Detection of Contact Binary Candidates Observed By TESS Using the Autoencoder Neural Network

A contact binary may be the progenitor of a red nova that eventually produces a merger event and have a cut-off period of around 0.2 days. Therefore, a large number of contact binaries is needed to search for the progenitor of red novae and to study the characteristics of short-period contact binari...
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Autor*in:	Xu Ding [verfasserIn] ZhiMing Song [verfasserIn] ChuanJun Wang [verfasserIn] KaiFan Ji [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	Binary stars Eclipsing binary stars Contact binary stars

Übergeordnetes Werk:	In: The Astronomical Journal - IOP Publishing, 2022, 167(2024), 5, p 192
Übergeordnetes Werk:	volume:167 ; year:2024 ; number:5, p 192

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3847/1538-3881/ad3048

Katalog-ID:	DOAJ098678493

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spelling	10.3847/1538-3881/ad3048 doi (DE-627)DOAJ098678493 (DE-599)DOAJ2e867f3b0a8d465b9ea44a103b51aec7 DE-627 ger DE-627 rakwb eng QB1-991 Xu Ding verfasserin aut Detection of Contact Binary Candidates Observed By TESS Using the Autoencoder Neural Network 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A contact binary may be the progenitor of a red nova that eventually produces a merger event and have a cut-off period of around 0.2 days. Therefore, a large number of contact binaries is needed to search for the progenitor of red novae and to study the characteristics of short-period contact binaries. In this paper, we employ the Phoebe program to generate a large number of light curves based on the fundamental parameters of contact binaries. Using these light curves as samples, an autoencoder model is trained, which can reconstruct the light curves of contact binaries very well. When the error between the output light curve from the model and the input light curve is large, it may be due to other types of variable stars. The goodness of fit ( R ^2 ) between the output light curve from the model and the input light curve is calculated. Based on the thresholds for global goodness of fit ( R ^2 ), period, range magnitude, and local goodness of fit ( R ^2 ), a total of 1322 target candidates were obtained. Binary stars Eclipsing binary stars Contact binary stars Astronomy ZhiMing Song verfasserin aut ChuanJun Wang verfasserin aut KaiFan Ji verfasserin aut In The Astronomical Journal IOP Publishing, 2022 167(2024), 5, p 192 (DE-627)312175647 (DE-600)2003104-X 15383881 nnns volume:167 year:2024 number:5, p 192 https://doi.org/10.3847/1538-3881/ad3048 kostenfrei https://doaj.org/article/2e867f3b0a8d465b9ea44a103b51aec7 kostenfrei https://doi.org/10.3847/1538-3881/ad3048 kostenfrei https://doaj.org/toc/1538-3881 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2006 GBV_ILN_2014 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2129 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 167 2024 5, p 192
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allfieldsGer	10.3847/1538-3881/ad3048 doi (DE-627)DOAJ098678493 (DE-599)DOAJ2e867f3b0a8d465b9ea44a103b51aec7 DE-627 ger DE-627 rakwb eng QB1-991 Xu Ding verfasserin aut Detection of Contact Binary Candidates Observed By TESS Using the Autoencoder Neural Network 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A contact binary may be the progenitor of a red nova that eventually produces a merger event and have a cut-off period of around 0.2 days. Therefore, a large number of contact binaries is needed to search for the progenitor of red novae and to study the characteristics of short-period contact binaries. In this paper, we employ the Phoebe program to generate a large number of light curves based on the fundamental parameters of contact binaries. Using these light curves as samples, an autoencoder model is trained, which can reconstruct the light curves of contact binaries very well. When the error between the output light curve from the model and the input light curve is large, it may be due to other types of variable stars. The goodness of fit ( R ^2 ) between the output light curve from the model and the input light curve is calculated. Based on the thresholds for global goodness of fit ( R ^2 ), period, range magnitude, and local goodness of fit ( R ^2 ), a total of 1322 target candidates were obtained. Binary stars Eclipsing binary stars Contact binary stars Astronomy ZhiMing Song verfasserin aut ChuanJun Wang verfasserin aut KaiFan Ji verfasserin aut In The Astronomical Journal IOP Publishing, 2022 167(2024), 5, p 192 (DE-627)312175647 (DE-600)2003104-X 15383881 nnns volume:167 year:2024 number:5, p 192 https://doi.org/10.3847/1538-3881/ad3048 kostenfrei https://doaj.org/article/2e867f3b0a8d465b9ea44a103b51aec7 kostenfrei https://doi.org/10.3847/1538-3881/ad3048 kostenfrei https://doaj.org/toc/1538-3881 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2006 GBV_ILN_2014 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2129 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 167 2024 5, p 192
allfieldsSound	10.3847/1538-3881/ad3048 doi (DE-627)DOAJ098678493 (DE-599)DOAJ2e867f3b0a8d465b9ea44a103b51aec7 DE-627 ger DE-627 rakwb eng QB1-991 Xu Ding verfasserin aut Detection of Contact Binary Candidates Observed By TESS Using the Autoencoder Neural Network 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A contact binary may be the progenitor of a red nova that eventually produces a merger event and have a cut-off period of around 0.2 days. Therefore, a large number of contact binaries is needed to search for the progenitor of red novae and to study the characteristics of short-period contact binaries. In this paper, we employ the Phoebe program to generate a large number of light curves based on the fundamental parameters of contact binaries. Using these light curves as samples, an autoencoder model is trained, which can reconstruct the light curves of contact binaries very well. When the error between the output light curve from the model and the input light curve is large, it