BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Nicole Yunger Halpern (NIST\, QuICS and University of Maryland) DTSTART:20220711T170000Z DTEND:20220711T180000Z DTSTAMP:20260412T170608Z UID:IIPSeminar2022/1 DESCRIPTION:Title: MBL-mobile: Many-body-localized engine\nby Nicole Yunger Halper n (NIST\, QuICS and University of Maryland) as part of Virtual Seminar of the International Institute of Physics 2022\n\n\nAbstract\nMany-body-local ized (MBL) systems do not thermalize under their intrinsic dynamics. The a thermality of MBL\, we propose\, can be harnessed for thermodynamic tasks. We illustrate this ability by formulating an Otto engine cycle for a quan tum many-body system. The system is ramped between a strongly localized MB L regime and a thermal (or weakly localized) regime. The difference betwee n the energy-level correlations of MBL systems and of thermal systems enab les mesoscale engines to run in parallel in the thermodynamic limit\, enha nces the engine’s reliability\, and suppresses worst-case trials. We est imate analytically and calculate numerically the engine’s efficiency and per- cycle power. The efficiency mirrors the efficiency of the convention al thermodynamic Otto engine. This work introduces a thermodynamic lens on to MBL\, which\, having been studied much recently\, can now be leveraged in thermodynamic tasks\n LOCATION:https://researchseminars.org/talk/IIPSeminar2022/1/ END:VEVENT BEGIN:VEVENT SUMMARY:Kathryn Tunyasuvunakool (DeepMind) DTSTART:20221031T170000Z DTEND:20221031T180000Z DTSTAMP:20260412T170608Z UID:IIPSeminar2022/2 DESCRIPTION:Title: Highly accurate protein structure prediction with AI\nby Kathry n Tunyasuvunakool (DeepMind) as part of Virtual Seminar of the Internation al Institute of Physics 2022\n\n\nAbstract\nThere is increasing interest i n applying AI methods to problems in the sciences. Particularly in biology \, these methods hold the promise of extracting actionable hypotheses from complex data\, and developing practically useful predictive models. In th is talk\, I'll discuss a specific example: the recent progress in predicti ng a protein's 3D structure from its amino acid sequence\, in particular u sing the model AlphaFold. While the focus will be on how this model works and how it's being applied in the life sciences\, I'll also try to touch o n the relationship between AlphaFold and protein physics.\n LOCATION:https://researchseminars.org/talk/IIPSeminar2022/2/ END:VEVENT BEGIN:VEVENT SUMMARY:Isabel Garcia Garcia (NYU and IAS\, Princeton) DTSTART:20221107T170000Z DTEND:20221107T180000Z DTSTAMP:20260412T170608Z UID:IIPSeminar2022/3 DESCRIPTION:Title: Gravity and Effective Field Theory\nby Isabel Garcia Garcia (NY U and IAS\, Princeton) as part of Virtual Seminar of the International Ins titute of Physics 2022\n\n\nAbstract\nFrom the cosmological constant to th e smallness of the weak scale to the strong-CP problem\, the problems of t he Standard Model are problems of effective field theory. Yet improvements in our understanding of gravity -- from the absence of global symmetries to the subextensive entropy of black holes -- challenge some of our long-h eld views on the applicability of this framework.\n\nI will discuss how gr avitational considerations provide an opportunity to get a new perspective on some of the long-standing puzzles in particle physics. I will emphasiz e the role of semiclassical gravity techniques and black hole thought expe riments on our improved understanding of gravitational theories\, and argu e that only a combination of new theoretical developments and original ide as\, confronted with the vast array of experiments at our disposal\, will provide us with the big picture we need to discover what comes next.\n LOCATION:https://researchseminars.org/talk/IIPSeminar2022/3/ END:VEVENT END:VCALENDAR