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Statistical Physics of Turbulence (Lecture 2) by Jeremie Bec
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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.
0:00:00 Statistical Physics of Turbulence (Lecture 2)
0:00:12 Lecture 2: A statistical description
0:00:48 Recap on Kolmogorov 1941
0:03:17 Formalizing the phenomenology
0:06:28 Two exact laws
0:25:05 Scaling exponents
0:29:57 Breaking of scale invariance
0:35:06 Spatial intermittently
0:38:45 Intermittent cascade
0:39:37 Kolmogorov 1962
0:47:32 Multifractal formalism
1:08:19 Log-normal model
1:27:16 Lagrangian structure function
1:29:18 Other temporal intermittency
1:33:48 Q&A
1:35:36 Thanks
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.
0:00:00 Statistical Physics of Turbulence (Lecture 2)
0:00:12 Lecture 2: A statistical description
0:00:48 Recap on Kolmogorov 1941
0:03:17 Formalizing the phenomenology
0:06:28 Two exact laws
0:25:05 Scaling exponents
0:29:57 Breaking of scale invariance
0:35:06 Spatial intermittently
0:38:45 Intermittent cascade
0:39:37 Kolmogorov 1962
0:47:32 Multifractal formalism
1:08:19 Log-normal model
1:27:16 Lagrangian structure function
1:29:18 Other temporal intermittency
1:33:48 Q&A
1:35:36 Thanks
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