may be due to other types of variable stars. The goodness of fit ( R ^2 ) between the output light curve from the model and the input light curve is calculated. Based on the thresholds for global goodness of fit ( R ^2 ), period, range magnitude, and local goodness of fit ( R ^2 ), a total of 1322 target candidates were obtained. Binary stars Eclipsing binary stars Contact binary stars Astronomy ZhiMing Song verfasserin aut ChuanJun Wang verfasserin aut KaiFan Ji verfasserin aut In The Astronomical Journal IOP Publishing, 2022 167(2024), 5, p 192 (DE-627)312175647 (DE-600)2003104-X 15383881 nnns volume:167 year:2024 number:5, p 192 https://doi.org/10.3847/1538-3881/ad3048 kostenfrei https://doaj.org/article/2e867f3b0a8d465b9ea44a103b51aec7 kostenfrei https://doi.org/10.3847/1538-3881/ad3048 kostenfrei https://doaj.org/toc/1538-3881 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2006 GBV_ILN_2014 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2129 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 167 2024 5, p 192
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source	In The Astronomical Journal 167(2024), 5, p 192 volume:167 year:2024 number:5, p 192
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callnumber-first	Q - Science
author	Xu Ding
spellingShingle	Xu Ding misc QB1-991 misc Binary stars misc Eclipsing binary stars misc Contact binary stars misc Astronomy Detection of Contact Binary Candidates Observed By TESS Using the Autoencoder Neural Network
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topic_title	QB1-991 Detection of Contact Binary Candidates Observed By TESS Using the Autoencoder Neural Network Binary stars Eclipsing binary stars Contact binary stars
topic	misc QB1-991 misc Binary stars misc Eclipsing binary stars misc Contact binary stars misc Astronomy
topic_unstemmed	misc QB1-991 misc Binary stars misc Eclipsing binary stars misc Contact binary stars misc Astronomy
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title	Detection of Contact Binary Candidates Observed By TESS Using the Autoencoder Neural Network
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title_full	Detection of Contact Binary Candidates Observed By TESS Using the Autoencoder Neural Network
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title_sort	detection of contact binary candidates observed by tess using the autoencoder neural network
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title_auth	Detection of Contact Binary Candidates Observed By TESS Using the Autoencoder Neural Network
abstract	A contact binary may be the progenitor of a red nova that eventually produces a merger event and have a cut-off period of around 0.2 days. Therefore, a large number of contact binaries is needed to search for the progenitor of red novae and to study the characteristics of short-period contact binaries. In this paper, we employ the Phoebe program to generate a large number of light curves based on the fundamental parameters of contact binaries. Using these light curves as samples, an autoencoder model is trained, which can reconstruct the light curves of contact binaries very well. When the error between the output light curve from the model and the input light curve is large, it may be due to other types of variable stars. The goodness of fit ( R ^2 ) between the output light curve from the model and the input light curve is calculated. Based on the thresholds for global goodness of fit ( R ^2 ), period, range magnitude, and local goodness of fit ( R ^2 ), a total of 1322 target candidates were obtained.
abstractGer	A contact binary may be the progenitor of a red nova that eventually produces a merger event and have a cut-off period of around 0.2 days. Therefore, a large number of contact binaries is needed to search for the progenitor of red novae and to study the characteristics of short-period contact binaries. In this paper, we employ the Phoebe program to generate a large number of light curves based on the fundamental parameters of contact binaries. Using these light curves as samples, an autoencoder model is trained, which can reconstruct the light curves of contact binaries very well. When the error between the output light curve from the model and the input light curve is large, it may be due to other types of variable stars. The goodness of fit ( R ^2 ) between the output light curve from the model and the input light curve is calculated. Based on the thresholds for global goodness of fit ( R ^2 ), period, range magnitude, and local goodness of fit ( R ^2 ), a total of 1322 target candidates were obtained.
abstract_unstemmed	A contact binary may be the progenitor of a red nova that eventually produces a merger event and have a cut-off period of around 0.2 days. Therefore, a large number of contact binaries is needed to search for the progenitor of red novae and to study the characteristics of short-period contact binaries. In this paper, we employ the Phoebe program to generate a large number of light curves based on the fundamental parameters of contact binaries. Using these light curves as samples, an autoencoder model is trained, which can reconstruct the light curves of contact binaries very well. When the error between the output light curve from the model and the input light curve is large, it may be due to other types of variable stars. The goodness of fit ( R ^2 ) between the output light curve from the model and the input light curve is calculated. Based on the thresholds for global goodness of fit ( R ^2 ), period, range magnitude, and local goodness of fit ( R ^2 ), a total of 1322 target candidates were obtained.
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container_issue	5, p 192
title_short	Detection of Contact Binary Candidates Observed By TESS Using the Autoencoder Neural Network
url	https://doi.org/10.3847/1538-3881/ad3048 https://doaj.org/article/2e867f3b0a8d465b9ea44a103b51aec7 https://doaj.org/toc/1538-3881
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up_date	2024-07-03T18:35:09.913Z
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