[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120229-en":3,"doc-seo-120229-105":30,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},120229,7971461740886,"Theodore","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",8,"Research & Report","Enhancing Galaxy Surveys with Machine Learning - Applications of Machine Learning in Astrophysics","Machine learning and artificial intelligence are applied to astrophysics and cosmology to support galaxy surveys aimed at revealing the nature of cosmic acceleration and dark energy. The presentation updates two prior efforts: using graph neural networks to infer cosmological information beyond survey geometry by leveraging campus supercomputing, and improving galaxy target selection in the Subaru Prime Focus Spectrograph survey with reinforcement learning methods such as A2C and revised reward functions. Results show major gains in model speed and performance, especially for locating faint, high-redshift galaxies.","Apr 10th,2024-Apr 26th,20244:00 PM  \n# Enhancing Galaxy Surveys with Machine Learning\n\nSteven KarstMissouri University of Science and Technology  \nFollow this and additional works at:https://scholarsmine.mst.edu/ugrc  \nPart of the Computer Sciences Commons,and the Physics Commons  \nKarst,Steven,\"Enhancing Galaxy Surveys with Machine Learning\"(2024).Undergraduate ResearchConference at MissouriS&T.5.https://scholarsmine.mst.edu/ugrc/2024/oure/5  \nThis Presentation is brought to you for free and open access by Scholars'Mine.It has been accepted for inclusionin Undergraduate Research Conference at MissouriS&T by an authorized administrator of Scholars'Mine.Thiswork is protected by U.S.Copyright Law.Unauthorized use including reproduction for redistribution requires thepermission of the copyright holder.For more information,please contact scholarsmine@mst.edu.  \nSteven Karst  \nDepartment:  \nPhysics  \nPhysics &Computer Science  \nMajor:  \nResearch Advisor:  Dr.Shun Saito  \nAdvisor Department:Physics  \nFunding Source:   NSF  \nEnhancing Galaxy Surveys with Machine Learning  \nApplications of machine learning(ML)or artificial intelligence (Al)toproblems in astrophysics and cosmology have recently entered a goldenera.In response,we have updated two of our recent MLIAl efforts thatcontribute to galaxy surveys whose main scientific target is to reveal thenature of the Comsic Acceleration or Dark Energy.We first revised our effortto infer cosmological information beyond the survey geometry using GraphNeural Networks(GNNs)to take advantage of supercomputing resourceson campus.We then updated our methods for galaxy target selection in theSubaru Prime Focus Spectrograph(PFS)survey with modern reinforcementlearning techniques such as A2C and revised reward functions.In bothcases,we found that these changes dramatically improved the speed andperformance of the ML models,especially when locating faint galaxies withhigh redshifts.  \nSteven Karst is a senior from Ballwin,Missouri majoring in Physics and ComputerScience at Missouri S&T,where he is the Computing Lead for the Underwater RoboticsTeam as well as the vice president of ACM Game Dev.He was originally introduced tothe Institute for Multi-Messenger Astrophysics and Cosmology through the National MeritSemifinalist Package.His research for that program won first prize at the 2021Undergraduate Research Conference as well as at the 2021 Fuller Prize Competition.","cbCaiup46PN8IBo1","https://ap.wps.com/l/cbCaiup46PN8IBo1","pdf",493775,1,2,"English","en",105,"# Enhancing Galaxy Surveys with Machine Learning\n## Applying ML/AI to Astrophysics and Cosmology\n## Graph Neural Networks for Cosmological Inference\n## Reinforcement Learning for Galaxy Target Selection\n## Performance Gains for Faint High-Redshift Galaxies","[{\"question\":\"What scientific goal do the galaxy surveys target in this work?\",\"answer\":\"They aim to reveal the nature of cosmic acceleration, often associated with dark energy, by extracting cosmological information from survey observations.\"},{\"question\":\"How does the presentation use graph neural networks (GNNs)?\",\"answer\":\"It revises a method to infer cosmological information beyond the survey geometry, taking advantage of supercomputing resources.\"},{\"question\":\"Which reinforcement learning techniques are used for galaxy target selection?\",\"answer\":\"The methods include modern reinforcement learning techniques such as A2C, along with revised reward functions for the Subaru Prime Focus Spectrograph (PFS) survey.\"}]","Enhancing Galaxy Surveys with Machine Learning - Applications of Machine Learning in Astrophysics | PDF",1785728843,5,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":28},"enhancing-galaxy-surveys-with-machine-learning-applications-of-machine-learning-in-astrophysics","",{"@graph":36,"@context":84},[37,53,67],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,47,50],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":21},"https://docshare.wps.com/document/","Document",{"item":48,"name":12,"@type":43,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":43,"position":52},"https://docshare.wps.com/document/enhancing-galaxy-surveys-with-machine-learning-applications-of-machine-learning-in-astrophysics/120229/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"What scientific goal do the galaxy surveys target in this work?","Question",{"text":74,"@type":75},"They aim to reveal the nature of cosmic acceleration, often associated with dark energy, by extracting cosmological information from survey observations.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"How does the presentation use graph neural networks (GNNs)?",{"text":79,"@type":75},"It revises a method to infer cosmological information beyond the survey geometry, taking advantage of supercomputing resources.",{"name":81,"@type":72,"acceptedAnswer":82},"Which reinforcement learning techniques are used for galaxy target selection?",{"text":83,"@type":75},"The methods include modern reinforcement learning techniques such as A2C, along with revised reward functions for the Subaru Prime Focus Spectrograph (PFS) survey.","https://schema.org",{"og:url":51,"og:type":86,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":88,"canonical":51},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":91},[92,96,100,104,108,113,118,121,126,129,133],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":93,"show_sort_weight":94,"slug":95},"Story & Novel",90,"story-novel",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":97,"show_sort_weight":98,"slug":99},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":46,"category_name":101,"show_sort_weight":102,"slug":103},"Exam",70,"exam",{"id":29,"doc_module":4,"doc_module_name":46,"category_name":105,"show_sort_weight":106,"slug":107},"Comic",60,"comic",{"id":109,"doc_module":4,"doc_module_name":46,"category_name":110,"show_sort_weight":111,"slug":112},6,"Technology",50,"technology",{"id":114,"doc_module":4,"doc_module_name":46,"category_name":115,"show_sort_weight":116,"slug":117},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":119,"slug":120},30,"research-report",{"id":122,"doc_module":4,"doc_module_name":46,"category_name":123,"show_sort_weight":124,"slug":125},9,"Religion & Spirituality",20,"religion-spirituality",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":127,"show_sort_weight":124,"slug":128},"World Cup","world-cup",{"id":130,"doc_module":4,"doc_module_name":46,"category_name":131,"show_sort_weight":130,"slug":132},10,"Lifestyle","lifestyle",{"id":134,"doc_module":4,"doc_module_name":46,"category_name":135,"show_sort_weight":29,"slug":136},19,"General","general"]