BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Memento EPFL// BEGIN:VEVENT SUMMARY:CECAM MARVEL Classics lecture on "Simulation methods for spin glas ses with applications in optimization" DTSTART:20221103T150000 DTEND:20221103T173000 DTSTAMP:20260407T103323Z UID:b15da8827d7eb84346788a85aad509b5648d5ba9e64eb986a8bb431b CATEGORIES:Conferences - Seminars DESCRIPTION:Giorgio Parisi\, Università di Roma La Sapienza\, Italy Marc Mezard\, Università Bocconi Milano\, Italy\nIn the CECAM MARVEL Classic s in molecular and materials modelling series\, methods that have become f undamental tools in computational physics and chemistry will be presented by their originators at a level appropriate for master and graduate studen ts. The lectures will be followed by an interview with the presenters: we ’ll ask them to recall for us the period\, problems\, people and circums tances that accompanied the creation of milestone methods and algorithms t hat we now routinely use. \nWe hope that you will be able to join us and share with us this unusual and interesting opportunity to learn first-hand from pioneers who have contributed significantly to our field and to get to know better the history and anecdotes behind work that is now recorded in books. \n\nThe CECAM MARVEL Classics are a fully online webinar series \, you can join us through Zoom at: https://epfl.zoom.us/j/68318773072? pwd=TWUxSzUxTmlzM3ZYbFpxeGRGVkI4QT09 \n\nProgram\n15:00 – Introduction\ n15:05 – 3d simulations of spin glasses on dedicated architectures (G. P arisi)\n15:45 – Spin glass concepts and algorithms in hard constrained s atisfaction problems (M. Mezard)\n16:25 – Break\n16:35 – Interview & r ecollections (moderator L. Berthier)\n17:30 – End\n\nAbstracts\n3d simul ations of spin glasses on dedicated architectures\nGiorgio Parisi\, Univer sità di Roma La Sapienza\nTBA\n\nSpin glasses concepts and algorithms in hard constraint satisfaction problems\nMarc Mézard\, Università Bocconi Milano\nSpin glass theory has had a large impact on many fields. Among the m\, a new field of research is rapidly expanding at the crossroad between statistical physics\, information theory and combinatorial optimization. I t deals with problems which are very important in each of these fields\, l ike spin glasses\, error correction\, or satisfiability. This talk will re view how the cavity method\, initially developed to understand spin glass theory in a framework more transparent than the replica method\, can be tr ansformed into message passing algorithms that turn out to be quite effici ent for several large-scale problems of constraint satisfaction and statis tical inference.\n\nAbout the speakers\nGiorgio Parisi is professor emeri tus of Theoretical Physics at the University of Rome La Sapienza and assoc iate researcher at the INFN National Institute of Nuclear Physics. From 20 18 to 2021 he was President of the Accademia Nazionale dei Lincei\, and cu rrently acts as President of the Class of Physical Sciences\, Mathematics and Natural and Vice President of the Academy. Born in Rome in 1948\, Pari si completed his studies at the Sapienza University of Rome where he gradu ated in physics in 1970. Throughout his scientific career\, Giorgio Parisi has made many decisive and widely recognized contributions in different a reas of physics: in particle physics\, statistical mechanics\, fluid dynam ics\, condensed matter\, supercomputer. He has also written articles on ne ural networks\, immune systems and movement of groups of animals. Among o ther recognitions\, Parisi was awarded\, in 1992\, the Boltzmann Medal f or his contributions to the theory of disordered systems\, the Dirac Medal in Theoretical Physics in 1999\, the Max Planck Medal in 2011\,  the Lar s Onsager Prize of the American Physical Society 2016\, the Nature Award f or Mentoring in Science 2013\, and the Wolf Prize in Physics in 2021. In 2 021 Giorgio Parisi was awarded the Nobel Prize in Physics.\n\nMarc Méza rd is a Professor of Theoretical Physics. He studied physics at Ecole normale supérieure in Paris and obtained his PhD in 1984. Hired at CNRS in Paris\, he was Research Director in Université Paris Sud. From 2012 and 2022 he became Director of Ecole normale supérieure\, and then joi ned Bocconi University as a professor\, in the newly created department of computational sciences.  Prof. Mezard’s work focuses on statistical physics of disordered systems\, with applications in various fields like i nformation theory\, computer science\, machine learning\, biophysics. In recent years his research has focused on information processing in neura l networks\, machine learning and deep networks\, with specific interest i n the theoretical impact of data structure on learning strategies and gen eralization performance. LOCATION:https://epfl.zoom.us/j/68318773072?pwd=TWUxSzUxTmlzM3ZYbFpxeGRGVk I4QT09 STATUS:CONFIRMED END:VEVENT END:VCALENDAR