by using the unique ascl ID assigned to each code. The ascl ID can be used to link to the code entry by prefacing the number with ascl.net (i.e., ascl.net/1201.001).
VISIBLE is a python code to apply approximated matched filters to interferometric data, allowing line detection directly in visibility space.
The Opik method gives a mean probability of collision of a small body with a given planet.
It is a statistical value valid for an orbit with given (a,e,i) and undefined argument of perihelion.
The Opik method gives the collision probability per orbital revolution of the small body, from this value it is calculated the mean collision time, that means, the mean time after which the object collides with the planet. In some cases the planet can eject the small body from the solar system. The program allows to estimate the mean time for the ejection. The Opik method does not take into account other perturbers than the planet considered, so it only provides an idea of the timescales involved.
Above a critical dark matter-nucleus scattering cross section any terrestrial direct detection experiment loses sensitivity to dark matter, since the Earth crust, atmosphere, and potential shielding layers start to block off the dark matter particles. This critical cross section is commonly determined by describing the average energy loss of the dark matter particles analytically. However, this treatment overestimates the stopping power of the Earth crust. Therefore the obtained bounds should be considered as conservative.
This tool allows to determine the critical cross-section for strongly interacting DM for various direct detection experiments systematically and precisely using Monte Carlo simulations of DM trajectories inside the Earth crust/atmosphere/any kind of shielding.
The Automated Radio Telescope Image Processing Pipeline (ARTIP) automates the entire process of flagging, calibrating, and imaging for radio-interferometric data. ARTIP starts with raw data, i.e. a measurement set and goes through multiple stages, such as flux calibration, bandpass calibration, phase calibration, and imaging to generate continuum and spectral line images. Each stage can also be run independently. The pipeline provides continuous feedback to the user through various messages, charts and logs. It is written using standard python libraries and the CASA package. The pipeline can deal with datasets with multiple spectral windows and also multiple target sources which may have arbitrary combinations of flux/bandpass/phase calibrators.
CMacIonize simulates the self-consistent evolution of HII regions surrounding young O and B stars, or other sources of ionizing radiation. The code combines a Monte Carlo photoionization algorithm that uses a complex mix of hydrogen, helium and several coolants in order to self-consistently solve for the ionization and temperature balance at any given time, with a standard first order hydrodynamics scheme. The code can be run as a post-processing tool to get the line emission from an existing simulation snapshot, but can also be used to run full radiation hydrodynamical simulations. Both the radiation transfer and the hydrodynamics are implemented in a general way that is independent of the grid structure that is used to discretize the system, allowing it to be run both as a standard fixed grid code and also as a moving-mesh code.
venice reads a mask file (DS9 or fits type) and a catalogue of objects (ascii or fits type) to create a pixelized mask, find objects inside/outside a mask, or generate a random catalogue of objects inside/outside a mask. The program reads the mask file and checks if a point, giving its coordinates, is inside or outside the mask, i.e. inside or outside at least one polygon of the mask.
Verne is a python code for calculating the Earth-stopping effect for super-heavy Dark Matter (DM). The code allows you to calculate the speed distribution (and DM signal rate) at an arbitrary detector location on the Earth. The calculation takes into account the full anisotropic DM velocity distribution and the full velocity dependence of the DM-nucleus cross section. Results can be obtained for any DM mass and cross section, though the results are most reliable for very heavy DM particles.
This code is meant to emulate a fortran program written by B. Peterson for use with reverberation mapping.
The code cross correlates two light curves that are unevenly sampled using linear interpolation and measures the peak and centroid of the cross-correlation function. In addition, it is possible to run Monteo Carlo iterations using flux randomization and random subset selection (RSS) to produce cross-correlation centroid distributions to estimate the uncertainties in the cross correlation results. The ideas behind the methodology that this code implements are described in detail by Peterson et al. (1998): http://arxiv.org/abs/astro-ph/9802103
FAC calculates various atomic radiative and collisional processes, including radiative transition rates, collisional excitation and ionization by electron impact, energy levels, photoionization, and autoionization, and their inverse processes radiative recombination and dielectronic capture. The package also includes a collisional radiative model to construct synthetic spectra for plasmas under different physical conditions.
RadVel models Keplerian orbits in radial velocity (RV) time series. The code is written in Python with a fast Kepler's equation solver written in C. It provides a framework for fitting RVs using maximum a posteriori optimization and computing robust confidence intervals by sampling the posterior probability density via Markov Chain Monte Carlo (MCMC). RadVel can perform Bayesian model comparison and produces publication quality plots and LaTeX tables.