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TZID:Europe/Paris
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BEGIN:VEVENT
UID:0-791@lptms.universite-paris-saclay.fr
DTSTART:20220111T110000Z
DTEND:20220111T123000Z
DTSTAMP:20220102T183015Z
URL:http://www.lptms.universite-paris-saclay.fr/seminars/seminaire-du-lptm
 s-alexei-chepelianskii-lps/
SUMMARY:Séminaire du LPTMS: Alexei Chepelianskii (LPS) - Petit amphi\, bâ
 timent Pascal n° 530 - 11 Jan 22 11:00
DESCRIPTION:Monte Carlo sampling: convergence\, localization transition and
  optimality\nAlexei Chepelianskii  (Laboratoire de Physique des Solides)\
 nOnsite + zoom.\n\nZoom link: https://cnrs.zoom.us/j/96861999262?pwd=bzlk
 QThNenNyYVdoMXpKUlF0VXloQT09\n\nMeeting ID: 968 6199 9262\nPasscode: 5C7NB
 W\nAmong random sampling methods\, Markov Chain Monte Carlo algorithms are
  foremost. From a combination of analytical and numerical approaches\, we 
 study their convergence properties towards the steady state. We show that 
 the deviations from the target steady-state distribution features a locali
 zation transition as a function of the characteristic length of the attemp
 ted jumps defining the random walk in a Metropolis scheme. This transition
  changes drastically the error which is introduced by incomplete convergen
 ce. Remarkably\, the localization transition occurs for parameters that al
 so provide the optimal Monte Carlo convergence speed. We show that the rel
 axation of the error in the localized regime has some similarities with re
 laxation in a greedy Monte Carlo algorithm where jumps always  occur to l
 ower energy sites (zero temperature limit). In both cases relaxation is de
 scribed by a self-similar ansatz instead of being dominated by the  eigen
 mode with the slowest relaxation rate as in diffusion problems.\n&nbsp\;
CATEGORIES:seminars
LOCATION:Petit amphi\, bâtiment Pascal n° 530\, rue André Rivière\, Ors
 ay\, 91405\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=rue André Rivière\, Orsay
 \, 91405\, France;X-APPLE-RADIUS=100;X-TITLE=Petit amphi\, bâtiment Pasca
 l n° 530:geo:0,0
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