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We describe an efficient numerical method for simulating the dynamics of interacting spin ensembles in the presence of dephasing and decay. The method builds on the discrete truncated Wigner approximation for isolated systems, which…

Quantum Physics · Physics 2022-02-01 Julian Huber , Ana Maria Rey , Peter Rabl

We introduce a methodology for seeking conservation laws within a Hamiltonian dynamical system, which we term ``neural deflation''. Inspired by deflation methods for steady states of dynamical systems, we propose to {iteratively} train a…

Pattern Formation and Solitons · Physics 2023-03-29 Wei Zhu , Hong-Kun Zhang , P. G. Kevrekidis

Extreme values and the tail behavior of probability distributions are essential for quantifying and mitigating risk in complex systems of all kinds. In multivariate settings, accounting for correlations is crucial. Although extreme value…

Statistical Finance · Quantitative Finance 2026-03-06 Benjamin Köhler , Anton J. Heckens , Thomas Guhr

We propose a machine learning based approach to develop the exchange-correlation potential of time dependent density functional theory (TDDFT). The neural network projection from the time-varying electron densities to the corresponding…

Computational Physics · Physics 2020-05-20 Yasumitsu Suzuki , Ryo Nagai , Jun Haruyama

Considering an $N$-level system interacting factorizably with a continuous spectrum, we derive analytical expressions for the bound states and the dynamical evolution within this single-excitation Friedrichs model by using the projection…

Quantum Physics · Physics 2025-12-22 Jia-Ming Zhang , Yu Xin , Bing Chen

The generic behavior of quantum systems has long been of theoretical and practical interest. Any quantum process is represented by a sequence of quantum channels. We consider general ergodic sequences of stochastic channels with arbitrary…

Quantum Physics · Physics 2022-07-08 Ramis Movassagh , Jeffrey Schenker

Moving beyond simple associations, researchers need tools to quantify how variables influence each other in space and time. Correlation functions provide a mathematical framework for characterizing these essential dependencies, revealing…

Statistical Mechanics · Physics 2025-10-15 Henrique A. de Lima , Ismael S. S. Carrasco , Marcio Santos , Fernando A. Oliveira

In systems with detailed balance, the stationary distribution and the equilibrium distribution are identical, creating a clear connection between energetic and entropic quantities. Many driven systems violate detailed balance and still pose…

Statistical Mechanics · Physics 2025-01-22 Markus Hofer , Jan Korbel , Rudolf Hanel , Stefan Thurner

We devise an iterative scheme for numerically calculating dynamical two-point correlation functions in integrable many-body systems, in the Eulerian scaling limit. Expressions for these were originally derived in Ref. [1] by combining the…

Statistical Mechanics · Physics 2021-01-01 Frederik S. Møller , Gabriele Perfetto , Benjamin Doyon , Jörg Schmiedmayer

The correlation functions near higher-order glass-transition singularities are discussed for a schematic two-component model within the mode-coupling theory for ideal glass-transitions. The correlators decay in leading order like…

Soft Condensed Matter · Physics 2007-05-23 Matthias Sperl

For over 30 years, mode-coupling theory (MCT) has been the de facto theoretic description of dense fluids and the liquid-glass transition. MCT, however, is limited by its ad hoc construction and lacks a mechanism to institute corrections.…

Soft Condensed Matter · Physics 2015-08-12 David D. McCowan

The correlation properties of the nonaffine elastic response in strongly disordered materials are investigated using the theory of correlated random matrices and supported by numerical models. While the nonaffine displacement field itself…

Disordered Systems and Neural Networks · Physics 2026-04-09 D. A. Conyuh , D. V. Babin , I. O. Raikov , Y. M. Beltukov

In this paper, models that approximate stochastic processes from the space $Sub_\varphi(\Omega)$ with given reliability and accuracy in $L_p(T)$ are considered for some specific functions $\varphi(t)$. For processes that are decomposited in…

Statistics Theory · Mathematics 2025-03-25 Oleksandr Mokliachuk

Learning meaningful representations that disentangle the underlying structure of the data generating process is considered to be of key importance in machine learning. While disentangled representations were found to be useful for diverse…

Correlations between factors of variation are prevalent in real-world data. Exploiting such correlations may increase predictive performance on noisy data; however, often correlations are not robust (e.g., they may change between domains,…

Machine Learning · Computer Science 2022-12-26 Christina M. Funke , Paul Vicol , Kuan-Chieh Wang , Matthias Kümmerer , Richard Zemel , Matthias Bethge

We present a model of discrete quantum evolution based on quantum correlations between the evolving system and a reference quantum clock system. A quantum circuit for the model is provided, which in the case of a constant Hamiltonian is…

Quantum Physics · Physics 2016-07-06 A. Boette , R. Rossignoli , N. Gigena , M. Cerezo

We identify peak and valley structures in the exact exchange-correlation potential of time-dependent density functional theory that are crucial for time-resolved electron scattering in a model one-dimensional system. These structures are…

Chemical Physics · Physics 2018-01-03 Yasumitsu Suzuki , Lionel Lacombe , Kazuyuki Watanabe , Neepa T. Maitra

Learning meaningful and compact representations with disentangled semantic aspects is considered to be of key importance in representation learning. Since real-world data is notoriously costly to collect, many recent state-of-the-art…

Our motivation in this paper is twofold. First, we study the geometry of a class of exploration sets, called exit sets, which are naturally associated with a 2D vector-valued GFF : $\phi : Z^2 \to R^N, N\geq 1$. We prove that, somewhat…

Probability · Mathematics 2022-12-14 Juhan Aru , Christophe Garban , Avelio Sepúlveda

This is the second paper in a cycle investigating the exact solution of loop equations in decaying turbulence. We perform numerical simulations of the Euler ensemble, suggested in the previous work, as a solution to the loop equations. We…

Fluid Dynamics · Physics 2024-03-04 Alexander Migdal