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A non-Markovian stochastic Schroedinger equation for a quantum system coupled to an environment of harmonic oscillators is presented. Its solutions, when averaged over the noise, reproduce the standard reduced density operator without any…

Quantum Physics · Physics 2009-10-31 Walter T Strunz , Lajos Diosi , Nicolas Gisin

Two-stage stochastic programming is a problem formulation for decision-making under uncertainty. In the first stage, the actor makes a best "here and now" decision in the presence of uncertain quantities that will be resolved in the future,…

We address a long-standing criticism of the stochastic mechanics approach to quantum theory by one of its pioneers, Edward Nelson: multi-time correlations in stochastic mechanics differ from those in textbook quantum theory. We elaborate…

Quantum Physics · Physics 2023-08-14 Maaneli Derakhshani , Guido Bacciagaluppi

A semiclassical diagrammatic approach is constructed for calculating correlation functions of observables in open chaotic systems with time reversal symmetry. The results are expressed in terms of classical correlation functions involving…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 Oded Agam

We consider stochastic volatility models using piecewise constant parameters. We suggest a hybrid optimization algorithm for fitting the models to a volatility surface and provide some numerical results. Finally, we provide an outlook on…

Pricing of Securities · Quantitative Finance 2010-10-07 Wolfgang Putschoegl

We develop a statistical description of chaotic wavefunctions in closed systems obeying arbitrary boundary conditions by combining a semiclassical expression for the spatial two-point correlation function with a treatment of eigenfunctions…

Chaotic Dynamics · Physics 2013-05-29 Juan Diego Urbina , Klaus Richter

We develop an extension of the Monte Carlo wave function approach that unambiguously identifies dynamical entanglement in general composite, open systems. Our algorithm performs tangential projections onto the set of separable states,…

Quantum Physics · Physics 2026-01-21 Laura Ares , Julien Pinske , Benjamin Hinrichs , Martin Kolb , Jan Sperling

Stochastic approximation is a framework unifying many random iterative algorithms occurring in a diverse range of applications. The stability of the process is often difficult to verify in practical applications and the process may even be…

Probability · Mathematics 2014-03-10 Christophe Andrieu , Matti Vihola

Previous years researchers began to simulate open quantum system, taking into account the interaction between system and the environment. One approach to deal with this problem is to use the density matrix within the Liouville-von-Neumann…

Quantum Physics · Physics 2025-09-15 Mohammad Attrash , Roi Baer

A quantum stochastic model for an open dynamical system (quantum receiver) and output multi-channel of observation with an additive nonvacuum quantum noise is given. A quantum stochastic Master equation for the corresponding instrument is…

Quantum Physics · Physics 2015-06-26 V. P. Belavkin

We show that the dynamics of a quantum system can be represented by the dynamics of an underlying classical systems obeying the Hamilton equations of motion. This is achieved by transforming the phase space of dimension $2n$ into a Hilbert…

Statistical Mechanics · Physics 2023-08-02 Mário j. de Oliveira

In this paper, we present an overview of the recent developments of functional quantization of stochastic processes, with an emphasis on the quadratic case. Functional quantization is a way to approximate a process, viewed as a…

Probability · Mathematics 2013-04-03 Gilles Pagès

We consider the wave equation with highly oscillatory initial data, where there is uncertainty in the wave speed, initial phase and/or initial amplitude. To estimate quantities of interest related to the solution and their statistics, we…

Numerical Analysis · Mathematics 2015-09-11 Gabriela Malenova , Mohammad Motamed , Olof Runborg , Raul Tempone

We introduce a hybrid classical-quantum algorithm to compute dynamical correlation functions and excitation spectra in many-body quantum systems, with a focus on molecular systems. The method combines classical preparation of a perturbed…

Quantum Physics · Physics 2025-10-30 Alessandro Santini , Stefano Barison , Filippo Vicentini

We present quantum algorithms for solving two problems regarding stochastic processes. The first algorithm prepares the thermal Gibbs state of a quantum system and runs in time almost linear in $\sqrt{N \beta/{\cal Z}}$ and polynomial in…

Quantum Physics · Physics 2017-01-11 Anirban Narayan Chowdhury , Rolando D. Somma

Stochastic quantization in physics has been considered to provide a path integral representation of a probability distribution for Ito processes. It has been indicated that the stochastic quantization can involve a potential term, if the…

Systems and Control · Computer Science 2020-05-05 Masakazu Sano

We present a systematic way to analyze and model systems having many characteristic time-scales. The method we propose is employed for a test-case of a meandering jet model manifesting chaotic tracer dispersion with long time-correlations.…

Chaotic Dynamics · Physics 2007-05-23 M. Abel , K. H. Andersen , G. Lacorata

We present a novel method to simulate the Lindblad equation, drawing on the relationship between Lindblad dynamics, stochastic differential equations, and Hamiltonian simulations. We derive a sequence of unitary dynamics in an enlarged…

Quantum Physics · Physics 2024-08-27 Zhiyan Ding , Xiantao Li , Lin Lin

Firstly, the Markovian stochastic Schr\"odinger equations are presented, together with their connections with the theory of measurements in continuous time. Moreover, the stochastic evolution equations are translated into a simulation…

Quantum Physics · Physics 2014-03-17 I. Semina , V. Semin , F. Petruccione , A. Barchielli

Understanding the precise interaction mechanisms between quantum systems and their environment is crucial for advancing stable quantum technologies, designing reliable experimental frameworks, and building accurate models of real-world…