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We consider a class of infinite-dimensional dynamical systems driven by non-linear parabolic partial differential equations with initial condition $\theta$ modelled by a Gaussian process `prior' probability measure. Given discrete samples…

Statistics Theory · Mathematics 2026-04-20 Richard Nickl

It is widely believed that the underlying reality behind statistical mechanics is a deterministic and unitary time evolution of a many-particle wave function, even though this is in conflict with the irreversible, stochastic nature of…

Statistical Mechanics · Physics 2017-05-16 Barbara Drossel

We consider nonlinear, or "event-dependent", sampling, i.e. such that the sampling instances {tk} depend on the function being sampled. The use of such sampling in the construction of Lebesgue's integral sums is noted and discussed as…

Data Analysis, Statistics and Probability · Physics 2016-11-17 Emanuel Gluskin

Power moments, modified moments, and optimized moments are powerful tools for solving microscopic models of macroscopic systems; however the expansion of the density of states as a continued fraction does not converge to the macroscopic…

Materials Science · Physics 2009-11-11 Roger Haydock , C. M. M. Nex

We study the probability distribution function of the long-time values of observables being time-evolved by Hamiltonians modeling clean and disordered one-dimensional chains of many spin-1/2 particles. In particular, we analyze the return…

Disordered Systems and Neural Networks · Physics 2023-10-10 I. Vallejo-Fabila , E. Jonathan Torres-Herrera

We investigate the generic transport in a one-dimensional strongly correlated fermionic chain beyond linear response. Starting from a Gaussian wave packet with positive momentum on top of the ground state, we find that the numerical time…

Strongly Correlated Electrons · Physics 2025-07-24 Flávia B. Ramos , Rodrigo G. Pereira , Sebastian Eggert , Imke Schneider

We address the observability problem for ensembles that are described by probability distributions. The problem is to reconstruct a probability distribution of the initial state from the time-evolution of the probability distribution of the…

Optimization and Control · Mathematics 2015-07-09 Shen Zeng , Steffen Waldherr , Christian Ebenbauer , Frank Allgower

In a recent Letter, Bennett and coworkers [1] argue that proofs of exotic quantum effects using closed timelike curves (CTC's) based on the work of Deutsch [2], or other nonlinear quantum dynamics, suffer from a fallacy that they call the…

Quantum Physics · Physics 2010-06-10 Eric G. Cavalcanti , Nicolas C. Menicucci

We give a closed form of the discrete-time evolution of a recombination transformation in population genetics. This decomposition allows to define a Markov chain in a natural way. We describe the geometric decay rate to the limit…

Probability · Mathematics 2016-03-24 Servet Martinez

A study of time homogeneous, real valued Markov processes with a special property and a non-atomic initial distribution is provided. The new notion of a function of evolution of distribution which determines the dependency between one…

Probability · Mathematics 2022-07-04 Tomasz Bielecki , Jacek Jakubowski , Maciej Wiśniewolski

The Dirac-Frenkel variational principle is a widely used building block for using nonlinear parametrizations in the context of model reduction and numerically solving partial differential equations; however, it typically leads to…

Numerical Analysis · Mathematics 2025-12-23 Yijun Dong , Paul Schwerdtner , Benjamin Peherstorfer

We consider the problem of tracking an unknown time varying parameter that characterizes the probabilistic evolution of a sequence of independent observations. To this aim, we propose a stochastic gradient descent-based recursive scheme in…

Statistics Theory · Mathematics 2023-03-01 Alberto Lanconelli , Christopher S. A. Lauria

We give a general method of deriving statistical limit theorems, such as the central limit theorem and its functional version, in the setting of ergodic measure preserving transformations. This method is applicable in situations where the…

Dynamical Systems · Mathematics 2008-04-15 Marta Tyran-Kaminska

The classical limit problem of quantum mechanics is revisited on the basis of a scheme that enables a quantitative study of the way the quantum-classical agreement emerges while going through the intermediate mass range between the…

Quantum Physics · Physics 2015-05-13 Dipankar Home , Alok Kumar Pan , Arka Banerjee

There is a growing interest, both from the theoretical as well as experimental side, to test the validity of the quantum superposition principle, and of theories which explicitly violate it by adding nonlinear terms to the Schr\"odinger…

Quantum Physics · Physics 2015-10-19 Angelo Bassi , Kasra Hejazi

Exponential averages that appear in integral fluctuation theorems can be recast as a sum over moments of thermodynamic observables. We use two examples to show that such moment series can exhibit non-uniform convergence in certain singular…

Statistical Mechanics · Physics 2022-05-31 Hila Katznelson , Saar Rahav

We introduce a linear space of finitely additive measures to treat the problem of optimal expected utility from consumption under a stochastic clock and an unbounded random endowment process. In this way we establish existence and…

General Finance · Quantitative Finance 2008-12-10 Gordan Zitkovic

The concept of time emerges as an ordering structure in a classical statistical ensemble. Probability distributions $p_\tau(t)$ at a given time $t$ obtain by integrating out the past and future. We discuss all-time probability distributions…

High Energy Physics - Theory · Physics 2015-05-18 C. Wetterich

We modify the path integral representation of exciton transport in open quantum systems such that an exact description of the quantum fluctuations around the classical evolution of the system is possible. As a consequence, the time…

Quantum Physics · Physics 2017-04-19 Anton Ivanov , Heinz-Peter Breuer

The research paper addresses linear decomposition of time series of non-additive metrics that allows for the identification and interpretation of contributing factors (input features) of variance. Non-additive metrics, such as ratios, are…

Machine Learning · Computer Science 2022-04-15 Alex Glushkovsky