{"id":441711,"date":"2023-04-01T11:00:35","date_gmt":"2023-04-01T09:00:35","guid":{"rendered":"https:\/\/innovationorigins.com\/?post_type=selected&p=441711"},"modified":"2023-04-01T11:00:35","modified_gmt":"2023-04-01T09:00:35","slug":"machine-learning-supernova-nucleosynthesis","status":"publish","type":"selected","link":"https:\/\/ioplus.nl\/archive\/en\/selected\/machine-learning-supernova-nucleosynthesis\/","title":{"rendered":"Artificial intelligence finds the first stars were not alone"},"content":{"rendered":"\n

Using machine learning and state-of-the-art supernova nucleosynthesis, a team of researchers have found the majority of observed second-generation stars in the universe were enriched by multiple supernovae. The news was announced by the Kavli Institute for the Physics and Mathematics of the Universe (IPMU) in a press release<\/a>.<\/p>\n\n\n\n

Nuclear astrophysics research has shown elements including and heavier than carbon in the universe are produced in stars. But the first stars, stars born soon after the Big Bang, did not contain such heavy elements, which astronomers call \u2018metals\u2019. The next generation of stars contained only a small amount of heavy elements produced by the first stars. To understand the universe in its infancy, it requires researchers to study these metal-poor stars.<\/p>\n\n\n

<\/a>
<\/div><\/div>
Hubble discovers the brightest quasar in the early universe<\/div>
The NASA\/ESA Hubble Space Telescope discovered the brightest quasar ever seen in the early universe 12.8 billion light years from Earth. <\/div><\/div><\/div>\n\n\n

A new algorithm<\/h2>\n\n\n\n

Luckily, these second-generation metal-poor stars are observed in our Milky Way Galaxy, and have been studied to close in on the physical properties of the first stars in the universe.<\/p>\n\n\n\n

The study<\/a>, led by assistant professors Tilman Hartwig and Miho Ishigaki, professors Chiaki Kobayashi and Nozomu Tominaga and professor emeritus Ken\u2019ichi Nomoto, used artificial intelligence to analyze elemental abundances in more than 450 extremely metal-poor stars observed to date. Based on the newly developed supervised machine learning algorithm trained on theoretical supernova nucleosynthesis models, they found that 68 per cent of the observed extremely metal-poor stars have a chemical fingerprint consistent with enrichment by multiple previous supernovae.<\/p>\n\n\n\n

\u201cOur new algorithm provides an excellent tool to interpret the big data we will have in the next decade from on-going and future astronomical surveys across the world\u201d said Kobayashi.<\/p>\n\n\n\n

Promising results <\/h2>\n\n\n\n

The team\u2019s results give the first quantitative constraint based on observations on the multiplicity of the first stars.<\/p>\n\n\n\n

\u201cMultiplicity of the first stars were only predicted from numerical simulations so far, and there was no way to observationally examine the theoretical prediction until now\u201d, said lead author Hartwig. \u201cOur result suggests that most first stars formed in small clusters so that multiple of their supernovae can contribute to the metal enrichment of the early interstellar medium,\u201d he said.<\/p>\n\n\n

<\/a>
<\/div><\/div>
Flying observatory SOFIA uncovers oldest molecule in the universe<\/div>
What happened in our universe immediately after the Big Bang and how did life develop over the course of time? These are questions that people have been trying to solve for ages. Therefore, the first chemical compound since the Big Bang was the object of years of search.<\/div><\/div><\/div>\n\n\n

“The stars were not born alone”<\/h2>\n\n\n\n

\u201cAt the moment, the available data of old stars are the tip of the iceberg within the solar neighborhood. The Prime Focus Spectrograph, a cutting-edge multi-object spectrograph on the Subaru Telescope developed by the international collaboration led by Kavli IPMU, is the best instrument to discover ancient stars in the outer regions of the Milky Way far beyond the solar neighborhood,” said Ishigaki.<\/p>\n\n\n\n

In turn, Kobayashi added: \u201cThe theory of the first stars tells us that the first stars should be more massive than the Sun. The natural expectation was that the first star was born in a gas cloud containing the mass million times more than the Sun. However, our new finding strongly suggests that the first stars were not born alone, but instead formed as a part of a star cluster or a binary or multiple star system. This also means that we can expect gravitational waves from the first binary stars soon after the Big Bang, which could be detected future missions in space or on the Moon”.<\/p>\n","protected":false},"author":2583,"featured_media":507412,"template":"views\/single-selected.blade.php","meta":{"_acf_changed":false,"advgb_blocks_editor_width":"","advgb_blocks_columns_visual_guide":""},"categories":[76370,42],"tags":[25811,66576,130004,130006,34265],"location":[66582],"internal_archives":[],"class_list":["post-441711","selected","type-selected","status-publish","has-post-thumbnail","hentry","category-science","category-sustainability-nl","tag-astronomy","tag-cosmos","tag-kavli-institute","tag-machine-learning-11","tag-stars","location-europe"],"blocksy_meta":[],"acf":[],"featured_img":"https:\/\/ioplus.nl\/archive\/wp-content\/uploads\/2019\/01\/heic1902a.jpg","coauthors":[],"author_meta":{"author_link":"https:\/\/ioplus.nl\/archive\/author\/francesco-morelli\/","display_name":"Francesco Morelli"},"relative_dates":{"created":"Posted 3 years ago","modified":"Updated 3 years ago"},"absolute_dates":{"created":"Posted on April 1, 2023","modified":"Updated on April 1, 2023"},"absolute_dates_time":{"created":"Posted on April 1, 2023 11:00 am","modified":"Updated on April 1, 2023 11:00 am"},"featured_img_caption":"","tax_additional":{"category":{"linked":["Science<\/a>","Sustainability<\/a>"],"unlinked":["Science<\/span>","Sustainability<\/span>"],"slug":"category","name":"Categories"},"post_tag":{"linked":["astronomy<\/a>","cosmos<\/a>","Kavli Institute<\/a>","Machine Learning<\/a>","stars<\/a>"],"unlinked":["astronomy<\/span>","cosmos<\/span>","Kavli Institute<\/span>","Machine Learning<\/span>","stars<\/span>"],"slug":"post_tag","name":"Tags"},"language":{"linked":["EN<\/a>"],"unlinked":["EN<\/span>"],"slug":"language","name":"Tags"},"post_translations":{"linked":["pll_6423fb3990048<\/a>"],"unlinked":["pll_6423fb3990048<\/span>"],"slug":"post_translations","name":""},"location":{"linked":["Europe<\/a>"],"unlinked":["Europe<\/span>"],"slug":"location","name":"Locations"},"internal_archives":{"linked":[],"unlinked":[],"slug":"internal_archives","name":"Internal Archives"}},"series_order":"","_links":{"self":[{"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/selected\/441711","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/selected"}],"about":[{"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/types\/selected"}],"author":[{"embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/users\/2583"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/media\/507412"}],"wp:attachment":[{"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/media?parent=441711"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/categories?post=441711"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/tags?post=441711"},{"taxonomy":"location","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/location?post=441711"},{"taxonomy":"internal_archives","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/internal_archives?post=441711"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}