{"title":"Cover Picture: Astron. Nachr. 9/2024","authors":"Balázs Pál, László Dobos","doi":"10.1002/asna.20249017","DOIUrl":null,"url":null,"abstract":"<p>Denoising a medium resolution stellar spectrum with neural networks. <i>Top</i>: Example of a noiseless simulated stellar spectrum (blue) transformed to an “observation” by adding a realistic noise component (gray) such that the effective S/N≈19. <i>Middle</i>: Comparison of the original noiseless simulated spectrum (blue) and the reconstructed spectrum (dashed orange) using a trained denoising autoencoder. The two lines overlap almost entirely, indicating the high accuracy of the machine learning method. <i>Bottom</i>: Relative error calculated as the fraction of pixel-wise residual noise and the original noiseless flux. The mean and maximum of the relative error are 0.175% and 1.806%, respectively. Formore details see the related paper by Pál and Dobos, published in this issue e240049. \n <figure>\n <div><picture>\n <source></source></picture><p></p>\n </div>\n </figure></p>","PeriodicalId":55442,"journal":{"name":"Astronomische Nachrichten","volume":"345 9-10","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asna.20249017","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Astronomische Nachrichten","FirstCategoryId":"101","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/asna.20249017","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ASTRONOMY & ASTROPHYSICS","Score":null,"Total":0}
引用次数: 0
Abstract
Denoising a medium resolution stellar spectrum with neural networks. Top: Example of a noiseless simulated stellar spectrum (blue) transformed to an “observation” by adding a realistic noise component (gray) such that the effective S/N≈19. Middle: Comparison of the original noiseless simulated spectrum (blue) and the reconstructed spectrum (dashed orange) using a trained denoising autoencoder. The two lines overlap almost entirely, indicating the high accuracy of the machine learning method. Bottom: Relative error calculated as the fraction of pixel-wise residual noise and the original noiseless flux. The mean and maximum of the relative error are 0.175% and 1.806%, respectively. Formore details see the related paper by Pál and Dobos, published in this issue e240049.
期刊介绍：
Astronomische Nachrichten, founded in 1821 by H. C. Schumacher, is the oldest astronomical journal worldwide still being published. Famous astronomical discoveries and important papers on astronomy and astrophysics published in more than 300 volumes of the journal give an outstanding representation of the progress of astronomical research over the last 180 years. Today, Astronomical Notes/ Astronomische Nachrichten publishes articles in the field of observational and theoretical astrophysics and related topics in solar-system and solar physics. Additional, papers on astronomical instrumentation ground-based and space-based as well as papers about numerical astrophysical techniques and supercomputer modelling are covered. Papers can be completed by short video sequences in the electronic version. Astronomical Notes/ Astronomische Nachrichten also publishes special issues of meeting proceedings.
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