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We propose a simple method to estimate the parameters of a continuously measured quantum system, by fitting correlation functions of the measured signal. We demonstrate the approach in simulation, both on toy examples and on a recent…

Quantum Physics · Physics 2024-10-17 Pierre Guilmin , Pierre Rouchon , Antoine Tilloy

In this paper, we study smooth stochastic multi-level composition optimization problems, where the objective function is a nested composition of $T$ functions. We assume access to noisy evaluations of the functions and their gradients,…

Optimization and Control · Mathematics 2022-02-15 Krishnakumar Balasubramanian , Saeed Ghadimi , Anthony Nguyen

We propose a computationally efficient method to solve the dynamics of operators of bosonic quantum systems coupled to their environments. The method maps the operator under interest to a set of complex-valued functions, and its adjoint…

This paper is concerned with risk-sensitive performance analysis for linear quantum stochastic systems interacting with external bosonic fields. We consider a cost functional in the form of the exponential moment of the integral of a…

Optimization and Control · Mathematics 2017-07-31 Igor G. Vladimirov , Ian R. Petersen , Matthew R. James

We present embedding procedures for the non-Markovian stochastic Schr\"{o}dinger equations, arising from studies of quantum systems coupled with bath environments. By introducing auxiliary wave functions, it is demonstrated that the…

Computational Physics · Physics 2020-05-04 Xiantao Li

This paper presents a new numerical scheme for simulating stochastic processes specified by their marginal distribution functions and covariance functions. Stochastic samples are firstly generated to automatically satisfy target marginal…

Computational Physics · Physics 2020-08-11 Zhibao Zheng

High Reynolds numbers Navier-Stokes equations are believed to break self-similarity concerning both spatial and temporal properties: correlation functions of different orders exhibit distinct decorrelation times and anomalous spatial…

Fluid Dynamics · Physics 2012-10-04 Luca Biferale , Enrico Calzavarini , Federico Toschi

Dynamical maps are the principal subject of the open system theory. Formally, the dynamical map of a given open quantum system is a density matrix transformation that takes any initial state and sends it to the state at a later time.…

Quantum Physics · Physics 2025-09-03 Piotr Szańkowski

The lifted Heston model is a stochastic volatility model emerging as a Markovian lift of the rough Heston model and the class of rough volatility processes. The model encodes the path dependency of volatility on a set of N square-root state…

Mathematical Finance · Quantitative Finance 2025-10-13 Nicola F. Zaugg , Lech A. Grzelak

We introduce a multivariate stochastic volatility model for asset returns that imposes no restrictions to the structure of the volatility matrix and treats all its elements as functions of latent stochastic processes. When the number of…

Machine Learning · Statistics 2017-01-09 P. Dellaportas , A. Plataniotis , M. K. Titsias

We consider state and parameter estimation for a dynamical system having both time-varying and time-invariant parameters. It has been shown that the robustness of the Markov Chain Monte Carlo (MCMC) algorithm for estimating time-invariant…

Computational Engineering, Finance, and Science · Computer Science 2022-10-18 Philippe Bisaillon , Brandon Robinson , Mohammad Khalil , Chris L. Pettit , Dominique Poirel , Abhijit Sarkar

In this work we develop a stochastic algorithm to integrate the Cahn-Hilliard equations. The algorithm is based on Gillespie's stochastic simulation algorithm, also known as kinetic Monte Carlo. The deterministic integration of the phase…

Statistical Mechanics · Physics 2024-02-14 Qianran Yu , Nicholas Julian , Jaime Marian , Enrique Martinez

Simulation of open quantum systems is an area of active research in quantum algorithms. In this work, we revisit the connection between Markovian open-system dynamics and averages of Hamiltonian real-time evolutions, which we refer to as…

Quantum Physics · Physics 2026-01-28 Minbo Gao , Zhengfeng Ji , Chenghua Liu

Motivated by applications to multi-antenna wireless networks, we propose a distributed and asynchronous algorithm for stochastic semidefinite programming. This algorithm is a stochastic approximation of a continous- time matrix exponential…

Optimization and Control · Mathematics 2016-06-15 Bruno Gaujal , Panayotis Mertikopoulos

We present a Bayesian algorithm to identify generators of open quantum system dynamics, described by a Lindblad master equation, that are compatible with measured experimental data. The algorithm, based on a Markov Chain Monte Carlo…

Quantum Physics · Physics 2025-09-15 Stewart Wallace , Yoann Altmann , Brian D. Gerardot , Erik M. Gauger , Cristian Bonato

Stochastic volatility models are the backbone of financial engineering. We study both continuous time diffusions as well as discrete time models. We propose two novel approaches to estimating stochastic volatility diffusions, one using…

Quantum Physics · Physics 2025-07-30 Eric Ghysels , Jack Morgan , Hamed Mohammadbagherpoor

We consider a new formulation of the stochastic coupled cluster method in terms of the similarity transformed Hamiltonian. We show that improvement in the granularity with which the wavefunction is represented results in a reduction in the…

Chemical Physics · Physics 2016-02-02 Ruth S. T. Franklin , James S. Spencer , Alberto Zoccante , Alex J. W. Thom

We study the statistics of wave functions in a ballistic chaotic system. The statistical ensemble is generated by adding weak smooth disorder. The conjecture of Gaussian fluctuations of wave functions put forward by Berry and generalized by…

Mesoscale and Nanoscale Physics · Physics 2016-08-31 I. V. Gornyi , A. D. Mirlin

Stochastic representation for interaction of quantum systems is formulated which allows to replace some of them by equivalent but purely commutative random sources. The formalism is applied to two-level systems interacting with Gaussian…

Statistical Mechanics · Physics 2016-08-31 Yu. E. Kuzovlev

We propose and analyze the convergence of a novel stochastic forward-backward splitting algorithm for solving monotone inclusions given by the sum of a maximal monotone operator and a single-valued maximal monotone cocoercive operator. This…

Optimization and Control · Mathematics 2015-02-23 Lorenzo Rosasco , Silvia Villa , Bang Công Vũ
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