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The mathematical similarities between non-relativistic wavefunction propagation in quantum mechanics and image propagation in scalar diffraction theory are used to develop a novel understanding of time and paths through spacetime as a…

Quantum Physics · Physics 2021-03-08 Sky Nelson-Isaacs

Stochastic methods are ubiquitous to a variety of fields, ranging from Physics to Economy and Mathematics. In many cases, in the investigation of natural processes, stochasticity arises every time one considers the dynamics of a system in…

Statistical Mechanics · Physics 2012-08-02 Robert Biele , Roberto D'Agosta

This work discusses simple examples how quantum systems are obtained as subsystems of classical statistical systems. For a single qubit with arbitrary Hamiltonian and for the quantum particle in a harmonic potential we provide explicitly…

Quantum Physics · Physics 2024-08-14 C. Wetterich

We present new extensions to a method for constructing several families of solvable one-dimensional time-homogeneous diffusions whose transition densities are obtainable in analytically closed-form. Our approach is based on a dual…

Pricing of Securities · Quantitative Finance 2014-12-03 Giuseppe Campolieti , Roman N. Makarov

A theory of systems with long-range correlations based on the consideration of binary N-step Markov chains is developed. In the model, the conditional probability that the i-th symbol in the chain equals zero (or unity) is a linear function…

Data Analysis, Statistics and Probability · Physics 2016-09-08 O. V. Usatenko , V. A. Yampol'skii , K. E. Kechedzhy , S. S. Mel'nyk

Some ideas from quantum theory are just beginning to percolate back to classical probability theory. For example, there is a widely used and successful theory of "chemical reaction networks", which describes the interactions of molecules in…

Quantum Physics · Physics 2019-05-07 John C. Baez , Jacob Biamonte

As an extension of the theory of Dyson's Brownian motion models for the standard Gaussian random-matrix ensembles, we report a systematic study of hermitian matrix-valued processes and their eigenvalue processes associated with the chiral…

Mathematical Physics · Physics 2007-05-23 Makoto Katori , Hideki Tanemura

We propose a natural, parameter-free, discrete-variable formulation of Feynman path integrals. We show that for discrete-variable quantum systems, Feynman path integrals take the form of walks on the graph whose weighted adjacency matrix is…

Quantum Physics · Physics 2025-12-08 Amir Kalev , Itay Hen

We theoretically investigate the non-equilibrium quantum dynamical theory of a quantum dot system coupled to fermionic reservoirs using the recently developed stochastic fermionic quantum state diffusion (FQSD) equation. The exact or…

Quantum Physics · Physics 2018-12-07 Wufu Shi , Yusui Chen , Lihui Sun , J. Q. You , Ting Yu

By using a simple observation that the density processes appearing in Ito's martingale representation theorem are invariant under the change of measures, we establish a non-linear version of the Cameron-Martin formula for solutions of a…

Probability · Mathematics 2010-11-16 G. Liang , A. Lionnet , Z. Qian

For a stochastic system, its evolution from one state to another can have a large number of possible paths. Non-uniformity in the field of system variables leads the local dynamics in state transition varies considerably from path to path…

Statistical Mechanics · Physics 2019-03-26 De-yu Zhong , Guang-qian Wang , Tie-jian Li , Ming-xi ZHANG , You Xia , Yu Zhang

We consider the discrete time unitary dynamics given by a quantum walk on $\Z^d$ performed by a particle with internal degree of freedom, called coin state, according to the following iterated rule: a unitary update of the coin state takes…

Mathematical Physics · Physics 2015-05-30 Eman Hamza , Alain Joye

Statistical mechanics of the discrete nonlinear Schr\"odinger equation is studied by means of analytical and numerical techniques. The lower bound of the Hamiltonian permits the construction of standard Gibbsian equilibrium measures for…

Statistical Mechanics · Physics 2009-10-31 K. Ø. Rasmussen , T. Cretegny , P. G. Kevrekidis , N. Grønbech-Jensen

The development of methods of quantum statistical mechanics is considered in light of their applications to quantum solid-state theory. We discuss fundamental problems of the physics of magnetic materials and the methods of the quantum…

Strongly Correlated Electrons · Physics 2011-02-21 A. L. Kuzemsky

The non-Markovian dynamics of open quantum systems is still a challenging task, particularly in the non-perturbative regime at low temperatures. While the Stochastic Liouville-von Neumann equation (SLN) provides a formally exact tool to…

Statistical Mechanics · Physics 2016-12-21 Michael Wiedmann , Jürgen T. Stockburger , Joachim Ankerhold

We study large deviations principles for $ N $ random processes on the lattice $ \Z^d $ with finite time horizon $ [0,\beta] $ under a symmetrised measure where all initial and terminal points are uniformly given by a random permutation.…

Mathematical Physics · Physics 2007-05-23 Stefan Adams , Tony Dorlas

We study the diffusion process in a Heisenberg chain with correlated spatial disorder, with a power spectrum in the momentum space behaving as $k^{-\beta}$, using a stochastic description. It establishes a direct connection between the…

Statistical Mechanics · Physics 2007-05-23 M. H. Vainstein , R. Morgado , F. A. Oliveira , F. A. B. F. de Moura , M. D. Coutinho-Filho

Discrete diffusion models have gained increasing attention for their ability to model complex distributions with tractable sampling and inference. However, the error analysis for discrete diffusion models remains less well-understood. In…

Machine Learning · Computer Science 2025-03-04 Yinuo Ren , Haoxuan Chen , Grant M. Rotskoff , Lexing Ying

Analytical (rational) mechanics is the mathematical structure of Newtonian deterministic dynamics developed by D'Alembert, Langrange, Hamilton, Jacobi, and many other luminaries of applied mathematics. Diffusion as a stochastic process of…

Mathematical Physics · Physics 2012-09-03 Hao Ge , Hong Qian

We develop an approach to learn an interpretable semi-parametric model of a latent continuous-time stochastic dynamical system, assuming noisy high-dimensional outputs sampled at uneven times. The dynamics are described by a nonlinear…

Machine Learning · Statistics 2019-02-13 Lea Duncker , Gergo Bohner , Julien Boussard , Maneesh Sahani