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BEGIN:VEVENT
DTSTART;TZID=Atlantic/Canary:20210916T140000
DTEND;TZID=Atlantic/Canary:20210916T150000
UID:iactalks-1499
X-WR-CALNAME: IAC Talks: Open Astronomy Seminars
X-ORIGINAL-URL: /iactalks/Talks/view/1499
CREATED:2021-09-16T14:00:00+01:00
X-WR-CALDESC: IAC Talks upcomming talks
SUMMARY:Application of simulation-based inference to problems in astrophysi
 cs
DESCRIPTION:Application of simulation-based inference to problems in astrop
 hysics\nDr. Siddharth Mishra-Sharme\n\nThe next decade will see a deluge o
 f new cosmological data that will enable us to accurately map out the dist
 ribution of matter in the local Universe, image billions of star
 s and galaxies to unprecedented precision, and create high-resolution maps
  of the Milky Way. Signatures of new physics as well as astrophysical proc
 esses of interest may be hiding in these observations, offering significan
 t discovery potential. At the same time, the complexity of astrophysical d
 ata provides significant challenges to carrying out these searches using c
 onventional methods. I will describe how overcoming these issues will requ
 ire a qualitative shift in how we approach modeling and inference in cosmo
 logy, bringing together several recent advances in machine learning and si
 mulation-based (or likelihood-free) inference. I will ground the talk thro
 ugh examples of proposed analyses that use machine learning-enabled simula
 tion-based inference with an aim to uncover the identity of dark matter, w
 hile at the same time emphasizing the generality of these techniques to a 
 broad range of problems in astrophysics, cosmology, and beyond.\n&nbs
 p;\nhttps://rediris.zoom.us/j/83193959785?pwd=TExXSDJ6UDg5a24yWDM1TnlOWkNT
 Zz09\nMeeting ID: 831 9395 9785Passcode: 343950O\nYouTube: https://yo
 utu.be/1Nkzn-cGaIo
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