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We upper- and lower-bound the optimal precision with which one can estimate an unknown Hamiltonian parameter via measurements of Gibbs thermal states with a known temperature. The bounds depend on the uncertainty in the Hamiltonian term…

After a sudden disruption, weakly interacting quantum systems first relax to a prethermalized state that can be described by perturbation theory and a generalized Gibbs ensemble. Using these properties of the prethermalized state we…

Strongly Correlated Electrons · Physics 2013-08-27 Michael Stark , Marcus Kollar

The application of a random modulation of a system parameter usually increases decoherence effects. Here we show how, employing an appropriate stochastic modulation, it is instead possible to preserve the quantum coherence of a system.

Quantum Physics · Physics 2009-11-07 Stefano Mancini , David Vitali , Paolo Tombesi , Rodolfo Bonifacio

It is notorious that quantum mechanics cannot predict well-defined values for all physical quantities. Less well-known, however, is the fact that quantum mechanics is unable to furnish -- without additional assumptions -- probabilistic…

Quantum Physics · Physics 2025-09-24 Matheus V. Scherer , Alexandre D. Ribeiro , Renato M. Angelo

This paper investigates dynamical relaxation to quantum equilibrium in the stochastic de Broglie-Bohm-Bell formulation of quantum mechanics. The time-dependent probability distributions are computed as in a Markov process with slowly…

Quantum Physics · Physics 2023-02-01 Jeroen C. Vink

Existing deterministic variational inference approaches for diffusion processes use simple proposals and target the marginal density of the posterior. We construct the variational process as a controlled version of the prior process and…

Machine Learning · Computer Science 2021-03-02 Christian Wildner , Heinz Koeppl

The experimental detection of multipartite entanglement usually requires a number of appropriately chosen local quantum measurements which are aligned with respect to a previously shared common reference frame. The latter, however, can be a…

Quantum Physics · Physics 2019-04-02 Andreas Ketterer , Nikolai Wyderka , Otfried Gühne

We propose novel goodness-of-fit tests for the Weibull distribution with unknown parameters. These tests are based on an alternative characterizing representation of the Laplace transform related to the density approach in the context of…

Statistics Theory · Mathematics 2022-06-15 Bruno Ebner , Adrian Fischer , Norbert Henze , Celeste Mayer

Increasingly larger data sets of processes in space and time ask for statistical models and methods that can cope with such data. We show that the solution of a stochastic advection-diffusion partial differential equation provides a…

Methodology · Statistics 2016-02-18 Fabio Sigrist , Hans R. Künsch , Werner A. Stahel

In this tutorial, we present the definition, interpretation and properties of some of the main quasiprobabilities that can describe the statistics of measurement outcomes evaluated at two or more times. Such statistics incorporate the…

Quantum Physics · Physics 2024-09-23 Stefano Gherardini , Gabriele De Chiara

We propose an algorithm based on modulable hidden variables and adaptive step lengths, inspired by heuristic statistical physics and the replica method, to study the effect of mutual correlations and the emergent Wigner-Dyson distribution…

Statistical Mechanics · Physics 2026-05-27 Chen-Huan Wu

We describe a previously unexplored effect of the continuous spontaneous localization model whereby a correlation develops in the distributions of two nearby non-interacting particles following a period of diffusion. We propose the use of…

Quantum Physics · Physics 2014-11-27 Daniel Bedingham

This paper deals with partially-observed optimal control problems for the state governed by stochastic differential equation with delay. We develop a stochastic maximum principle for this kind of optimal control problems using a variational…

Optimization and Control · Mathematics 2020-10-15 Shuaiqi Zhang , Xun Li , Jie Xiong

Quantum dynamics simulations can be improved using novel quasiprobability distributions based on non-orthogonal hermitian kernel operators. This introduces arbitrary functions (gauges) into the stochastic equations, which can be used to…

Quantum Physics · Physics 2009-11-07 P. Deuar , P. D. Drummond

Switching dynamical systems provide a powerful, interpretable modeling framework for inference in time-series data in, e.g., the natural sciences or engineering applications. Since many areas, such as biology or discrete-event systems, are…

Machine Learning · Computer Science 2021-09-30 Lukas Köhs , Bastian Alt , Heinz Koeppl

Given a stochastic structure with a filtration $\mathbb{F}$, the class of all random times whose conditional distribution functions are differentiable with respect to some $\mathbb{F}$ adapted non decreasing processes is considered. The…

Probability · Mathematics 2013-12-20 Shiqi Song

The problem of simulating the thermal behavior of quantum systems remains a central open challenge in quantum computing. Unlike well-established quantum algorithms for unitary dynamics, \emph{provably efficient} algorithms for preparing…

Quantum Physics · Physics 2026-05-14 Dominik Hahn , Ryan Sweke , Abhinav Deshpande , Oles Shtanko

In this paper, we study the diffusion approximation for singularly perturbed stochastic reaction-diffusion equation with a fast oscillating term. The asymptotic limit for the original system is obtained, where an extra Gaussian term…

Probability · Mathematics 2021-06-08 Longjie Xie , Li Yang

We consider the impact that temporal correlations in the measurement statistics can have on the achievable precision in a sequential metrological protocol. In this setting, and for a single quantum probe, we establish that it is the…

Quantum Physics · Physics 2024-04-02 Eoin O'Connor , Steve Campbell , Gabriel T. Landi

The recently established connection between stochastic thermodynamics and fluctuating hydrodynamics is applied to a study of efficiencies in the coupled transport of heat and matter on a small scale. A stochastic model for a mesoscopic cell…

Statistical Mechanics · Physics 2019-04-01 Jean-François Derivaux , Yannick De Decker
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