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A time series is a sample of observations of well-defined data points obtained through repeated measurements over a certain time range. The analysis of such data samples has become increasingly important not only in natural science but also…
$clustertools$ is a Python package for analyzing star cluster simulations. The package is built around the $StarCluster$ class, which stores all data read in from the snapshot of a given model star cluster. The package contains functions…
This paper introduces the multiband periodogram, a general extension of the well-known Lomb-Scargle approach for detecting periodic signals in time-domain data. In addition to advantages of the Lomb-Scargle method such as treatment of…
The characterization and analysis of light curves are vital for understanding the physical and rotational properties of artificial space objects such as satellites, rocket stages, and space debris. This paper introduces the Light Curve…
The wavelet transform has been used for numerous studies in astrophysics, including signal--noise periodicity and decomposition as well as the signature of differential rotation in stellar light curves. In the present work, we apply the…
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…
In this letter, we propose a method for period estimation in light curves from periodic variable stars using correntropy. Light curves are astronomical time series of stellar brightness over time, and are characterized as being noisy and…
Rotation curves are a fundamental tool in the study of galaxies across cosmic time, and with the advent of large integral field unit (IFU) kinematic surveys there is an increasing need for efficient and flexible modelling tools. We present…
Since 2009, the Kepler, K2, and TESS missions have produced a vast number of lightcurves for public use. To assist citizen scientists in processing those lightcurves, the LcTools software system was developed. The system provides a set of…
Light curves represent astronomical time series of flux measured across one or more photometric bands. With the rapid growth of large-scale sky surveys, time-domain astronomy has become an essential area of modern astrophysical research.…
Data cleaning is one of the most important tasks in data analysis processes. One of the perennial challenges in data analytics is the detection and handling of non-valid data. Failing to do so can result in inaccurate analytics and…
AOtools is a Python package which is open-source and aimed at providing tools for adaptive optics users and researchers. We present version 1.0 which contains tools for adaptive optics processing, including analysing data in the pupil…
The first step when investigating time varying data is the detection of any reliable changes in star brightness. This step is crucial to decreasing the processing time by reducing the number of sources processed in later, slower steps.…
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.…
The field of gamma-ray astronomy has seen important progress during the last decade, yet there exists so far no common software framework for the scientific analysis of gamma-ray telescope data. We propose to fill this gap by means of the…
Astronomy light curves are sparse, gappy, and heteroscedastic. As a result standard time series methods regularly used for financial and similar datasets are of little help and astronomers are usually left to their own instruments and…
With the volume and availability of astronomical data growing rapidly, astronomers will soon rely on the use of machine learning algorithms in their daily work. This proceeding aims to give an overview of what machine learning is and delve…
We present a versatile transit simulator aimed at generating light curves for arbitrarily shaped objects transiting stars. Utilizing a Monte Carlo algorithm, it accurately models the stellar flux blocked by these objects, producing precise…
We present a web-based application designed to simulate rotational light curves of small airless Solar System bodies under user-defined geometrical and physical conditions. The tool integrates both physical and empirical photometric models…
Fractal behaviour, i.e. scale invariance in spatio-temporal dynamics, have been found to describe and model many systems in nature, in particular fluid mechanics and geophysical related geometrical objects, like the convective boundary…