{"title":"利用深度学习推断红巨星混合模振荡的耦合强度","authors":"Siddharth Dhanpal, Othman Benomar, Shravan Hanasoge, Masao Takata, Subrata Kumar Panda, Abhisek Kundu","doi":"10.3847/1538-4357/ad0046","DOIUrl":null,"url":null,"abstract":"Abstract Asteroseismology is a powerful tool that may be applied to shed light on stellar interiors and stellar evolution. Mixed modes, behaving like acoustic waves in the envelope and buoyancy modes in the core, are remarkable because they allow for probing the radiative cores and evanescent zones of red giant stars. Here, we have developed a neural network that can accurately infer the coupling strength, a parameter related to the size of the evanescent zone, of solar-like stars in ∼5 ms. In comparison with existing methods, we found that only ∼43% of inferences were in agreement with a difference less than 0.03 in a sample of ∼1700 Kepler red giants. To understand the origin of these differences, we analyzed a few of these stars using independent techniques such as the Monte Carlo Markov Chain method and echelle diagrams. Through our analysis, we discovered that these alternate techniques are supportive of the neural-net inferences. We also demonstrate that the network can be used to yield estimates of coupling strength and period spacing in stars with structural discontinuities. Our findings suggest that the rate of decline in the coupling strength in the red giant branch is greater than previously believed. These results are in closer agreement with calculations of stellar-evolution models than prior estimates, further underscoring the remarkable success of stellar evolution theory and computation. Additionally, we show that the uncertainty in measuring period spacing increases rapidly with diminishing coupling strength.","PeriodicalId":50735,"journal":{"name":"Astrophysical Journal","volume":null,"pages":null},"PeriodicalIF":4.8000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Inferring Coupling Strengths of Mixed-mode Oscillations in Red Giant Stars Using Deep Learning\",\"authors\":\"Siddharth Dhanpal, Othman Benomar, Shravan Hanasoge, Masao Takata, Subrata Kumar Panda, Abhisek Kundu\",\"doi\":\"10.3847/1538-4357/ad0046\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Asteroseismology is a powerful tool that may be applied to shed light on stellar interiors and stellar evolution. Mixed modes, behaving like acoustic waves in the envelope and buoyancy modes in the core, are remarkable because they allow for probing the radiative cores and evanescent zones of red giant stars. Here, we have developed a neural network that can accurately infer the coupling strength, a parameter related to the size of the evanescent zone, of solar-like stars in ∼5 ms. In comparison with existing methods, we found that only ∼43% of inferences were in agreement with a difference less than 0.03 in a sample of ∼1700 Kepler red giants. To understand the origin of these differences, we analyzed a few of these stars using independent techniques such as the Monte Carlo Markov Chain method and echelle diagrams. Through our analysis, we discovered that these alternate techniques are supportive of the neural-net inferences. We also demonstrate that the network can be used to yield estimates of coupling strength and period spacing in stars with structural discontinuities. Our findings suggest that the rate of decline in the coupling strength in the red giant branch is greater than previously believed. These results are in closer agreement with calculations of stellar-evolution models than prior estimates, further underscoring the remarkable success of stellar evolution theory and computation. Additionally, we show that the uncertainty in measuring period spacing increases rapidly with diminishing coupling strength.\",\"PeriodicalId\":50735,\"journal\":{\"name\":\"Astrophysical Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2023-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Astrophysical Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3847/1538-4357/ad0046\",\"RegionNum\":2,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ASTRONOMY & ASTROPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Astrophysical Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3847/1538-4357/ad0046","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ASTRONOMY & ASTROPHYSICS","Score":null,"Total":0}
Inferring Coupling Strengths of Mixed-mode Oscillations in Red Giant Stars Using Deep Learning
Abstract Asteroseismology is a powerful tool that may be applied to shed light on stellar interiors and stellar evolution. Mixed modes, behaving like acoustic waves in the envelope and buoyancy modes in the core, are remarkable because they allow for probing the radiative cores and evanescent zones of red giant stars. Here, we have developed a neural network that can accurately infer the coupling strength, a parameter related to the size of the evanescent zone, of solar-like stars in ∼5 ms. In comparison with existing methods, we found that only ∼43% of inferences were in agreement with a difference less than 0.03 in a sample of ∼1700 Kepler red giants. To understand the origin of these differences, we analyzed a few of these stars using independent techniques such as the Monte Carlo Markov Chain method and echelle diagrams. Through our analysis, we discovered that these alternate techniques are supportive of the neural-net inferences. We also demonstrate that the network can be used to yield estimates of coupling strength and period spacing in stars with structural discontinuities. Our findings suggest that the rate of decline in the coupling strength in the red giant branch is greater than previously believed. These results are in closer agreement with calculations of stellar-evolution models than prior estimates, further underscoring the remarkable success of stellar evolution theory and computation. Additionally, we show that the uncertainty in measuring period spacing increases rapidly with diminishing coupling strength.
期刊介绍:
The Astrophysical Journal is the foremost research journal in the world devoted to recent developments, discoveries, and theories in astronomy and astrophysics.