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SUMMARY:Quantum annealing for material science
DTSTART:20250702T130000Z
DTEND:20250702T140000Z
DTSTAMP:20260418T044500Z
UID:indico-event-17055@indico.psi.ch
CONTACT:matthias.krack@psi.ch
DESCRIPTION:Speakers: Alfredo Fiorentino (PSI)\n\nFinding the global minim
 um of the potential-energy surface is a fundamental problem in material sc
 ience\, with applications ranging from protein folding to cluster physics
 —or more generally\, to systems where the number of (meta)stable configu
 rations becomes prohibitively large. Classical annealing (CA) is a time-ho
 nored\, robust technique that explores the configurational phase space via
  thermal fluctuations. However\, in recent decades\, quantum annealing (Q
 A) has emerged as a promising alternative\, relying instead on quantum flu
 ctuations and often outperforming CA in multi-minima systems with large en
 ergy barriers [1\,2].\nWe propose a novel QA implementation using path-int
 egral molecular dynamics\, a method well-suited for sampling quantum nucle
 ar densities. This offers an alternative to the path-integral Monte Carlo 
 approaches used in previous works [1\,3]. After validating our method on s
 tandard benchmarks such as Lennard-Jones clusters\, we apply it—together
  with machine-learning potentials—to problems of broad relevance in mate
 rial science.\n[1] G. E. Santoro et al.\, J. Phys. A 39\, R393 (2006).[2]
  L. Stella et al.\, Phys. Rev. B 72\, 014303 (2005).[3] T. Gregor et al.\
 , Chem. Phys. Lett. 412\, 125 (2005)\n\nhttps://indico.psi.ch/event/17055
 /
LOCATION:OVGA/200
URL:https://indico.psi.ch/event/17055/
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