Spin Glasses and Related Systems (Lecture 5) by Chandan Dasgupta
PROGRAM: BANGALORE SCHOOL ON STATISTICAL PHYSICS - XIII (HYBRID)
ORGANIZERS: Abhishek Dhar (ICTS-TIFR, India) and Sanjib Sabhapandit (RRI, India)
DATE & TIME: 11 July 2022 to 22 July 2022
VENUE: Madhava Lecture Hall and Online
This school is the thirteenth in the series. The school this year will be conducted in the hybrid mode. Local participants in Bangalore can attend the school in-person. We expect that a few lectures will be delivered in-person.
This is a pedagogical school, aimed at bridging the gap between masters-level courses and topics in statistical physics at the forefront of current research. It is intended for Ph.D. students, post-doctoral fellows and interested faculty members. The following courses will be offered.
Statistical physics of Turbulence — Jérémie Bec (Université Côte d’Azur, Nice)
Spin glasses — Chandan Dasgupta (ICTS and IISc, Bangalore)
Stochastic chemical reaction networks — Supriya Krishnamurthy (Stockholm University, Stockholm)
Pattern formation in Biology — Vijaykumar Krishnamurthy (ICTS, Bangalore)
Stochastic Gradient Descent and Machine Learning — Praneeth Netrapalli (Google Research India, Bangalore)
Statistical physics of long-range systems — Stefano Ruffo (SISSA, Trieste) and Nicolò Defenu (ETH Zürich, Zürich)
You need to register even if you intend to attend only a few of the lecture sets.
ICTS is committed to building an environment that is inclusive, non-discriminatory and welcoming of diverse individuals. We especially encourage the participation of women and other under-represented groups.
CONTACT US: bssp@icts.res.in
PROGRAM LINK: https://www.icts.res.in/program/bssp2022
Table of Contents (powered by https://videoken.com)
0:00:00 Spin Glasses and Related Systems (Lecture 5)
0:00:12 Ultrametricity: The valleys are arranged in a hierarchical tree-like ('ultrametric') structure
0:00:33 Thouless-Anderson-Palmer Equations
0:05:39 TAP Equations (contd.)
0:15:09 Physical interpretation of RSB
0:19:42 Predictions of the Paris solution have been confirmed from simulations.
0:20:51 Does the Paris solution explain experimentally observed behaviour in real spin glasses?
1:02:11 Dynamics: Slow relaxation, hysteresis, memory effects, aging, ....
1:06:52 Significance of the Paris Solution
1:09:37 Structural Glass: Disordered solid-like state obtained by rapidly cooling a liquid to a temperature lower than the equilibrium crystallization temperature
1:10:00 Glass: non-crystalline "solid"
1:10:44 Viscosity increases by 14-16 orders of magnitude as the temperature of a supercooled liquid is decreased by about 100 degrees
1:13:04 Slow dynamics of glass-forming liquids
1:13:22 The Adam-Gibbs Relation
1:13:55 Energy landscape picture
1:15:16 The dependence of the alpha relaxation time on both T and N is well described by the Adam-Gibbs relation
1:15:52 Random First Order Transition (RFOT) Theory
1:18:39 For T Td:
1:22:30 Other "Glassy" Systems
1:22:43 The String Theory Landscape
1:22:45 Associative Memory: Retrieval of stored information from partial knowledge [content addressable memory]
1:32:52 Physical Interpretation of the Paris Solution
1:36:45 Thank You
Видео Spin Glasses and Related Systems (Lecture 5) by Chandan Dasgupta канала International Centre for Theoretical Sciences
ORGANIZERS: Abhishek Dhar (ICTS-TIFR, India) and Sanjib Sabhapandit (RRI, India)
DATE & TIME: 11 July 2022 to 22 July 2022
VENUE: Madhava Lecture Hall and Online
This school is the thirteenth in the series. The school this year will be conducted in the hybrid mode. Local participants in Bangalore can attend the school in-person. We expect that a few lectures will be delivered in-person.
This is a pedagogical school, aimed at bridging the gap between masters-level courses and topics in statistical physics at the forefront of current research. It is intended for Ph.D. students, post-doctoral fellows and interested faculty members. The following courses will be offered.
Statistical physics of Turbulence — Jérémie Bec (Université Côte d’Azur, Nice)
Spin glasses — Chandan Dasgupta (ICTS and IISc, Bangalore)
Stochastic chemical reaction networks — Supriya Krishnamurthy (Stockholm University, Stockholm)
Pattern formation in Biology — Vijaykumar Krishnamurthy (ICTS, Bangalore)
Stochastic Gradient Descent and Machine Learning — Praneeth Netrapalli (Google Research India, Bangalore)
Statistical physics of long-range systems — Stefano Ruffo (SISSA, Trieste) and Nicolò Defenu (ETH Zürich, Zürich)
You need to register even if you intend to attend only a few of the lecture sets.
ICTS is committed to building an environment that is inclusive, non-discriminatory and welcoming of diverse individuals. We especially encourage the participation of women and other under-represented groups.
CONTACT US: bssp@icts.res.in
PROGRAM LINK: https://www.icts.res.in/program/bssp2022
Table of Contents (powered by https://videoken.com)
0:00:00 Spin Glasses and Related Systems (Lecture 5)
0:00:12 Ultrametricity: The valleys are arranged in a hierarchical tree-like ('ultrametric') structure
0:00:33 Thouless-Anderson-Palmer Equations
0:05:39 TAP Equations (contd.)
0:15:09 Physical interpretation of RSB
0:19:42 Predictions of the Paris solution have been confirmed from simulations.
0:20:51 Does the Paris solution explain experimentally observed behaviour in real spin glasses?
1:02:11 Dynamics: Slow relaxation, hysteresis, memory effects, aging, ....
1:06:52 Significance of the Paris Solution
1:09:37 Structural Glass: Disordered solid-like state obtained by rapidly cooling a liquid to a temperature lower than the equilibrium crystallization temperature
1:10:00 Glass: non-crystalline "solid"
1:10:44 Viscosity increases by 14-16 orders of magnitude as the temperature of a supercooled liquid is decreased by about 100 degrees
1:13:04 Slow dynamics of glass-forming liquids
1:13:22 The Adam-Gibbs Relation
1:13:55 Energy landscape picture
1:15:16 The dependence of the alpha relaxation time on both T and N is well described by the Adam-Gibbs relation
1:15:52 Random First Order Transition (RFOT) Theory
1:18:39 For T Td:
1:22:30 Other "Glassy" Systems
1:22:43 The String Theory Landscape
1:22:45 Associative Memory: Retrieval of stored information from partial knowledge [content addressable memory]
1:32:52 Physical Interpretation of the Paris Solution
1:36:45 Thank You
Видео Spin Glasses and Related Systems (Lecture 5) by Chandan Dasgupta канала International Centre for Theoretical Sciences
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