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DTSTART;TZID=Europe/Paris:20230613T140000
DTEND;TZID=Europe/Paris:20230613T153000
DTSTAMP:20260423T072348
CREATED:20230606T140038Z
LAST-MODIFIED:20230612T121721Z
UID:9013-1686664800-1686670200@fermi.univ-tlse3.fr
SUMMARY:Automatic differentiation in iPEPS simulations : unravelling the black box . - (Anna Francuz / LPT / Seminar). - 13/06/2023\, 14H
DESCRIPTION:Anna Francuz (Université de Vienne) \nSeminar LPT\, 13/06/2023\, 14H\, 3R1\, seminar room\, 3rd floor \nSummary : \nTensor networks have already proven to be extremely useful tools in the studies of strongly correlated quantum systems. Being immune to the sign problem\, they enable calculations beyond Quantum Monte Carlo and directly in the thermodynamic limit. The most established and understood tensor network method is density matrix renormalization group (DMRG)\, while all others\, including projected entangled pair states (PEPS) seemed to remain far behind until recently\, when an automatic differentiation framework was established. This toolbox\, originally developed for the deep learning purposes\, enables a simple calculation of exact derivatives in an optimization problem at hand and hence bridges the gap between DMRG and PEPS simulations. I will try to deliver a multi-level talk\, starting with a comprehensive introduction of tensor network methods with focus on iPEPS before delving into details of derivative calculation for optimization purposes. On the example of Corner Transfer Matrix (CTM) I will explain the idea of algorithmic differentiation\, present possible challenges and show ways to overcome them. \n  \n 
URL:https://fermi.univ-tlse3.fr/event/tba-anna-francuz-lpt-seminar-13-06-2023-14h/
LOCATION:salle de séminaire 3ème étage\, Bâtiment 3r1 Université Toulouse III\, Toulouse\, 31400\, France
CATEGORIES:Events,LPT,Seminars
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