Загрузка страницы
Все видеоНовые видеоПопулярные видеоКатегории видео

Dor Elboim - Poisson-Dirichlet distribution for the interchange process in five dimensions

Recorded 07 May 2024. Dor Elboim of the Institute for Advanced Study presents "Poisson-Dirichlet distribution for the interchange process in five dimensions" at IPAM's Statistical Mechanics Beyond 2D Workshop.
Abstract: In the interchange process on a graph G=(V,E), distinguished particles are placed on the vertices of G with independent Poisson clocks on the edges. When the clock of an edge rings, the two particles on the two sides of the edge interchange. In this way a random permutation on the set of vertices is formed for any time t 0. One of the main objects of study is the cycle structure of the random permutation and the emergence of long cycles.
We consider the process on the torus of side length L in dimension d 4 and prove that macroscopic cycles emerge after a long time t. These are cycles whose length is proportional to the volume of the torus L^d. Moreover, we show that the cycle lengths converge to the Poisson-Dirichlet distribution.
This is a joint work with Allan Sly.
Learn more online at: https://www.ipam.ucla.edu/programs/workshops/workshop-iii-statistical-mechanics-beyond-2d/

Видео Dor Elboim - Poisson-Dirichlet distribution for the interchange process in five dimensions канала Institute for Pure & Applied Mathematics (IPAM)
Показать
Комментарии отсутствуют
Введите заголовок:

Введите адрес ссылки:

Введите адрес видео с YouTube:

Зарегистрируйтесь или войдите с
Информация о видео
8 мая 2024 г. 2:01:31
00:47:14
Institute for Pure & Applied Mathematics (IPAM)
Теги
Правообладателям
Жалоба
Комментарии
Другие видео канала
Jaafar El-Awady - dislocation in high thermomechanical condition in Additive Manufacturing of AlloysJaafar El-Awady - dislocation in high thermomechanical condition in Additive Manufacturing of AlloysVikram Gavini - Fast, Accurate and Large-scale Ab-initio Calculations for Materials ModelingVikram Gavini - Fast, Accurate and Large-scale Ab-initio Calculations for Materials ModelingBistra Dilkina - Machine Learning for MIP Solving - IPAM at UCLABistra Dilkina - Machine Learning for MIP Solving - IPAM at UCLAAmit Acharya - Slow time-scale behavior of fast microscopic dynamics - IPAM at UCLAAmit Acharya - Slow time-scale behavior of fast microscopic dynamics - IPAM at UCLAEran Rabani - Stochastic Density Functional Theory - IPAM at UCLAEran Rabani - Stochastic Density Functional Theory - IPAM at UCLADeanna Needell - Using Algebraic Factorizations for Interpretable Learning - IPAM at UCLADeanna Needell - Using Algebraic Factorizations for Interpretable Learning - IPAM at UCLAXavier Bresson - Learning to Untangle Genome Assembly Graphs - IPAM at UCLAXavier Bresson - Learning to Untangle Genome Assembly Graphs - IPAM at UCLAJack Gilbert: "Microbiome of the Built Environment"Jack Gilbert: "Microbiome of the Built Environment"John Harrison - Formalization and Automated Reasoning: A Personal and Historical PerspectiveJohn Harrison - Formalization and Automated Reasoning: A Personal and Historical PerspectiveRaymond Clay - Machine Learning in Equation of State and Transport Modeling at Extreme ConditionsRaymond Clay - Machine Learning in Equation of State and Transport Modeling at Extreme ConditionsDavid Ceperley - Quantum Monte Carlo and Machine Learning Simulations of Dense HydrogenDavid Ceperley - Quantum Monte Carlo and Machine Learning Simulations of Dense HydrogenRose Yu - Incorporating Symmetry for Learning Spatiotemporal Dynamics - IPAM at UCLARose Yu - Incorporating Symmetry for Learning Spatiotemporal Dynamics - IPAM at UCLAYongsoo Yang - Neural network-assisted atomic electron tomography - IPAM at UCLAYongsoo Yang - Neural network-assisted atomic electron tomography - IPAM at UCLAAlbert Fannjiang - From Tomographic Phase Retrieval to Projection Tomography - IPAM at UCLAAlbert Fannjiang - From Tomographic Phase Retrieval to Projection Tomography - IPAM at UCLAThomas Swinburne - Learning uncertainty-aware models of defect kinetics at scale - IPAM at UCLAThomas Swinburne - Learning uncertainty-aware models of defect kinetics at scale - IPAM at UCLAKevin Kelly - Machine Learning Enhanced Compressive Hyperspectral Imaging - IPAM at UCLAKevin Kelly - Machine Learning Enhanced Compressive Hyperspectral Imaging - IPAM at UCLADemetri Psaltis - Machine Learning for 3D Optical Imaging - IPAM at UCLADemetri Psaltis - Machine Learning for 3D Optical Imaging - IPAM at UCLAPaola Gori-Giorgi - Large-coupling strength expansion in DFT and Hartree-Fock adiabatic connectionsPaola Gori-Giorgi - Large-coupling strength expansion in DFT and Hartree-Fock adiabatic connectionsBohua Zhan - Verifying symbolic computation in the HolPy theorem prover - IPAM at UCLABohua Zhan - Verifying symbolic computation in the HolPy theorem prover - IPAM at UCLAXiantao Li - A stochastic algorithm for self-consistent calculations in DFT - IPAM at UCLAXiantao Li - A stochastic algorithm for self-consistent calculations in DFT - IPAM at UCLAPascal Van Hentenryck - Fusing Machine Learning and Optimization - IPAM at UCLAPascal Van Hentenryck - Fusing Machine Learning and Optimization - IPAM at UCLA
Статистика портала
Яндекс.Метрика
© 2008-2024 «Информационно-развлекательный портал города Верхняя Салда»
| Карта портала | Реклама | Контакты | Сообщить об ошибке | Соглашения
salda.ws salda.ws@mail.ru
Сейчас на сайте: 512 Статистика портала