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This paper aims at using the functional renormalization group formalism to study the equilibrium states of a stochastic process described by a quench--disordered multilinear Langevin equation. Such an equation characterizes the evolution of…

High Energy Physics - Theory · Physics 2023-01-16 Vincent Lahoche , Dine Ousmane Samary , Mohamed Ouerfelli

Reliable numerical computation of quantum dynamics is a fundamental challenge when the long-ranged quantum entanglement plays essential roles as in the cases governed by quantum criticality in strongly correlated systems. Here we apply a…

Quantum Physics · Physics 2025-01-24 Ryui Kaneko , Masatoshi Imada , Yoshiyuki Kabashima , Tomi Ohtsuki

A machine-learning strategy for investigating the stability of fluid flow problems is proposed herein. The goal is to provide a simple yet robust methodology to find a nonlinear mapping from the parametric space to an indicator representing…

Fluid Dynamics · Physics 2026-01-06 David J. Silvester

This work develops quantized local reduced-order models (ql-ROMs) of the turbulent Minimal Flow Unit (MFU) for the analysis and interpretation of intermittent dissipative dynamics and extreme events. The ql-ROM combines data-driven…

Fluid Dynamics · Physics 2025-11-07 Antonio Colanera , Luca Magri

We present an alternative "encapsulated" formulation of the Selective Frequency Damping method for finding unstable equilibria of dynamical systems, which is particularly useful when analysing the stability of fluid flows. The formulation…

Fluid Dynamics · Physics 2015-06-18 Bastien E. Jordi , C. J. Cotter , Spencer J. Sherwin

A data-driven, model-free approach to modeling the temporal evolution of physical systems mitigates the need for explicit knowledge of the governing equations. Even when physical priors such as partial differential equations are available,…

Machine Learning · Computer Science 2026-03-12 Siyuan Chen , Zhecheng Wang , Yixin Chen , Yue Chang , Peter Yichen Chen , Eitan Grinspun , Jonathan Panuelos

The time evolution of one- and two-dimensional discrete-time quantum walk with increase in disorder is studied. We use spatial, temporal and spatio-temporal broken periodicity of the unitary evolution as disorder to mimic the effect of…

Quantum Physics · Physics 2013-05-17 C. M. Chandrashekar

Turbulent dynamical systems characterized by both a high-dimensional phase space and a large number of instabilities are ubiquitous among many complex systems in science and engineering. The existence of a strange attractor in the turbulent…

Fluid Dynamics · Physics 2018-02-23 Andrew J. Majda , Di Qi

We introduce a diagrammatic quantum field formalism for the evaluation of normalized expectation values of operators, and suitable for systems with localized electrons. It is used to develop a convergent series expansion for the energy in…

Other Condensed Matter · Physics 2009-11-13 S. A. Bonev , N. W. Ashcroft

We explore the free boson unitary dynamics subject to repeated random forced measurement. The input state is chosen as a Fock state in real space with the particle number conserved in the entire dynamics. We show that each boson is…

Quantum Physics · Physics 2021-10-26 Xiao Chen

The question of how the low-energy properties of disordered quantum systems may be connected to exotic localization phenomena at high energy is a key open question in the context of quantum glasses and many-body localization. In…

Disordered Systems and Neural Networks · Physics 2021-08-31 L. Villa , S. J. Thomson , L. Sanchez-Palencia

Normalizing flow is a generative modeling approach with efficient sampling. However, Flow-based models suffer two issues: 1) If the target distribution is manifold, due to the unmatch between the dimensions of the latent target distribution…

Machine Learning · Computer Science 2024-04-24 Qinglong Meng , Chongkun Xia , Xueqian Wang

We propose a hybrid variational framework that enhances Neural Quantum States (NQS) with a Normalising Flow-based sampler to improve the expressivity and trainability of quantum many-body wavefunctions. Our approach decouples the sampling…

Quantum Physics · Physics 2025-06-17 Vishal S. Ngairangbam , Michael Spannowsky , Timur Sypchenko

We propose a scheme for data-driven parameterization of unresolved dimensions of dynamical systems based on the mathematical framework of quantum mechanics and Koopman operator theory. Given a system in which some components of the state…

Dynamical Systems · Mathematics 2022-08-09 David Freeman , Dimitrios Giannakis , Joanna Slawinska

The spatial localization of quantum states plays a central role in condensed-matter phenomena, ranging from many-body localization to topological matter. Building on the dissipation-fluctuation theorem, we propose that the localization…

Mesoscale and Nanoscale Physics · Physics 2019-11-20 Tomoki Ozawa , Nathan Goldman

We develop an efficient numerical method to study the quantum critical behavior of disordered systems with $\mathcal{O}(N)$ order-parameter symmetry in the large$-N$ limit. It is based on the iterative solution of the large$-N$ saddle-point…

Statistical Mechanics · Physics 2015-06-15 David Nozadze , Thomas Vojta

It has become increasingly clear that a full understanding of the physics of electrons in disordered systems requires an approach in which both disorder and interactions are taken into account. Work on small numbers of electrons has…

Disordered Systems and Neural Networks · Physics 2007-05-23 Jonathan M Carter , Angus MacKinnon

Despite its numerical challenges, finite element method is used to compute viscous fluid flow. A consensus on the cause of numerical problems has been reached; however, general algorithms---allowing a robust and accurate simulation for any…

Computational Engineering, Finance, and Science · Computer Science 2019-02-05 Bilen Emek Abali

Computational Fluid Dynamics (CFD) is central to science and engineering, but faces severe scalability challenges, especially in high-dimensional, multiscale, and turbulent regimes. Traditional numerical methods often become prohibitively…

This paper proposes a novel method for solving and tracing power flow solutions with changes of a loading parameter. Different from the conventional continuation power flow method, which repeatedly solves static AC power flow equations, the…

Dynamical Systems · Mathematics 2022-03-10 Yang Liu , Kai Sun , Jiaojiao Dong