[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117121-en":3,"doc-seo-117121-105":29,"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":11,"language":21,"language_code":22,"site_id":23,"html_lang":22,"table_of_contents":24,"faqs":25,"seo_title":26,"seo_description":14,"update_tm":27,"read_time":28},117121,549758252649,"Ivy","https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819",8,"Research & Report","Machine Learning Applications in Astrophysics - Photometric Redshift Estimation","Machine learning has become a key research tool, expanding from early adoption in the astrophysics community to widespread use across many sub-fields, fueled by the availability of large, openly accessible astronomical datasets. This review focuses on estimating photometric redshifts of galaxies and quasars, outlining the background and scientific significance of redshift inference. It summarizes how machine learning has improved photometric redshift estimation methods over the past two decades and highlights recent Malaysia-based examples to support the feasibility of contributions from developing research communities.","arXiv :2312 .09813v1 [ astro-ph .IM] 15 Dec 2023  \nMachine Learning Applications in Astrophysics: Photometric  \nRedshift Estimation  \nJohn Y. H. Soo, a) Ishaq Yahya Khalfan Al Shuaili, and Imdad Mahmud Pathi  \nSchool of Physics, Universiti Sains Malaysia, 11800 USM, Pulau Pinang, Malaysia.  \na) [Corresponding author: johnsooyh@usm.my](Corresponding author: johnsooyh@usm.my)  \nAbstract. Machine learning has rose to become an important research tool in the past decade, its application has been expanded to almost if not all disciplines known to mankind. Particularly, the use of machine learning in astrophysics research had a humble beginning in the early 1980s, it has rose and become widely used in many sub-fields today, driven by the vast availability of free astronomical data online. In this short review, we narrow our discussion to a single topic in astrophysics – the estimation of photometric redshifts of galaxies and quasars, where we discuss its background, significance, and how machine learning has been used to improve its estimation methods in the past 20 years. We also show examples of some recent machine learning photometric redshift work done in Malaysia, affirming that machine learning is a viable and easy way a developing nation can contribute towards general research in astronomy and astrophysics.  \nINTRODUCTION  \nThe words ’artificial intelligence’ and ’machine learning’ have been the buzzword of the past decade, industries and governmental policies have been revolving around the development of tools related to them. While artificial intelligence is the attempt to create machines with human-like cognitive functions to think and solve problems, machine learning is merely a subset of it: it is a framework where machines can learn from data and find patterns between inputs and outputs provided and guided by humans. Machine learning has been used to solve various complex classification, regression, clustering, object detection and segmentation problems, speeding up processes which the limited human brain can do.  \nThe viability of machine learning really depends on the availability of data: the more data one has, the better a machine will be able to learn. In the last century, astrophysics research has moved progressively from being theorydriven, observation-driven, and now data-driven [1] . Currently with the existence of many large astronomical sky surveys, satellites and telescopes, astronomy has generated plenty of stellar and galaxy data, most of which has been processed and analysed, and remain openly accessible to the world. An example being the Strasbourg Astronomical Data Centre (CDS), which hosts the SIMBAD and VIZIER astronomical databases, providing physical data of millions of nearby stars and galaxies, as well as more than 21 000 deep-sky object catalogues [2, 3] . Not to mention upcoming large sky surveys, like the Legacy Survey of Space and Time (LSST) and the Square Kilometre Array (SKA), which would provide us with data of unprecedented volume and quality, requiring state-of-the-art data storage and analysis peripheral to handle them [4, 5] .  \nMachine learning applications in astrophysics have been present since the late 1980s, as shown in Fig. 1. The first instance where the word ’neural network’was used in an astronomy-related refereed journal paper was in 1986, when neural networks and simulated annealing where compared as optimisation methods for remote sensing data [6] . Areview paper was later written in 1993 [7], suggesting that machine learning could be applied in telescopic adaptive optics, object classification and object detection.  \nDuring the 1990s, several prominent uses of machine learning in astrophysics include galaxy morphology classification [8], star-galaxy separation [9], and stellar spectral classification [10] . Since then, the number of astronomy journal papers with keywords ’neural network’ and ’machine learning’ in their abstracts has increased, moving on an exponential tren","cbCaiuQDX8LBrloP","https://ap.wps.com/l/cbCaiuQDX8LBrloP","pdf",1212815,1,"English","en",105,"# Introduction\n# Photometric Redshifts","[{\"question\":\"Why is machine learning considered important in astrophysics research?\",\"answer\":\"Machine learning helps model complex classification and regression tasks and its effectiveness grows with larger available datasets. The expansion of open astronomical data and improved computation has accelerated its adoption across astrophysics sub-fields.\"},{\"question\":\"What does the review focus on regarding redshifts?\",\"answer\":\"The review concentrates on estimating photometric redshifts of galaxies and quasars. It covers the background and significance of photometric redshifts and how machine learning has been used to improve estimation methods in the last 20 years.\"},{\"question\":\"How are photometric redshifts related to determining galaxy distance?\",\"answer\":\"Redshift serves as a proxy for distance because cosmological redshifts arise from the expansion of space and shift the observed spectra. Higher redshift corresponds to greater distance from the observer.\"}]","Machine Learning Applications in Astrophysics - Photometric Redshift Estimation | PDF",1785674003,20,{"code":4,"msg":30,"data":31},"ok",{"site_id":23,"language":22,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":27},"machine-learning-applications-in-astrophysics-photometric-redshift-estimation","",{"@graph":35,"@context":84},[36,53,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/machine-learning-applications-in-astrophysics-photometric-redshift-estimation/117121/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":22,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-08-02",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},"Why is machine learning considered important in astrophysics research?","Question",{"text":74,"@type":75},"Machine learning helps model complex classification and regression tasks and its effectiveness grows with larger available datasets. The expansion of open astronomical data and improved computation has accelerated its adoption across astrophysics sub-fields.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"What does the review focus on regarding redshifts?",{"text":79,"@type":75},"The review concentrates on estimating photometric redshifts of galaxies and quasars. It covers the background and significance of photometric redshifts and how machine learning has been used to improve estimation methods in the last 20 years.",{"name":81,"@type":72,"acceptedAnswer":82},"How are photometric redshifts related to determining galaxy distance?",{"text":83,"@type":75},"Redshift serves as a proxy for distance because cosmological redshifts arise from the expansion of space and shift the observed spectra. Higher redshift corresponds to greater distance from the observer.","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":23},{"code":4,"msg":5,"data":91},[92,96,100,104,109,114,119,122,126,129,133],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":93,"show_sort_weight":94,"slug":95},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":97,"show_sort_weight":98,"slug":99},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":45,"category_name":101,"show_sort_weight":102,"slug":103},"Exam",70,"exam",{"id":105,"doc_module":4,"doc_module_name":45,"category_name":106,"show_sort_weight":107,"slug":108},5,"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":45,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":45,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":45,"category_name":124,"show_sort_weight":28,"slug":125},9,"Religion & Spirituality","religion-spirituality",{"id":28,"doc_module":4,"doc_module_name":45,"category_name":127,"show_sort_weight":28,"slug":128},"World Cup","world-cup",{"id":130,"doc_module":4,"doc_module_name":45,"category_name":131,"show_sort_weight":130,"slug":132},10,"Lifestyle","lifestyle",{"id":134,"doc_module":4,"doc_module_name":45,"category_name":135,"show_sort_weight":105,"slug":136},19,"General","general"]