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Classical and quantum statistical mechanics are cast here in the language of projective geometry to provide a unified geometrical framework for statistical physics. After reviewing the Hilbert space formulation of classical statistical…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Dorje C. Brody , Lane P. Hughston

Predictive statistical mechanics is a form of inference from available data, without additional assumptions, for predicting reproducible phenomena. By applying it to systems with Hamiltonian dynamics, a problem of predicting the macroscopic…

Statistical Mechanics · Physics 2015-09-22 Domagoj Kuic

Maintaining the position that the wave function $\psi$ provides a complete description of state, the traditional formalism of quantum mechanics is augmented by introducing continuous trajectories for particles which are sample paths of a…

Quantum Physics · Physics 2007-05-23 Tulsi Dass

We propose a new interpretation of objective deterministic chances in statistical physics based on physical computational complexity. This notion applies to a single physical system (be it an experimental set--up in the lab, or a subsystem…

Quantum Physics · Physics 2013-03-20 Amit Hagar , Giuseppe Sergioli

Mechanisms for the automation of uncertainty are required for expert systems. Sometimes these mechanisms need to obey the properties of probabilistic reasoning. A purely numeric mechanism, like those proposed so far, cannot provide a…

Artificial Intelligence · Computer Science 2013-04-15 Alan Bundy

The Boltzmann distribution of an ideal gas is determined by the Hamiltonian function generating single particle dynamics. Systems with higher complexity often exhibit topological constraints, which are independent of the Hamiltonian and may…

General Relativity and Quantum Cosmology · Physics 2021-07-29 Naoki Sato

Multi-model ensembles provide a pragmatic approach to the representation of model uncertainty in climate prediction. However, such representations are inherently ad hoc, and, as shown, probability distributions of climate variables based on…

Atmospheric and Oceanic Physics · Physics 2009-08-26 T. N. Palmer , F. J. Doblas-Reyes , A. Weisheimer , G. J. Shutts , J. Berner , J. M. Murphy

The new interpretation of Quantum Mechanics is based on a complex probability theory. An interpretation postulate specifies events which can be observed and it follows that the complex probability of such event is, in fact, a real positive…

Quantum Physics · Physics 2007-05-23 Jiri Soucek

Stochastic mechanics is regarded as a physical theory to explain quantum mechanics with classical terms such that some of the quantum mechanics paradoxes can be avoided. Here we propose a new variational principle to uncover more insights…

Quantum Physics · Physics 2025-12-02 Jianhao M. Yang

The present paper is meant to give a simple introduction to the problem of the connection between microscopic dynamics and statistical laws. For sake of simplicity, we mostly refer to non-dissipative dynamics, since dissipation adds…

Statistical Mechanics · Physics 2014-10-02 Sergio Chibbaro , Lamberto Rondoni , Angelo Vulpiani

Most versions of classical physics imply that if the 4-volume of the entire space-time is infinite or at least extremely large, then random fluctuations in the matter will by coincidence create copies of us in remote places, so called…

General Relativity and Quantum Cosmology · Physics 2018-12-06 Roderich Tumulka

The question about the existence of so-called ``hidden'' variables in quantum mechanics and the perception of the completeness of quantum mechanics are two sides of the same coin. Quantum analytical mechanics constitutes a completion of…

Quantum Physics · Physics 2026-05-01 Wolfgang Paul

We describe the statistical mechanics of a new method to produce very cold atoms or molecules. The method results from trapping a gas in a potential well, and sweeping through the well a semi-permeable barrier, one that allows particles to…

Atomic Physics · Physics 2009-11-11 Artem M. Dudarev , M. Marder , Qian Niu , Nathaniel J. Fisch , Mark G. Raizen

In this paper we study binary interaction schemes with uncertain parameters for a general class of Boltzmann-type equations with applications in classical gas and aggregation dynamics. We consider deterministic (i.e., a priori averaged) and…

Analysis of PDEs · Mathematics 2018-11-05 Andrea Tosin , Mattia Zanella

Robots are still poor at traversing cluttered large obstacles required for important applications like search and rescue. By contrast, animals are excellent at doing so, often using direct physical interaction with obstacles rather than…

Robotics · Computer Science 2022-03-15 Bokun Zheng , Qihan Xuan , Chen Li

This paper is concerned by statistical inference problems from a data set whose elements may be modeled as random probability measures such as multiple histograms or point clouds. We propose to review recent contributions in statistics on…

Statistics Theory · Mathematics 2019-08-27 Jérémie Bigot

We examine the fundamental aspects of statistical mechanics, dividing the problem into a discussion purely about probability, which we analyse from a Bayesian standpoint. We argue that the existence of a unique maximising probability…

Statistical Mechanics · Physics 2015-12-07 B. Buck , A. C. Merchant

Conventional thermo-statistics address infinite homogeneous systems within the canonical ensemble. However, some 150 years ago the original motivation of thermodynamics was the description of steam engines, i.e. boiling water. Its essential…

Statistical Mechanics · Physics 2009-11-10 D. H. E. Gross

Studying evolutionary correlations in alignments of homologous sequences by means of an inverse Potts model has proven useful to obtain residue-residue contact energies and to predict contacts in proteins. The quality of the results depend…

Biomolecules · Quantitative Biology 2019-09-04 G. Franco , M. Cagiada , G. Bussi , G. Tiana

Computational mechanics is a method for discovering, describing and quantifying patterns, using tools from statistical physics. It constructs optimal, minimal models of stochastic processes and their underlying causal structures. These…

Machine Learning · Computer Science 2007-05-23 Cosma Rohilla Shalizi , James P. Crutchfield