{"id":16131,"date":"2021-11-25T16:00:26","date_gmt":"2021-11-25T16:00:26","guid":{"rendered":"https:\/\/www.innovationnewsnetwork.com\/?p=16131"},"modified":"2024-09-04T21:07:37","modified_gmt":"2024-09-04T20:07:37","slug":"ucla-astronomers-discover-over-300-possible-new-exoplanets","status":"publish","type":"post","link":"https:\/\/www.innovationnewsnetwork.com\/ucla-astronomers-discover-over-300-possible-new-exoplanets\/16131\/","title":{"rendered":"UCLA astronomers discover over 300 possible new exoplanets"},"content":{"rendered":"
Astronomers from the UCLA<\/a> have identified 366 new exoplanets, largely due to an algorithm developed by a UCLA postdoctoral scholar.<\/p>\n Among their most noteworthy findings is a planetary system that encompasses a star and at least two gas giant planets, each approximately the size of Saturn and are unusually located close to one another.<\/p>\n These discoveries are outlined in a paper published 24 November in the Astronomical Journal<\/em>.<\/p>\n The term \u201cexoplanets\u201d is used to describe planets situated outside of our own solar system. The number of exoplanets that have been identified by astronomers\u2019 is less than 5,000, meaning the identification of hundreds of new ones is a very significant advance. Researching such a large group of exoplanets could help scientists better understand how other planets form and how their orbits evolve. It could also provide new insights into how unusual our solar system is.<\/p>\n \u201cDiscovering hundreds of new exoplanets is a significant accomplishment by itself, but what sets this work apart is how it will illuminate features of the exoplanet population as a whole,\u201d said Erik Petigura, a UCLA astronomy professor and co-author of the research.<\/p>\n The paper\u2019s lead author, Jon Zink, received his doctorate from UCLA in June and is currently a UCLA postdoctoral scholar. He and Petigura, as well as an international team of astronomers under the mission\u2019s name Scaling K2 project<\/em>, identified the exoplanets using data from the NASA Kepler Space Telescope\u2019s K2 mission.<\/p>\n The discovery was achieved through a new planet detection algorithm that was developed by Zink. One challenge with identifying new planets is that reductions in stellar brightness may originate from the instrument or from an alternative astrophysical source that mimics a planetary signature. Deciphering which ones are which requires extra investigation, which traditionally has been extremely time consuming and only possible through visual inspection. Zink\u2019s algorithm however is able to separate which signals indicate planets and which are merely noise.<\/p>\n \u201cThe catalogue and planet detection algorithm that Jon and the Scaling K2 team came devised is a major breakthrough in understanding the population of planets,\u201d explained Petigura. \u201cI have no doubt they will sharpen our understanding of the physical processes by which planets form and evolve.\u201d<\/p>\n Kepler\u2019s original mission came to an unexpected halt in 2013 when a mechanical failure left the spacecraft unable to remain pointed at the same precise location in the sky that it had been observing for years.<\/p>\n However, astronomers repurposed the telescope for a new mission\u00a0known as K2,\u00a0whose objective is to detect exoplanets located near distant stars. The data produced from K2 is helping scientists to better understand how stars\u2019 location in the galaxy influences what kind of planets are able to form around them. Unfortunately, the software utilised by the original Kepler mission to identify possible planets was unable to handle the complexities of the K2 mission. This included the inability to determine the planets\u2019 size and their location relative to their star.<\/p>\n Previous work by Zink and collaborators introduced the first fully automated pipeline for K2, with software to discover likely planets in the processed data. For the new study, the researchers used the new software to analyse the entire dataset from K2. This encompassed about 500 terabytes of data comprising of more than 800 million images of stars, used in order to create a \u201ccatalogue\u201d that will soon be incorporated into NASA\u2019s master exoplanet archive. The researchers used UCLA\u2019s\u00a0Hoffman2 Cluster<\/a>\u00a0to process the data. In addition to the 366 new exoplanets the researchers identified, the catalogue lists another 381 planets that had been previously identified.<\/p>\n Zink expressed that the findings could be a significant step toward in helping astronomers to better understand which types of stars are most likely to have planets orbiting them, and what that indicates about what is required for successful planet formation. \u201cWe need to look at a wide range of stars, not just ones like our sun, to understand that\u201d he added.<\/p>\n The discovery of the planetary system with two gas giant planets is also significant due to the rarity of discovering gas giants, such as Saturn in our own solar system, as close to their host star as they were in this case. The researchers are not yet able to explain why it occurred there, but Zink said that makes the finding especially useful as it could help scientists form a more accurate understanding of the parameters for how planets and planetary systems develop.<\/a><\/p>\n \u201cThe discovery of each new world provides a unique glimpse into the physics that play a role in planet formation,\u201d Zink expressed.<\/p>\n","protected":false},"excerpt":{"rendered":" Astronomers from the UCLA utilised an algorithm that enabled the discovery of over 300 exoplanets, as well as a distinctive planetary system with two gas giants. Astronomers from the UCLA have identified 366 new exoplanets, largely due to an algorithm developed by a UCLA postdoctoral scholar. Among their most noteworthy findings is a planetary system […]<\/p>\n","protected":false},"author":19,"featured_media":16133,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[24615],"tags":[570,17008,3477,809],"acf":[],"yoast_head":"\nNew exoplanet discovery<\/h3>\n
Planet detection algorithm<\/h3>\n
The significance of these discoveries<\/h3>\n