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The stellar occultation technique provides competitive accuracy in determining the sizes, shapes, astrometry, etc., of the occulting body, comparable to in-situ observations by spacecraft. With the increase in the number of known Solar…
aeon is a unified Python 3 library for all machine learning tasks involving time series. The package contains modules for time series forecasting, classification, extrinsic regression and clustering, as well as a variety of utilities,…
orbitize! is an open-source, object-oriented software package for fitting the orbits of directly-imaged objects. It packages the Orbits for the Impatient (OFTI) algorithm and a parallel-tempered Markov Chain Monte Carlo (MCMC) algorithm…
The challenges inherent to time-domain multi-messenger astronomy require strategic actions so that adapted, optimized follow-up observations are performed efficiently. In particular, poorly localized events require dedicated tiling and/or…
The analysis of experimental results with Python often requires writing many code scripts which all need access to the same set of functions. In a common field of research, this set will be nearly the same for many users. The qspec Python…
This review outlines concepts of mathematical statistics, elements of probability theory, hypothesis tests and point estimation for use in the analysis of modern astronomical data. Least squares, maximum likelihood, and Bayesian approaches…
We present sensipy, an open-source Python toolkit for simulating observations of transient astrophysical sources, particularly in the high-energy (HE, keV-GeV) and very-high-energy (VHE, GeV-TeV) gamma-ray ranges. The most explosive events…
Astronomy depends on ever increasing computing power. Processor clock-rates have plateaued, and increased performance is now appearing in the form of additional processor cores on a single chip. This poses significant challenges to the…
NEMESISPY is a Python package developed to perform parametric atmospheric modelling and radiative transfer calculation for the retrievals of exoplanetary spectra. It is a recent development of the well-established Fortran NEMESIS library…
Different research communities are involved in planetary coordinate standardization. Geologists and Remote Sensing specialists work on extending Earth standards to Planets using Geographical Information Systems (GIS) and coordinate…
Astronomy began as a visual science, first through careful observations of the sky using either an eyepiece or the naked eye, then on to the preservation of those images with photographic media and finally the digital encoding of that…
Astronomy is increasingly encountering two fundamental truths: (1) The field is faced with the task of extracting useful information from extremely large, complex, and high dimensional datasets; (2) The techniques of astroinformatics and…
Filtergraph is a web application being developed and maintained by the Vanderbilt Initiative in Data-intensive Astrophysics (VIDA) to flexibly and rapidly visualize a large variety of astronomy datasets of various formats and sizes. The…
This paper presents gnss_lib_py, a Python library used to parse, analyze, and visualize data from a variety of GNSS (Global Navigation Satellite Systems) data sources. The gnss_lib_py library's ease of use, modular capabilities, testing…
We review some aspects of the current state of data-intensive astronomy, its methods, and some outstanding data analysis challenges. Astronomy is at the forefront of "big data" science, with exponentially growing data volumes and data…
For over a decade, the SpacePy project has contributed open-source solutions for the production and analysis of heliophysics data and simulation results. Here we introduce SpacePy's functionality for the scientific user and present relevant…
In this article, we describe a very simple technique to locate naked-eye planets in the sky, to an accuracy of $\sim 1^{\circ}$. The procedure, comprising just three steps, involves very simple manual calculations for planetary orbits…
Data volumes from multiple sky surveys have grown from gigabytes into terabytes during the past decade, and will grow from terabytes into tens (or hundreds) of petabytes in the next decade. This exponential growth of new data both enables…
We describe the use of Multi Order Coverage (MOC) maps as a practical way to manage complex regions of the sky for the planning of multi-messenger observations. MOC maps are a data structure that provides a multi-resolution representation…
The emergence of Agile Earth Observation Satellites (AEOSs) has marked a significant turning point in the field of Earth Observation (EO), offering enhanced flexibility in data acquisition. Concurrently, advancements in onboard satellite…