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UID:a8805929-57fc-4079-9dc0-2922df16c4c5@findlocal.community
DTSTAMP:20261026T233646Z
DTSTART;TZID=America/Detroit:20261026T150000
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SUMMARY:HEP-Astro Seminar | Cin-zs: an entry of the DESC Photo-z Data Cha
 llenge
DESCRIPTION:Accurate photometric redshifts are necessary for mapping the 
 three-dimensional structure of the universe\, allowing us to test models
  of cosmology and galaxy evolution. To prepare for the beginning of the 
 Vera C. Rubin Observatory's Legacy Survey of Space and Time\, the Dark E
 nergy Science Collaboration (DESC) launched a photometric redshift (phot
 o-z) estimation challenge in spring 2026. At that time\, all existing ph
 oto-z estimation methods had a redshift uncertainty larger than limits o
 utlined in the official DESC Science Requirements. In this talk\, I pres
 ent Cin-zs\, a machine learning-based approach for photo-z estimation su
 bmitted by our group as part of this challenge. I report on the performa
 nce of our algorithm when applied to Tasksets 1 and 2 and outline possib
 le avenues for improvement when extending to Tasksets 3 and 4.\n\nMore i
 nfo: https://events.umich.edu/event/153778\n\nhttps://findlocal.communit
 y/event/a8805929-57fc-4079-9dc0-2922df16c4c5
LOCATION:The University of Michigan\, Ann Arbor\, MI
URL:https://findlocal.community/event/a8805929-57fc-4079-9dc0-2922df16c4c
 5
STATUS:CONFIRMED
SEQUENCE:0
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