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Register a new userPython Open Source Waveform Extractor (POWER): An open source, Python package to monitor and post-process numerical relativity simulations
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Numerical simulations of Einsteins field equations provide unique insights into the physics of compact objects moving at relativistic speeds, and which are driven by strong gravitational interactions. Numerical relativity has played a key role to firmly establish gravitational wave astrophysics as a new field of research, and it is now paving the way to establish whether gravitational wave radiation emitted from compact binary mergers is accompanied by electromagnetic and astro-particle counterparts. As numerical relativity continues to blend in with routine gravitational wave data analyses to validate the discovery of gravitational wave events, it is essential to develop open source tools to streamline these studies. Motivated by our own experience as users and developers of the open source, community software, the Einstein Toolkit, we present an open source, Python package that is ideally suited to monitor and post-process the data products of numerical relativity simulations, and compute the gravitational wave strain at future null infinity in high performance environments. We showcase the application of this new package to post-process a large numerical relativity catalog and extract higher-order waveform modes from numerical relativity simulations of eccentric binary black hole mergers and neutron star mergers. This new software fills a critical void in the arsenal of tools provided by the Einstein Toolkit Consortium to the numerical relativity community.
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We present astroplan - an open source, open development, Astropy affiliated package for ground-based observation planning and scheduling in Python. astroplan is designed to provide efficient access to common observational quantities such as celestial rise, set, and meridian transit times and simple transformations from sky coordinates to altitude-azimuth coordinates without requiring a detailed understanding of astropys implementation of coordinate systems. astroplan provides convenience functions to generate common observational plots such as airmass and parallactic angle as a function of time, along with basic sky (finder) charts. Users can determine whether or not a target is observable given a variety of observing constraints, such as airmass limits, time ranges, Moon illumination/separation ranges, and more. A selection of observation schedulers are included which divide observing time among a list of targets, given observing constraints on those targets. Contributions to the source code from the community are welcome.
We present an object-oriented open-source framework for solving the dynamics of open quantum systems written in Python. Arbitrary Hamiltonians, including time-dependent systems, may be built up from operators and states defined by a quantum object class, and then passed on to a choice of master equation or Monte-Carlo solvers. We give an overview of the basic structure for the framework before detailing the numerical simulation of open system dynamics. Several examples are given to illustrate the build up to a complete calculation. Finally, we measure the performance of our library against that of current implementations. The framework described here is particularly well-suited to the fields of quantum optics, superconducting circuit devices, nanomechanics, and trapped ions, while also being ideal for use in classroom instruction.
Fermipy is an open-source python framework that facilitates analysis of data collected by the Fermi Large Area Telescope (LAT). Fermipy is built on the Fermi Science Tools, the publicly available software suite provided by NASA for the LAT mission. Fermipy provides a high-level interface for analyzing LAT data in a simple and reproducible way. The current feature set includes methods for extracting spectral energy distributions and lightcurves, generating test statistic maps, finding new source candidates, and fitting source position and extension. Fermipy leverages functionality from other scientific python packages including NumPy, SciPy, Matplotlib, and Astropy and is organized as a community-developed package following an open-source development model. We review the current functionality of Fermipy and plans for future development.
Axions and axion-like particles (ALPs) are hypothetical particles that occur in extensions of the Standard Model and are candidates for cold dark matter. They could be detected through their oscillations into photons in the presence of external electromagnetic fields. gammaALPs is an open-source python framework that computes the oscillation probability between photons and axions/ALPs. In addition to solving the photon-ALP equations of motion, gammaALPs includes models for magnetic fields in different astrophysical environments such as jets of active galactic nuclei, intra-cluster and intergalactic media, and the Milky Way. Users are also able to easily incorporate their own custom magnetic-field models. We review the basic functionality and features of gammaALPs, which is heavily based on other open-source scientific packages such as numpy and scipy. Although focused on gamma-ray energies, gammaALPs can be easily extended to arbitrary photon energies.
An algorithm implemented in an open-source python library was developed for building periodic coincidence site lattice (CSL) grain boundary models in a universal fashion. The software framework aims to generate tilt and twist grain boundaries from cubic and tetragonal crystals for ab-initio and classical atomistic simulation. This framework has two useful features: i) it can calculate all the CSL matrices for generating CSL from a given Sigma ({Sigma}) value and rotation axis, allowing the users to build the specific CSL and grain boundary models; ii) it provides a convenient command line tool to enable high-throughput generation of tilt and twist grain boundaries by assigning an input crystal structure, {Sigma} value, rotation axis, and grain boundary plane. The developed algorithm in the open-source python library is expected to facilitate studies of grain boundary in materials science. The software framework is available on the website: aimsgb.org.
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