BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//pretalx//pretalx.com//adass2023//talk//AZDQJY
BEGIN:VTIMEZONE
TZID:US/Arizona
BEGIN:STANDARD
DTSTART:20221106T000000
TZNAME:MST
TZOFFSETFROM:-0700
TZOFFSETTO:-0700
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
SUMMARY:Predicting the Radiation Field of Molecular Clouds using Denoising
  Diffusion Probabilistic Models - Duo Xu
DTSTART;TZID=US/Arizona:20231106T083000
DTEND;TZID=US/Arizona:20231106T083000
DTSTAMP:20260814T184828Z
UID:pretalx-adass2023-AZDQJY@pretalx.com
DESCRIPTION:Accurately quantifying the impact of radiation feedback in sta
 r formation is challenging. To address this complex problem\, we employ de
 ep learning techniques\, denoising diffusion probabilistic models (DDPMs)\
 , to predict the interstellar radiation field (ISRF) strength based on thr
 ee-band dust emission at 4.5 \\um\, 24 \\um\, and 250 \\um. We adopt magne
 tohydrodynamic simulations from the STARFORGE (STAR FORmation in Gaseous E
 nvironments) project that model star formation and giant molecular cloud (
 GMC) evolution. We generate synthetic dust emission maps matching observed
  spectral energy distributions in the Monoceros R2 (MonR2) GMC. We train D
 DPMs to estimate the ISRF using synthetic three-band dust emission. The di
 spersion between the predictions and true values is within a factor of 0.1
  for the test set. We further evaluate the diffusion model's performance o
 n new simulations with ISRF intensities 10 and 100 times higher than that 
 of the fiducial simulations. Despite a systematic underestimation factor o
 f 1.8 and 2.7 for the higher ISRF simulations\, the relative intensity rem
 ains well constrained. Meanwhile\, our analysis reveals weak correlation b
 etween the ISRF solely derived from dust temperature and the actual ISRF. 
 We apply our trained model to predict the ISRF in MonR2\, revealing a corr
 espondence between intense ISRF\, bright sources\, and high dust emission\
 , confirming the model's ability to capture ISRF variations. Our model pro
 vides a robust means to predict the distribution of radiation feedback eve
 n where the ISRF is complex and not well constrained\, such as in regions 
 influenced by nearby star clusters.
LOCATION:Posters
URL:https://pretalx.com/adass2023/talk/AZDQJY/
END:VEVENT
END:VCALENDAR