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We study astrometric residuals from a simultaneous fit of Hyper Suprime-Cam images. We aim to characterize these residuals and study the extent to which they are dominated by atmospheric contributions for bright sources. We use Gaussian…

Instrumentation and Methods for Astrophysics · Physics 2021-06-09 P. -F. Léget , P. Astier , N. Regnault , M. Jarvis , P. Antilogus , A. Roodman , D. Rubin , C. Saunders

The study of temporal properties of variable sources can elucidate their physical processes. In this context, we present a critical study comparing three approaches to periodic or quasiperiodic behavior: Gaussian process, power spectrum,…

High Energy Astrophysical Phenomena · Physics 2024-05-08 Fei-Fan Song , Jirong Mao

Very high precision seismic space missions such as CoRoT and Kepler provide the means for testing the modelling of transport processes in stellar interiors. For some stars, such as $\delta$ Scuti $\gamma$ Doradus and Be stars, for instance,…

Solar and Stellar Astrophysics · Physics 2015-07-15 Rhita-Maria Ouazzani , Ian W. Roxburgh , Marc-Antoine Dupret

Standard sparse pseudo-input approximations to the Gaussian process (GP) cannot handle complex functions well. Sparse spectrum alternatives attempt to answer this but are known to over-fit. We suggest the use of variational inference for…

Machine Learning · Statistics 2015-03-23 Yarin Gal , Richard Turner

Gaussian processes (GPs) are powerful and widely used probabilistic regression models, but their effectiveness in practice is often limited by the choice of kernel function. This kernel function is typically handcrafted from a small set of…

Machine Learning · Computer Science 2026-02-13 Jihao Andreas Lin , Sebastian Ament , Louis C. Tiao , David Eriksson , Maximilian Balandat , Eytan Bakshy

Simulating a Gaussian process requires sampling from a high-dimensional Gaussian distribution, which scales cubically with the number of sample locations. Spectral methods address this challenge by exploiting the Fourier representation,…

Machine Learning · Statistics 2026-02-27 Arsalan Jawaid , Abdullah Karatas , Jörg Seewig

The Kepler target KIC 5110407, a K-type star, shows strong quasi-periodic light curve fluctuations likely arising from the formation and decay of spots on the stellar surface rotating with a period of 3.4693 days. Using an established…

Solar and Stellar Astrophysics · Physics 2015-06-15 Rachael M. Roettenbacher , John D. Monnier , Robert O. Harmon , Thomas Barclay , Martin Still

We introduce a fast algorithm for Gaussian process regression in low dimensions, applicable to a widely-used family of non-stationary kernels. The non-stationarity of these kernels is induced by arbitrary spatially-varying vertical and…

Numerical Analysis · Mathematics 2025-03-28 P. Michael Kielstra , Michael Lindsey

We present the results of an automated variability analysis of the Kepler public data measured in the first quarter (Q1) of the mission. In total, about 150 000 light curves have been analysed to detect stellar variability, and to identify…

Solar and Stellar Astrophysics · Physics 2015-05-27 J. Debosscher , J. Blomme , C. Aerts , J. De Ridder

Light curves produced by the Kepler mission demonstrate stochastic brightness fluctuations (or "flicker") of stellar origin which contribute to the noise floor, limiting the sensitivity of exoplanet detection and characterization methods.…

Solar and Stellar Astrophysics · Physics 2021-06-02 Samuel J. Van Kooten , Evan H. Anders , Steven R. Cranmer

Gaussian processes (GPs) are flexible models that can capture complex structure in large-scale dataset due to their non-parametric nature. However, the usage of GPs in real-world application is limited due to their high computational cost…

Machine Learning · Statistics 2018-11-06 Congzheng Song , Yiming Sun

Gaussian processes are widely employed as versatile modelling and predictive tools in spatial statistics, functional data analysis, computer modelling and diverse applications of machine learning. They have been widely studied over…

Statistics Theory · Mathematics 2023-03-28 Didong Li , Wenpin Tang , Sudipto Banerjee

There have recently been several reports of apparently periodic variations in the light curves of quasars, e.g. PG 1302-102 by Graham et al. (2015a). Any quasar showing periodic oscillations in brightness would be a strong candidate to be a…

Instrumentation and Methods for Astrophysics · Physics 2016-07-27 S. Vaughan , P. Uttley , A. G. Markowitz , D. Huppenkothen , M. J. Middleton , W. N. Alston , J. D. Scargle , W. M. Farr

In galactic nuclei, the gravitational potential is dominated by the central supermassive black hole, so stars follow quasi-Keplerian orbits. These orbits are distorted by gravitational forces from other stars, leading to long-term orbital…

Astrophysics of Galaxies · Physics 2022-09-14 Jean-Baptiste Fouvry , Walter Dehnen , Scott Tremaine , Ben Bar-Or

Context. Considerable effort has been put into using light curves observed by space telescopes such as CoRoT, Kepler and TESS for determining stellar rotation periods. While rotation periods of active stars can be reliably determined, the…

Solar and Stellar Astrophysics · Physics 2020-01-08 A. I. Shapiro , E. M. Amazo-Gómez , N. A. Krivova , S. K. Solanki

We present a method for finding binaries among pulsating stars that were observed by the Kepler Mission. We use entire four-year light curves to accurately measure the frequencies of the strongest pulsation modes, then track the pulsation…

Solar and Stellar Astrophysics · Physics 2015-06-19 Simon J. Murphy , Timothy R. Bedding , Hiromoto Shibahashi , Donald W. Kurtz , Hans Kjeldsen

Fitting a theoretical model to experimental data in a Bayesian manner using Markov chain Monte Carlo typically requires one to evaluate the model thousands (or millions) of times. When the model is a slow-to-compute physics simulation,…

Machine Learning · Statistics 2022-08-25 Steven Stetzler , Michael Grosskopf , Earl Lawrence

Hundreds of substellar companions to solar-type stars will be discovered with the Kepler satellite. Kepler's extreme photometric precision gives access to low-amplitude stellar variability contributed by a variety of physical processes. We…

Astrophysics · Physics 2011-02-07 Eric Pfahl , Phil Arras , Bill Paxton

In $\gamma$ Doradus stars, the g-mode period spacing shows an approximately linear relation with period. The slope is a new asteroseismic diagnostic, related to the rotation rate and the azimuthal order $m$. We report two automated methods,…

Solar and Stellar Astrophysics · Physics 2018-10-17 Gang Li , Timothy R. Bedding , Simon J. Murphy , Timothy Van Reeth , Victoria Antoci , Rhita-Maria Ouazzani

Abstract abridged. Eclipsing binary systems provide the opportunity to measure the fundamental parameters of their component stars in a stellar-model-independent way. This makes them ideal candidates for testing and calibrating theories of…

Instrumentation and Methods for Astrophysics · Physics 2024-02-12 Luc W. IJspeert , Andrew Tkachenko , Cole Johnston , Andrej Prša , Mark A. Wells , Conny Aerts