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Related papers: Quantum Stochastic Generators

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In this lecture we present a brief outline of boson Fock space stochastic calculus based on the creation, conservation and annihilation operators of free field theory, as given in the 1984 paper of Hudson and Parthasarathy. We show how a…

Mathematical Physics · Physics 2014-12-02 K. R. Parthasarathy

The applicability of machine learning for predicting chaotic dynamics relies heavily upon the data used in the training stage. Chaotic time series obtained by numerically solving ordinary differential equations embed a complicated noise of…

Data Analysis, Statistics and Probability · Physics 2021-10-13 Igor A Khovanov

We study the structure of the ground states of local stoquastic Hamiltonians and show that under mild assumptions the following distributions can efficiently approximate one another: (a) distributions arising from ground states of…

Quantum Physics · Physics 2020-11-20 Robbie King , Sergii Strelchuk

Combining intuitive probabilistic assumptions with the basic laws of classical thermodynamics, using the latter to express probabilistic parameters in terms of the thermodynamic quantities, we get a simple unified derivation of the…

Probability · Mathematics 2022-05-03 Vassili N. Kolokoltsov

We study the relationship between the classical Hamilton flow and the quantum Schr\"odinger evolution where the Hamiltonian is a degree-2 complex-valued polynomial. When the flow obeys a strict positivity condition equivalent to compactness…

Analysis of PDEs · Mathematics 2017-01-05 Joe Viola

In this paper we develop a fractional Hamiltonian formulation for dynamic systems defined in terms of fractional Caputo derivatives. Expressions for fractional canonical momenta and fractional canonical Hamiltonian are given, and a set of…

Mathematical Physics · Physics 2009-11-11 Dumitru Baleanu , Om P. Agrawal

Normalizing flows, diffusion normalizing flows and variational autoencoders are powerful generative models. This chapter provides a unified framework to handle these approaches via Markov chains. We consider stochastic normalizing flows as…

Machine Learning · Computer Science 2023-02-06 Paul Hagemann , Johannes Hertrich , Gabriele Steidl

We perturb with an additive Gaussian white noise the Hamiltonian system associated to a cubic anharmonic oscillator. The stochastic system is assumed to start from initial conditions that guarantee the existence of a periodic solution for…

Probability · Mathematics 2019-07-26 Enrico Bernardi , Alberto Lanconelli

This paper introduces a novel deep-learning-based approach for numerical simulation of a time-evolving Schr\"odinger equation inspired by stochastic mechanics and generative diffusion models. Unlike existing approaches, which exhibit…

Machine Learning · Computer Science 2024-09-19 Elena Orlova , Aleksei Ustimenko , Ruoxi Jiang , Peter Y. Lu , Rebecca Willett

We present new stochastic differential equations, that are more general and simpler than the existing Ito-based stochastic differential equations. As an example, we apply our approach to the investment (portfolio) model.

Portfolio Management · Quantitative Finance 2012-11-27 Moawia Alghalith

Langevin equation with a multiplicative stochastic force is considered. That force is uncorrelated, it has the L\'evy distribution and the power-law intensity. The Fokker-Planck equations, which correspond both to the It\^o and Stratonovich…

Statistical Mechanics · Physics 2015-05-13 Tomasz Srokowski

This book covers a wide range of problems involving the applications of stochastic processes, stochastic calculus, large deviation theory, group representation theory and quantum statistics to diverse fields in dynamical systems,…

Mathematical Physics · Physics 2021-08-13 Harish Parthasarathy

We adapt the notion of generating functions for lagrangian submanifolds to symplectic microgeometry. We show that a symplectic micromorphism always admits a global generating function. As an application, we describe hamiltonian flows as…

Symplectic Geometry · Mathematics 2020-03-13 Alberto S. Cattaneo , Benoit Dherin , Alan Weinstein

Collective modes propagating in a moving superfluid are known to satisfy wave equations in a curved space time, with a metric determined by the underlying superflow. We use the Keldysh technique in a curved space-time to develop a quantum…

Quantum Gases · Physics 2018-07-03 Aydin Cem Keser , Victor Galitski

Multiplicative cascades have been introduced in turbulence to generate random or deterministic fields having intermittent values and long-range power-law correlations. Generally this is done using discrete construction rules leading to…

Statistical Mechanics · Physics 2007-05-23 Francois G. Schmitt

This paper compares the results of applying a recently developed method of stochastic uncertainty quantification designed for fluid dynamics to the Born-Infeld model of nonlinear electromagnetism. The similarities in the results are…

Mathematical Physics · Physics 2019-01-15 Darryl D. Holm

We study the coarse-graining approach to derive a generator for the evolution of an open quantum system over a finite time interval. The approach does not require a secular approximation but nevertheless generally leads to a…

Statistical Mechanics · Physics 2020-05-08 Gernot Schaller , Julian Ablaßmayer

In this contribution we sketch a branch-cut quantum formulation of the Wheeler-DeWitt equation analytically continued to the complex plane. As a starting point, we base our approach on the Ho\v{r}ava-Lifshitz formulation of gravity, which…

General Relativity and Quantum Cosmology · Physics 2022-12-08 Peter O. Hess , César A. Zen Vasconcellos , José de Freitas Pacheco , Dimiter Hadjimichef , Benno Bodmann

Stochastic field theories are often constructed phenomenologically, without a systematic assessment of thermodynamic consistency or local detailed balance. This may hinder a physical description of irreversibility at the field-theoretic…

Statistical Mechanics · Physics 2026-04-29 Héctor Vaquero del Pino , François Gay-Balmaz , Hiroaki Yoshimura , Lock Yue Chew

This article proposes a method for forming invariant stochastic differential systems, namely dynamic systems with trajectories belonging to a given smooth manifold. The It\^o or Stratonovich stochastic differential equations with the Wiener…

Probability · Mathematics 2026-02-03 Konstantin A. Rybakov