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We present approaches for the study of fluid-structure interactions subject to thermal fluctuations. A mixed mechanical description is utilized combining Eulerian and Lagrangian reference frames. We establish general conditions for…

Soft Condensed Matter · Physics 2023-02-28 Paul J. Atzberger

Self-consistent N-body simulations are efficient tools to study galactic dynamics. However, using them to study individual trajectories (or ensembles) in detail can be challenging. Such orbital studies are important to shed light on global…

Astrophysics of Galaxies · Physics 2015-06-17 T. Manos , Rubens E. G. Machado

Visual long-range interaction refers to modeling dependencies between distant feature points or blocks within an image, which can significantly enhance the model's robustness. Both CNN and Transformer can establish long-range interactions…

Computer Vision and Pattern Recognition · Computer Science 2023-03-13 Xiuxiu Bai , Shuaishuai Zhao , Yao Gao , Zhe Liu

An extension and generalization of a recently presented approach for the analysis of Langevin-type stochastic processes in the presence of strong measurement noise is presented. For a stochastic process in N dimensions which is superimposed…

Data Analysis, Statistics and Probability · Physics 2012-10-23 B. Lehle

The work distribution function for a non-relativistic, non-interacting quantum many-body system interacting with classical external sources is investigated. Exact expressions for the characteristic function corresponding to the work…

Quantum Physics · Physics 2020-04-22 Fardin Kheirandish

Positional ordering of a two-dimensional fluid of hard disks is examined in such narrow tubes where only the nearest-neighbor interactions take place. Using the exact transfer-matrix method the transverse and longitudinal pressure…

Statistical Mechanics · Physics 2015-05-30 S. Varga , G. Balló , P. Gurin

The dynamical control of energy transfer between interacting systems is fundamental in diverse applications related to physical, electronic and chemical processes. Recent developments show that noise may enhance or suppress power transfer…

Optics · Physics 2021-03-19 P. Bravo-Cassab , B. Jaramillo-Ávila , B. M. Rodríguez-Lara

We show that time-correlation functions of arbitrary order for any random variable in a statistical dynamical system can be calculated as higher-order response functions of the mean history of the variable. The response is to a ``control…

chao-dyn · Physics 2009-10-31 Gregory L. Eyink

We investigate the coupling relations among perturbations in general multi-field models. We derived the equations of motion for both background and perturbations in a general basis. Within this formalism, we revisit the construction of…

High Energy Physics - Theory · Physics 2015-06-16 Xian Gao

An interacting lattice model describing the subspace spanned by a set of strongly-correlated bands is rigorously coupled to density functional theory to enable ab initio calculations of geometric and topological material properties. The…

Strongly Correlated Electrons · Physics 2019-03-26 Ryan Requist , E. K. U. Gross

In this work we numerically investigate a new method for the characterization of growing length scales associated with spatially heterogeneous dynamics of glass-forming liquids. This approach, motivated by the formulation of the…

Disordered Systems and Neural Networks · Physics 2013-10-28 Kang Kim , Shinji Saito , Kunimasa Miyazaki , Giulio Biroli , David R. Reichman

We study many-body correlation functions within various Fundamental Measure Theory (FMT) formulations and compare their predictions to Monte Carlo simulations of hard-sphere fluids. FMT accurately captures the qualitative behavior of three-…

Chemical Physics · Physics 2025-10-30 Ilian Pihlajamaa , Teunike A. van de Pol , Liesbeth M. C. Janssen

Simultaneous recordings from multiple neural units allow us to investigate the activity of very large neural ensembles. To understand how large ensembles of neurons process sensory information, it is necessary to develop suitable…

Neurons and Cognition · Quantitative Biology 2013-05-30 Fernando Montani , Elena Phoka , Mariela Portesi , Simon R. Schultz

Molecular fluids show rich and complicated dynamics close to the glass transition. Some of these observations are related to the fact that translational and orientational degrees of freedom couple in nontrivial ways. A model system which…

Soft Condensed Matter · Physics 2017-08-23 M. Letz , R. Schilling

The thermodynamic formalism allows one to access the chaotic properties of equilibrium and out-of-equilibrium systems, by deriving those from a dynamical partition function. The definition that has been given for this partition function…

Statistical Mechanics · Physics 2011-11-29 Vivien Lecomte , Cécile Appert-Rolland , Frédéric van Wijland

Probing dynamic and static correlation in glass-forming supercooled liquids has been a challenge for decades in spite of extensive research. Dynamic correlation which manifests itself as Dynamic Heterogeneity is ubiquitous in a vast variety…

Statistical Mechanics · Physics 2021-09-22 Anoop Mutneja , Smarajit Karmakar

We derive relations between standard order parameter correlations and the noise correlations in time of flight images, which are valid for systems with long range order as well as low dimensional systems with algebraic decay of…

Other Condensed Matter · Physics 2011-05-31 L. Mathey , A. Vishwanath , E. Altman

The viability of a variant of numerical stochastic perturbation theory, where the Langevin equation is replaced by the SMD algorithm, is examined. In particular, the convergence of the process to a unique stationary state is rigorously…

High Energy Physics - Lattice · Physics 2017-06-02 Mattia Dalla Brida , Martin Lüscher

We report successful implementation of the time-dependent second-order many-body perturbation theory using optimized orthonormal orbital functions called time-dependent optimized second-order many-body perturbation theory [TD-OMP2] to reach…

Chemical Physics · Physics 2020-08-26 Himadri Pathak , Takeshi Sato , Kenichi L. Ishikawa

Stochastic reduced-order models are widely used to represent the effective dynamics of complex systems, but estimating their drift and diffusion coefficients from data remains challenging. Standard approaches often rely on short-time…

Machine Learning · Statistics 2026-04-28 Ludovico T. Giorgini
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