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Spectropolarimetry, the observation of polarization and intensity as a function of wavelength, is a powerful tool in stellar astrophysics. It is particularly useful for characterizing stars and circumstellar material, and for tracing the…

Timeseria is an object-oriented time series processing library implemented in Python, which aims at making it easier to manipulate time series data and to build statistical and machine learning models on top of it. Unlike common data…

Machine Learning · Computer Science 2024-12-31 Stefano Alberto Russo , Giuliano Taffoni , Luca Bortolussi

SpectraPy is an Astropy affiliated package for spectroscopic data reduction. It collects algorithms and methods for data reduction of astronomical spectra obtained by through-slits spectrographs. It has been created to fill the gap in…

Instrumentation and Methods for Astrophysics · Physics 2023-02-10 Marco Fumana

While current time series research focuses on developing new models, crucial questions of selecting an optimal approach for training such models are underexplored. Tsururu, a Python library introduced in this paper, bridges SoTA research…

Machine Learning · Computer Science 2025-09-22 Alina Kostromina , Kseniia Kuvshinova , Aleksandr Yugay , Andrey Savchenko , Dmitry Simakov

TemporAI is an open source Python software library for machine learning (ML) tasks involving data with a time component, focused on medicine and healthcare use cases. It supports data in time series, static, and eventmodalities and provides…

Machine Learning · Computer Science 2023-01-31 Evgeny S. Saveliev , Mihaela van der Schaar

Over the past few decades, the measurement precision of some pulsar-timing experiments has advanced from ~10 us to ~10 ns, revealing many subtle phenomena. Such high precision demands both careful data handling and sophisticated timing…

dtaianomaly is an open-source Python library for time series anomaly detection, designed to bridge the gap between academic research and real-world applications. Our goal is to (1) accelerate the development of novel state-of-the-art…

Machine Learning · Computer Science 2025-02-21 Louis Carpentier , Nick Seeuws , Wannes Meert , Mathias Verbeke

Understanding how the brain functions is one of the biggest challenges of our time. The analysis of experimentally recorded neural firing patterns (spike trains) plays a crucial role in addressing this problem. Here, the PySpike library is…

Data Analysis, Statistics and Probability · Physics 2016-07-12 Mario Mulansky , Thomas Kreuz

Partial differential equations describing the dynamics of physical systems rarely have closed-form solutions. Fourier spectral methods, which use Fast Fourier Transforms (FFTs) to approximate solutions, are a common approach to solving…

The current fleet of X-ray telescopes produces a wealth of multi-dimensional data, allowing us to study sources in time, photon energy and polarization. At the same time, it has become increasingly clear that progress in our physical…

High Energy Astrophysical Phenomena · Physics 2025-12-12 Matteo Lucchini , Benjamin Ricketts , Phil Uttley , Daniela Huppenkothen

We describe the $\texttt{Period detection and Identification Pipeline Suite}$ ($\texttt{PIPS}$) -- a new, fast, and statistically robust platform for period detection and analysis of astrophysical time-series data. $\texttt{PIPS}$ is an…

We derive analytic, closed form, numerically stable solutions for the total flux received from a spherical planet, moon or star during an occultation if the specific intensity map of the body is expressed as a sum of spherical harmonics.…

Instrumentation and Methods for Astrophysics · Physics 2019-01-30 Rodrigo Luger , Eric Agol , Daniel Foreman-Mackey , David P. Fleming , Jacob Lustig-Yaeger , Russell Deitrick

The increasing availability of high-quality optical and near-infrared spectroscopic data, as well as advances in modelling techniques, have greatly expanded the scientific potential of spectroscopic studies. However, the software tools…

Instrumentation and Methods for Astrophysics · Physics 2025-12-23 Daniele Gasparri , Lorenzo Morelli , Umberto Battino , Jairo Méndez Abreu , Adriana de Lorenzo-Cáceres

SkyPy is an open-source Python package for simulating the astrophysical sky. It comprises a library of physical and empirical models across a range of observables and a command-line script to run end-to-end simulations. The library provides…

We introduce Merlion, an open-source machine learning library for time series. It features a unified interface for many commonly used models and datasets for anomaly detection and forecasting on both univariate and multivariate time series,…

Libraries of stellar spectra are fundamental tools in the study of stellar populations and in automatic determination of atmospheric parameters for large samples of observed stars. In the context of the present volume, here I give an…

Solar and Stellar Astrophysics · Physics 2009-06-08 Paula Coelho

Plyades: A Python Library for Space Mission Design Designing a space mission is a computation-heavy task. Software tools that conduct the necessary numerical simulations and optimizations are therefore indispensable. The usability of…

Instrumentation and Methods for Astrophysics · Physics 2016-07-05 Helge Eichhorn , Reiner Anderl

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…

Computational Physics · Physics 2025-03-18 Patrick Müller , Wilfried Nörtershäuser

In this paper, we present the FATS (Feature Analysis for Time Series) library. FATS is a Python library which facilitates and standardizes feature extraction for time series data. In particular, we focus on one application: feature…

Instrumentation and Methods for Astrophysics · Physics 2015-09-02 Isadora Nun , Pavlos Protopapas , Brandon Sim , Ming Zhu , Rahul Dave , Nicolas Castro , Karim Pichara
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