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Complex systems such as glasses, gels, granular materials, and systems far from equilibrium exhibit violation of the ergodic hypothesis (EH) and of the fluctuation-dissipation theorem (FDT). Recent investigations in systems with memory have…

Disordered Systems and Neural Networks · Physics 2007-05-23 M. H. Vainstein , I. V. L. Costa , F. A. Oliveira

We propose a scenario for the glass transition based on the cooperative nature of nucleation processes and entropic effects. The main point is the relation between the off-equilibrium energy dissipation and nucleation processes in…

Soft Condensed Matter · Physics 2009-11-07 A. Crisanti , F. Ritort

This thesis describes the development of the density matrix embedding theory (DMET) and its applications to lattice strongly correlated electron problems, including a review of DMET theory and algorithms (Ch 2), investigation of finite size…

Strongly Correlated Electrons · Physics 2018-03-29 Bo-Xiao Zheng

We consider the effect of droplet excitations in the random first order transition theory of glasses on the configurational entropy. The contribution of these excitations is estimated both at and above the ideal glass transition…

Statistical Mechanics · Physics 2009-11-07 M. P. Eastwood , P. G. Wolynes

We introduce a notion of viscosity solutions for a nonlinear degenerate diffusion equation with a drift potential. We show that our notion of solutions coincide with the weak solutions defined via integration by parts. As an application of…

Analysis of PDEs · Mathematics 2009-10-20 I. C. Kim , H. K. Lei

Polymers near the glass transition temperature Tg often exhibit a breakdown of time-temperature-superposition (TTS), with chain relaxation times and viscosity exhibiting a weaker temperature dependence than segmental relaxation times. The…

Soft Condensed Matter · Physics 2024-03-05 Peijing Yue , David S. Simmons

We analyze isothermal aging of a four dimensional Edwards-Anderson model in detail by Monte Carlo simulations. We analyze the data in the view of an extended version of the droplet theory proposed recently (cond-mat/0202110) which is based…

Disordered Systems and Neural Networks · Physics 2009-11-07 Hajime Yoshino , Koji Hukushima , Hajime Takayama

For soft matter systems strongly driven by stationary flow, we discuss an extended fluctuation-dissipation theorem (FDT). Beyond the linear response regime, the FDT for the stress acquires an additional contribution involving the observable…

Soft Condensed Matter · Physics 2009-05-29 Thomas Speck , Udo Seifert

We apply divergence-type theory (DTT) dissipative hydrodynamics to study the 2+1 space-time evolution of the fireball created in Au+Au relativistic heavy-ion collisions at $\sqrt{s_{NN}}=$200 GeV. DTTs are exact hydrodynamic theories that…

High Energy Physics - Phenomenology · Physics 2010-12-02 J. Peralta-Ramos , E. Calzetta

We develop a computational method based on Dissipative Particle Dynamics (DPD) that introduces solvent hydrodynamic interactions to coarse-grained models of solutes, such as ions, molecules, or polymers. DPD-solvent (DPDS) is a fully…

Soft Condensed Matter · Physics 2024-05-24 Tine Curk

The detailed fluctuation theorem (DFT) is a statement about the asymmetry in the statistics of the entropy production. Consequences of the DFT are the second law of thermodynamics and the thermodynamics uncertainty relation (TUR), which…

Statistical Mechanics · Physics 2022-10-19 Domingos S. P. Salazar

Bayesian models based on Gaussian processes (GPs) offer a flexible framework to predict spatially distributed variables with uncertainty. But the use of nonstationary priors, often necessary for capturing complex spatial patterns, makes…

Machine Learning · Statistics 2025-06-02 Gabriel V Cardoso , Mike Pereira

In a fluid out of equilibrium, the fluctuation dissipation theorem (FDT) is usually violated. Using molecular dynamics simulations, we study in detail the relationship between correlation and response functions in a fluid driven into a…

Disordered Systems and Neural Networks · Physics 2009-10-31 Jean-Louis Barrat , Ludovic Berthier

The decentralized gradient descent (DGD) algorithm, and its sibling, diffusion, are workhorses in decentralized machine learning, distributed inference and estimation, and multi-agent coordination. We propose a novel, principled framework…

Signal Processing · Electrical Eng. & Systems 2025-06-04 Erik G. Larsson , Nicolo Michelusi

We discuss issues related to thermalization of plastic flow in the context of soft glassy rheology (SGR) theory. An apparent problem with the theory in its current form is that the stationarity of thermomechanical equilibrium obtained by…

Soft Condensed Matter · Physics 2018-06-07 Robert S. Hoy

Chemical structure has been long recognized to greatly influence polymer glass formation, but a general molecular theory that predicts how chemical structure determines the properties of glass-forming polymers has been slow to develop.…

Soft Condensed Matter · Physics 2017-11-01 Wen-Sheng Xu , Karl F. Freed

We extend classical Flory-Rehner theory for the expansion and compression of porous materials such as cross-linked polymer networks. The theory includes volume exclusion, affinity with the solvent, and finite stretching of the polymer…

Chemical Physics · Physics 2023-09-28 P. M. Biesheuvel , H. Fan , M. Elimelech

We consider holographic theories at finite temperature in which a continuous global symmetry in the bulk is spontaneously broken. We study the linear response of operators in a regime which is dual to time dependent, long wavelength…

High Energy Physics - Theory · Physics 2020-01-08 Aristomenis Donos , Daniel Martin , Christiana Pantelidou , Vaios Ziogas

We have connected the dynamic fragility, namely the rapidity of the relaxation time increase upon temperature reduction, to the excess entropy and heat capacity of a large number of glass-forming polymers. The connection was obtained in a…

Soft Condensed Matter · Physics 2009-11-11 D. Cangialosi , A. Alegria , J. Colmenero

Crystal structure determination from powder diffraction patterns is a complex challenge in materials science, often requiring extensive expertise and computational resources. This study introduces DiffractGPT, a generative pre-trained…

Materials Science · Physics 2025-08-13 Kamal Choudhary
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