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Mode classification in fast-rotating stars using a convolutional neural network: model-based regular patterns in δ Scuti stars

Mirouh, Giovanni M, Angelou, George C, Reese, Daniel R and Costa, Guglielmo (2018) Mode classification in fast-rotating stars using a convolutional neural network: model-based regular patterns in δ Scuti stars Monthly Notices of the Royal Astronomical Society: Letters, 483 (1). L28-L32.

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Abstract

Oscillation modes in fast-rotating stars can be split into several subclasses, each with their own properties. To date, seismology of these stars cannot rely on regular pattern analysis and scaling relations. However, recently there has been the promising discovery of large separations observed in spectra of fast-rotating δ Scuti stars; they were attributed to the island-mode subclass, and linked to the stellar mean density through a scaling law. In this work, we investigate the relevance of this scaling relation by computing models of fast-rotating stars and their oscillation spectra. In order to sort the thousands of oscillation modes thus obtained, we train a convolutional neural network isolating the island modes with 96 per cent accuracy. Arguing that the observed large separation is systematically smaller than the asymptotic one, we retrieve the observational Δν--ρ¯¯¯ scaling law. This relation will be used to drive forward modelling efforts, and is a first step towards mode identification and inversions for fast-rotating stars.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Physics
Authors :
NameEmailORCID
Mirouh, Giovanni Mg.mirouh@surrey.ac.uk
Angelou, George C
Reese, Daniel R
Costa, Guglielmo
Date : 13 November 2018
DOI : 10.1093/mnrasl/sly212
Copyright Disclaimer : © 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) This is a pre-copyedited, author-produced PDF of an article accepted for publication in Monthly Notices of the Royal Astronomical Society following peer review. The version of record - Giovanni M Mirouh, George C Angelou, Daniel R Reese, Guglielmo Costa; Mode classification in fast-rotating stars using a convolutional neural network: model-based regular patterns in δ Scuti stars, Monthly Notices of the Royal Astronomical Society: Letters, Volume 483, Issue 1, 11 February 2019, Pages L28–L32 - is available online at: https://doi.org/10.1093/mnrasl/sly212
Uncontrolled Keywords : Stars: oscillations. Stars: rotation. Stars: variables: Scuti.
Depositing User : Clive Harris
Date Deposited : 11 Mar 2019 14:10
Last Modified : 08 Oct 2019 09:27
URI: http://epubs.surrey.ac.uk/id/eprint/850709

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