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In this work, we establish a direct connection between generative diffusion models (DMs) and stochastic quantization (SQ). The DM is realized by approximating the reversal of a stochastic process dictated by the Langevin equation,…

High Energy Physics - Lattice · Physics 2024-05-10 Lingxiao Wang , Gert Aarts , Kai Zhou

In practical implementation of quantum key distributions (QKD), it requires efficient, real-time feedback control to maintain system stability when facing disturbance from either external environment or imperfect internal components.…

Quantum Physics · Physics 2019-08-07 Jing-Yang Liu , Hua-Jian Ding , Chun-Mei Zhang , Shi-Peng Xie , Qin Wang

We study the convergence to equilibrium of an underdamped Langevin equation that is controlled by a linear feedback force. Specifically, we are interested in sampling the possibly multimodal invariant probability distribution of a Langevin…

Optimization and Control · Mathematics 2022-01-12 Tobias Breiten , Carsten Hartmann , Lara Neureither , Upanshu Sharma

By means of quantum stochastic calculus we construct a model for an atom with two degenerate levels and stimulated by a laser and we compute its fluorescence spectrum; let us stress that, once the model for the unitary atom-field dynamics…

Quantum Physics · Physics 2009-11-07 Alberto Barchielli , Nicola Pero

Numerically exact simulations of quantum reaction dynamics, including non-adiabatic effects in excited electronic states, are essential to gain fundamental insights into ultrafast chemical reactivity and rigorous interpretations of…

Chemical Physics · Physics 2022-09-01 Ningyi Lyu , Micheline B. Soley , Victor S. Batista

Stochastic Gradient Langevin Dynamics (SGLD) is a powerful algorithm for optimizing a non-convex objective, where a controlled and properly scaled Gaussian noise is added to the stochastic gradients to steer the iterates towards a global…

Optimization and Control · Mathematics 2020-06-04 Yuanhan Hu , Xiaoyu Wang , Xuefeng Gao , Mert Gurbuzbalaban , Lingjiong Zhu

We study propagation and on-off switching of two colliding soliton sequences in the presence of second-order dispersion, Kerr nonlinearity, linear loss, cubic gain, and quintic loss. Employing a Lotka-Volterra (LV) model for dynamics of…

Pattern Formation and Solitons · Physics 2015-06-16 Debananda Chakraborty , Avner Peleg , Jae-Hun Jung

A stochastic approach to the quantum dynamics randomly modulated in time by a discrete state non-Markovian noise, which possesses an arbitrary non-exponential distribution of the residence times, is developed. The formally exact expression…

Statistical Mechanics · Physics 2007-05-23 Igor Goychuk

Stochastic approximation (SA) is an iterative algorithm for finding the fixed point of an operator using noisy samples and widely used in optimization and Reinforcement Learning (RL). The noise in RL exhibits a Markovian structure, and in…

Machine Learning · Computer Science 2025-05-13 Shaan Ul Haque , Sajad Khodadadian , Siva Theja Maguluri

The complex Langevin method (CLM) offers a potential solution to the sign problem in quantum field theories with complex actions, but can converge to incorrect results even when simulations appear stable. Existing diagnostics monitor drift…

High Energy Physics - Lattice · Physics 2025-10-30 Anosh Joseph , Arpith Kumar

We introduce Lindblad-like quantum tomography (L$\ell$QT) as a quantum characterization technique of time-correlated noise in quantum information processors. This approach enables the estimation of time-local master equations, including…

Quantum Physics · Physics 2025-06-17 Santiago Varona , Markus Müller , Alejandro Bermudez

Two models are first presented, of one-dimensional discrete-time quantum walk (DTQW) with temporal noise on the internal degree of freedom (i.e., the coin): (i) a model with both a coin-flip and a phase-flip channel, and (ii) a model with…

Brillouin-Mandelstam scattering is one of the most accessible nonlinear optical phenomena and has been widely studied since its theoretical discovery one hundred years ago. The scattering mechanism is a three-wave-mixing process between two…

We consider the inverse problem of reconstructing the posterior measure over the trajec- tories of a diffusion process from discrete time observations and continuous time constraints. We cast the problem in a Bayesian framework and derive…

Machine Learning · Statistics 2016-12-21 Botond Cseke , David Schnoerr , Manfred Opper , Guido Sanguinetti

Linear response functions are a cornerstone concept in physics as they enable efficient estimation of many dynamical properties. In addition to predicting dynamics of observables under perturbations without resimulating the system, these…

Quantum Physics · Physics 2025-10-08 Xiantao Li , Chunhao Wang

We study the nonlinear driven dissipative quantum dynamics of an array of optomechanical systems. At each site of such an array, a localized mechanical mode interacts with a laser-driven cavity mode via radiation pressure, and both photons…

Quantum Physics · Physics 2013-09-05 Max Ludwig , Florian Marquardt

We provide the necessary framework for carrying out stochastic positive-P and gauge-P simulations of bosonic systems with long range interactions. In these approaches, the quantum evolution is sampled by trajectories in phase space,…

Quantum Physics · Physics 2017-07-19 S. Wüster , J. F. Corney , J. M. Rost , P. Deuar

We derive model equations for optical pulse propagation in a medium described by a two-level Hamiltonian, without the use of the slowly varying envelope approximation. Assuming that the resonance frequency of the two-level atoms is either…

Pattern Formation and Solitons · Physics 2007-05-23 Herve Leblond , Francois Sanchez

The analysis of a continuous measurement record $z(t)$ poses a fundamental challenge in quantum measurement theory. Different approaches have been used in the past as records can, e.g., exhibit predominantly Gaussian noise, telegraph noise,…

Quantum Physics · Physics 2024-06-12 Markus Sifft , Daniel Hägele

We present a quantum algorithm based on repeated measurement to solve initial-value problems for nonlinear ordinary differential equations (ODEs), which may be generated from partial differential equations in plasma physics. We map a…

Quantum Physics · Physics 2025-04-30 Joseph Andress , Alexander Engel , Yuan Shi , Scott Parker