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Non-Gaussian quantum states of light are critical resources for optical quantum information processing, but methods to generate them efficiently remain challenging to implement. Here we introduce a generic approach for non-Gaussian state…

We analyze the semiclassical evolution of Gaussian wavepackets in chaotic systems. We prove that after some short time a Gaussian wavepacket becomes a primitive WKB state. From then on, the state can be propagated using the standard TDWKB…

Chaotic Dynamics · Physics 2009-11-13 Raphael N. P. Maia , Fernando Nicacio , Raul O. Vallejos , Fabricio Toscano

The simulation of quantum processes is a key goal for the grand programme aiming at grounding quantum technologies as the way to explore complex phenomena that are inaccessible through standard, classical calculators. Some interesting steps…

Quantum Physics · Physics 2013-06-12 Andrea Chiuri , Chiara Greganti , Laura Mazzola , Mauro Paternostro , Paolo Mataloni

Based on the dispersion chain of the Vlasov equations, the paper considers the construction of a new chain of equations of quantum mechanics of high kinematical values. The proposed approach can be applied to consideration of classical and…

Mathematical Physics · Physics 2023-03-22 E. E. Perepelkin , B. I. Sadovnikov , N. G. Inozemtseva , A. A. Korepanova

Starting from Feynman's Lagrangian description of quantum mechanics, we propose a method to construct explicitly the propagator for the Wigner distribution function of a single system. For general quadratic Lagrangians, only the classical…

Quantum Physics · Physics 2017-05-11 Dries Sels , Fons Brosens , Wim Magnus

The analysis of fluctuation-dissipation relations developed in Giona et al. (2024) for particle hydromechanics is extended to stochastic forcings alternative to Wiener processes, with the aim of addressing the occurrence of Gaussian…

Statistical Mechanics · Physics 2024-12-30 Chiara Pezzotti , Massimiliano Giona , Giuseppe Procopio

Reaction diffusion systems describe the behaviour of dynamic, interacting, particulate systems. Quantum stochastic processes generalise Brownian motion and Poisson processes, having operator valued It\^{o} calculus machinery. Here it is…

Mathematical Physics · Physics 2023-05-31 Chris D Greenman

We construct from first principles a perturbative framework for studying nonequilibrium quantum-field systems that include gauge bosons. The system of our concern is quasiuniform system near equilibrium or nonequilibrium quasistationary…

High Energy Physics - Phenomenology · Physics 2016-08-16 A. Niégawa

Dynamics of a state of interest coupled to a non-Markovian environment is studied for the first time by concatenating the non-Markovian quantum state diffusion (QSD) equation and the Feshbach projection operator partitioning technique. An…

Quantum Physics · Physics 2012-04-05 Jun Jing , Lian-Ao Wu , J. Q. You , Ting Yu

We consider the asymptotic behavior of the fluctuations for the empirical measures of interacting particle systems with singular kernels. We prove that the sequence of fluctuation processes converges in distribution to a generalized…

Probability · Mathematics 2024-12-31 Zhenfu Wang , Xianliang Zhao , Rongchan Zhu

The nonnegative Wigner function of all quantum states involved in teleportation of Gaussian states using the standard continuous-variable teleportation protocol means that there is a local realistic phase-space description of the process.…

Quantum Physics · Physics 2009-11-10 Carlton M. Caves , Krzysztof Wodkiewicz

We study the filtering and smoothing problem for continuous-time linear Gaussian systems. While classical approaches such as the Kalman-Bucy filter and the Rauch-Tung-Striebel (RTS) smoother provide recursive formulas for the conditional…

Statistics Theory · Mathematics 2026-01-06 Masahiro Kurisaki

We consider Gaussian quantum circuits supplemented with non-Gaussian input states and derive sufficient conditions for efficient classical strong simulation of these circuits. In particular, we generalise the stellar representation of…

Quantum Physics · Physics 2021-07-14 Ulysse Chabaud , Giulia Ferrini , Frédéric Grosshans , Damian Markham

We revisit the phenomenon of the resonant transmission of fermionic carriers through a quantum device connected to two contacts with different chemical potentials. We show that, besides the traditional in solid-state physics…

Quantum Physics · Physics 2021-09-15 Andrey R. Kolovsky , Dmitrii N. Maksimov

The Fokker-Planck equations describe time evolution of probability densities of stochastic dynamical systems and are thus widely used to quantify random phenomena such as uncertainty propagation. For dynamical systems driven by non-Gaussian…

Dynamical Systems · Mathematics 2015-06-04 Xu Sun , Jinqiao Duan

This review covers recent theoretical and experimental efforts to extend the application of the continuous-variable quantum technology of light beyond "Gaussian" quantum states, such as coherent and squeezed states, into the domain of…

We present numerical schemes for the strong solution of linear stochastic differential equations driven by an arbitrary number of Wiener processes. These schemes are based on the Neumann (stochastic Taylor) and Magnus expansions. Firstly,…

Numerical Analysis · Mathematics 2007-08-22 Gabriel Lord , Simon J. A. Malham , Anke Wiese

Feynman path integrals provide an elegant, classically inspired representation for the quantum propagator and the quantum dynamics, through summing over a huge manifold of all possible paths. From computational and simulational…

Quantum Physics · Physics 2022-06-22 Yanming Che , Clemens Gneiting , Franco Nori

We investigate dynamics of Gaussian states of continuous variable systems under Gaussianity preserving channels. We introduce a hierarchy of such evolutions encompassing Markovian, weakly and strongly non-Markovian processes, and provide…

Typical generative diffusion models rely on a Gaussian diffusion process for training the backward transformations, which can then be used to generate samples from Gaussian noise. However, real world data often takes place in discrete-state…

Machine Learning · Computer Science 2023-05-19 Javier E Santos , Zachary R. Fox , Nicholas Lubbers , Yen Ting Lin
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