Sampling and Statistical Physics via Symmetry
نویسندگان
چکیده
We formulate both Markov chain Monte Carlo (MCMC) sampling algorithms and basic statistical physics in terms of elementary symmetries. This perspective on yields derivations well-known MCMC a new parallel algorithm that appears to converge more quickly than current state the art methods. The symmetry also parsimonious framework for practical approach constructing meaningful notions effective temperature energy directly from time series data. apply these latter ideas Anosov systems.
منابع مشابه
statistical inference via empirical bayes approach for stationary and dynamic contingency tables
چکیده ندارد.
15 صفحه اولUnderstanding Search Trees via Statistical Physics
Satya N. Majumdar , David S. Dean 2 and P.L. Krapivsky 3 Laboratoire de Physique Théorique et Modèles Statistiques, Université Paris-Sud. Bât. 100. 91405 Orsay Cedex. France Laboratoire de Physique Theorique (UMR C5152 du CNRS), Université Paul Sabatier, 31062 Toulouse Cedex. France 3 Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215, USA (Febr...
متن کاملMonitoring Large Systems Via Statistical Sampling
As the trend in parallel systems scales toward petaflop performance tapped by advances in circuit density and by an increasingly available computational Grid, the development of efficient mechanisms for monitoring large systems becomes imperative. When computational components are coupled via dynamically shifting connections with various remote resources, the number of potential factors affecti...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Springer proceedings in mathematics & statistics
سال: 2021
ISSN: ['2194-1009', '2194-1017']
DOI: https://doi.org/10.1007/978-3-030-77957-3_20