English
Related papers

Related papers: Direct Interaction Approximation for Non-Markovian…

200 papers

An approach, called discretized environment method, is introduced to treat exactly non-Markovian effects in open quantum systems. In this approach, a complex environment described by a spectral function is mapped into a finite set of…

Quantum Physics · Physics 2015-06-22 Denis Lacroix , V. V. Sargsyan , G. G. Adamian , N. V. Antonenko

We consider systems of damped wave equations with a state-dependent damping coefficient and perturbed by a Gaussian multiplicative noise. Initially, we investigate their well-posedness, under quite general conditions on the friction.…

Probability · Mathematics 2023-12-15 Sandra Cerrai , Arnaud Debussche

We consider the Bayesian approach to the linear Gaussian inference problem of inferring the initial condition of a linear dynamical system from noisy output measurements taken after the initial time. In practical applications, the large…

Systems and Control · Electrical Eng. & Systems 2021-11-29 Elizabeth Qian , Jemima M. Tabeart , Christopher Beattie , Serkan Gugercin , Jiahua Jiang , Peter R. Kramer , Akil Narayan

We consider a Markov chain $(x_n)$ whose kernel is indexed by a scaling parameter $\gamma>0$, refered to as the step size. The aim is to analyze the behavior of the Markov chain in the doubly asymptotic regime where $n\to\infty$ then…

Probability · Mathematics 2017-12-18 Pascal Bianchi , Walid Hachem , Adil Salim

The aim of this paper is to propose a new method for numerical approximations of the solution of the linear stochastic partial differential equation arising in non-linear filtering problems: the Zaka\"i equation. The approximation scheme is…

Probability · Mathematics 2012-10-26 Bruno Saussereau

Measures characterizing the non-Markovianity degree of the quantum dynamics have several drawbacks when applied to real devices. They depend on the chosen measurement time interval and are highly sensitive to experimental noise and errors.…

We present a deep learning approximation, stochastic optimization based, method for wave kinetic equations. To build confidence in our approach, we apply the method to a Smoluchowski coagulation equation with multiplicative kernel for which…

Numerical Analysis · Mathematics 2022-09-27 Steven Walton , Minh-Binh Tran , Alain Bensoussan

We study the response of wind tunnel turbulence to perturbations using an active grid. We compare our findings to Kraichnan's linear response result $R(k,\tau_d) = \exp(-k^2 \: \tau_d^2 \: u^2)$ which predicts a decay of the response with…

Fluid Dynamics · Physics 2025-08-08 H. E. Cekli , G. Bertens , W van de Water

Non-Markovian dynamics is studied for two interacting quibts strongly coupled to a dissipative bosonic environment. For the first time, we have derived the non-Markovian quantum state diffusion (QSD) equation for the coupled two-qubit…

Quantum Physics · Physics 2011-09-07 Xinyu Zhao , Jun Jing , Brittany Corn , Ting Yu

Model of laminated wave turbulence allows to study statistical and discrete layers of turbulence in the frame of the same model. Statistical layer is described by Zakharov-Kolmogorov energy spectra in the case of irrational enough…

Mathematical Physics · Physics 2007-09-27 Elena Kartashova , Alexey Kartashov

In this paper, we present a discrete-type approximation scheme to solve continuous-time optimal stopping problems based on fully non-Markovian continuous processes adapted to the Brownian motion filtration. The approximations satisfy…

Probability · Mathematics 2019-06-24 Dorival Leão , Alberto Ohashi , Francesco Russo

We study well-posedness for fluid-structure interaction driven by stochastic forcing. This is of particular interest in real-life applications where forcing and/or data have a strong stochastic component. The prototype model studied here is…

Analysis of PDEs · Mathematics 2021-04-27 Jeffrey Kuan , Suncica Canic

Simulating atmospheric turbulence is an essential task for evaluating turbulence mitigation algorithms and training learning-based methods. Advanced numerical simulators for atmospheric turbulence are available, but they require evaluating…

Optics · Physics 2020-06-24 Nicholas Chimitt , Stanley H. Chan

A large variety of problems in statistical physics use a Gaussian distribution as a starting point. For the problem of intermittency in fluid turbulence, the Gaussian approximation is not a useful beginning. We find that the Cramer's rate…

Statistical Mechanics · Physics 2008-11-04 Jayanta Kumar Bhattacharjee , Sagar Chakraborty , Arnab Saha

Stokesian Dynamics (SD) is a numerical framework used for simulating hydrodynamic interactions in particle suspensions at low Reynolds number. It combines far-field approximations with near-field lubrication corrections, offering a balance…

Fluid Dynamics · Physics 2025-03-21 Kim William Torre , Joost de Graaf

This work presents Direct Numerical Simulations of capillary wave turbulence solving the full 3D Navier Stokes equations of a two-phase flow. When the interface is locally forced at large scales, a statistical stationary state appears after…

Fluid Dynamics · Physics 2014-07-21 Luc Deike , Daniel Fuster , Michaël Berhanu , Eric Falcon

We have derived an expression of the Dzyaloshinskii-Moriya (DM) interaction, where all the three components of the DM vector can be calculated independently, for a general, non-collinear magnetic configuration. The formalism is implemented…

The eikonal approximation (EA) is widely used in various high-energy scattering problems. In this work we generalize this approximation from the scattering problems with time-independent Hamiltonian to the ones with periodical Hamiltonians,…

Quantum Physics · Physics 2024-09-10 Yaru Liu , Peng Zhang

We study a model that intermediates among the wave, heat, and transport equations. The approach considers the propagation of initial disturbances in a one-dimensional medium that can vibrate. The medium is nonlinear in such a form that…

Mathematical Physics · Physics 2019-05-15 Fernando Olivar-Romero , Oscar Rosas-Ortiz

Interference alignment (IA) is a cooperative transmission strategy that improves spectral efficiency in high signal-to-noise ratio (SNR) environments, yet performs poorly in low-SNR scenarios. This limits IA's utility in cellular systems as…

Information Theory · Computer Science 2013-05-14 Jonathan Starr , Omar El Ayach , Robert W. Heath
‹ Prev 1 4 5 6 7 8 10 Next ›