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We derive a mode-coupling theory for the slow dynamics of fluids confined in disordered porous media represented by spherical particles randomly placed in space. Its equations display the usual nonlinear structure met in this theoretical…

Soft Condensed Matter · Physics 2007-05-23 V. Krakoviack

Considering the matter power spectrum covariance matrix, it has recently been found that there is a potentially dominant effect on mildly non-linear scales due to power in modes of size equal to and larger than the survey volume. This {\it…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-03 Roland de Putter , Christian Wagner , Olga Mena , Licia Verde , Will Percival

In an attempt to extend the mode coupling theory (MCT) to lower temperatures, an Unified theory was proposed which within the MCT framework incorporated the activated dynamics via the random first order transition theory (RFOT). Here we…

Soft Condensed Matter · Physics 2020-01-08 Manoj Kumar Nandi , Sarika Maitra Bhattacharyya

A self-consistent mode coupling theory (MCT) with microscopic inputs of equilibrium pair correlation functions is developed to analyze electrolyte dynamics. We apply the theory to calculate concentration dependence of (i) time dependent ion…

Statistical Mechanics · Physics 2015-01-09 Susmita Roy , Subramanian Yashonath , Biman Bagchi

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 asymmetric simple exclusion process and its analysis by mode coupling theory (MCT) is reviewed. To treat the weakly asymmetric case at large space scale $x\varepsilon^{-1}$, %(corresponding to small Fourier momentum at scale…

Statistical Mechanics · Physics 2023-06-27 G. M. Schütz

Exploratory factor analysis is often used in the social sciences to estimate potential measurement models. To do this, several important issues need to be addressed: (1) determining the number of factors, (2) learning constraints in the…

Methodology · Statistics 2025-05-28 Dale S. Kim , Audrey Lu , Qing Zhou

Optimal transport (OT) theory underlies many emerging machine learning (ML) methods nowadays solving a wide range of tasks such as generative modeling, transfer learning and information retrieval. These latter works, however, usually build…

Machine Learning · Statistics 2021-12-03 Quang Huy Tran , Hicham Janati , Ievgen Redko , Rémi Flamary , Nicolas Courty

We introduce a hybrid approach for computing dynamical observables in strongly correlated systems using higher-order moments. This method integrates memory kernel coupling theory (MKCT) with the density matrix renormalization group (DMRG),…

Computational Physics · Physics 2025-09-17 Yunhao Liu , Wenjie Dou

What happens when multiple compression methods are combined-does the order in which they are applied matter? Joint model compression has emerged as a powerful strategy to achieve higher efficiency by combining multiple methods such as…

Artificial Intelligence · Computer Science 2026-03-20 Minjun Kim , Jaehyeon Choi , Hyunwoo Yang , Jongjin Kim , Jinho Song , U Kang

The only available quantitative description of the slowing down of the dynamics upon approaching the glass transition has been, so far, the mode-coupling theory, developed in the 80's by G\"otze and collaborators. The standard derivation of…

Statistical Mechanics · Physics 2012-06-11 Hugo Jacquin , Frédéric Van Wijland

Generalization to novel compound tasks under distribution shift is important for deploying transformer-based language models (LMs). This work investigates Chain-of-Thought (CoT) reasoning as a means to enhance OOD generalization. Through…

Computation and Language · Computer Science 2026-03-31 Ru Wang , Wei Huang , Selena Song , Haoyu Zhang , Qian Niu , Yusuke Iwasawa , Yutaka Matsuo , Jiaxian Guo

Coupled mode theory (CMT) is a powerful framework for decomposing interactions between electromagnetic waves and scattering bodies into resonances and their couplings with power-carrying channels. It has widespread use in few-resonance,…

Optics · Physics 2020-10-22 Hanwen Zhang , Owen D. Miller

The charge-transfer (CT) together with the polarization energy appears at second and higher orders in symmetry-adapted perturbation theory (SAPT). At present there is no theoretically compelling way of isolating the charge-transfer energy…

Chemical Physics · Physics 2013-08-07 Alston J. Misquitta

The physical pictures of eigen-mode theory (EMT) and the conventional characteristic mode theory (CMT) reveal a fact that: the EMT and CMT are the modal theories for electromagnetic wave-guiding and scattering (for details, please see the…

Signal Processing · Electrical Eng. & Systems 2021-03-03 Renzun Lian

A simplified Ginzburg-Landau theory is presented to study generally a coupling of a first-order phase transition (FOPT) to a second-order phase transition (SOPT). We show analytically that, due to the coupling between the two phase…

Condensed Matter · Physics 2007-05-23 Fan Zhong

We investigate entanglement properties of a recently introduced class of macroscopic quantum superpositions in two-mode mixed states. One of the tools we use in order to infer the entanglement in this non-Gaussian class of states is the…

Quantum Physics · Physics 2009-11-11 M. Paternostro , H. Jeong , M. S. Kim

The predictions of the mode-coupling theory of the glass transition (MCT) for the tagged-particle density-correlation functions and the mean-squared displacement curves are compared quantitatively and in detail to results from Newtonian-…

Statistical Mechanics · Physics 2009-11-10 Th. Voigtmann , A. M. Puertas , M. Fuchs

We present molecular dynamics simulations on the structural relaxation of a simple bead-spring model for polymer blends. The introduction of a different monomer size induces a large time scale separation for the dynamics of the two…

Soft Condensed Matter · Physics 2009-11-13 A. J. Moreno , J. Colmenero

Chain-of-Thought (CoT) reasoning is known to improve Large Language Models both empirically and in terms of theoretical approximation power. However, our understanding of the inner workings and conditions of apparition of CoT capabilities…

Machine Learning · Computer Science 2024-10-29 Vivien Cabannes , Charles Arnal , Wassim Bouaziz , Alice Yang , Francois Charton , Julia Kempe