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The memory function formalism is an important tool to evaluate the frequency dependent electronic conductivity. It is previously used within some approximations in the case of electrons interacting with various other degrees of freedom in…

Strongly Correlated Electrons · Physics 2016-04-25 Pankaj Bhalla , Nabyendu Das , Navinder Singh

An explicit expression is derived for the scattering function of a self-avoiding polymer chain in a $d$-dimensional space. The effect of strength of segment interactions on the shape of the scattering function and the radius of gyration of…

Statistical Mechanics · Physics 2007-05-23 A. D. Drozdov

We show that the aging dynamics of a strong glass former displays a strikingly simple scaling behavior, connecting the average dynamics with its fluctuations, namely the dynamical heterogeneities. We perform molecular dynamics simulations…

Disordered Systems and Neural Networks · Physics 2016-07-27 Katharina Vollmayr-Lee , Christopher H. Gorman , Horacio E. Castillo

By means of molecular dynamics simulations we examine the aging process of a strong glass former, a silica melt modeled by the BKS potential. The system is quenched from a temperature above to one below the critical temperature, and the…

Disordered Systems and Neural Networks · Physics 2007-05-23 H. Wahlen , H. Rieger

We perform Discrete Element Method (DEM) simulations of granular particles (polystyrene spheres) vibrated inside a cubic container. The study investigates the evolution of the packing fraction with and without rotational friction at…

Soft Condensed Matter · Physics 2026-03-03 Linnea Heitmeier , Jan Gabriel

Neural surrogates for molecular scattering provide a route to continuously evaluable and differentiable direct simulation Monte Carlo (DSMC) collision kernels, but a small pointwise deflection-angle error is not sufficient evidence that a…

Chemical Physics · Physics 2026-05-26 Ehsan Roohi

Glassy silica is a foundational material in optics and electronics, yet accurately predicting its medium-range order (MRO) remains a major challenge for machine-learning interatomic potentials (MLIPs). While local MLIPs reproduce the…

Materials Science · Physics 2026-04-24 Sai Harshit Balantrapu , Atul C. Thakur , Chris Benmore , Ganesh Sivaraman

We report short-term memory formation in a nonlinear dynamical system with many degrees of freedom. The system ``remembers'' a sequence of impulses for a transient period, but it coarsens and eventually ``forgets'' nearly all of them. The…

We study the nonlinear rheology of a glass-forming binary mixture under the reversal of shear flow using molecular dynamics simulations and a schematic model of the mode-coupling theory of the glass transition (MCT). Memory effects lead to…

Soft Condensed Matter · Physics 2015-06-12 Fabian Frahsa , Amit Kumar Bhattacharjee , Jürgen Horbach , Matthias Fuchs , Thomas Voigtmann

We present a machine learning algorithm for the prediction of molecule properties inspired by ideas from density functional theory. Using Gaussian-type orbital functions, we create surrogate electronic densities of the molecule from which…

Chemical Physics · Physics 2019-11-27 Michael Eickenberg , Georgios Exarchakis , Matthew Hirn , Stéphane Mallat , Louis Thiry

Random projections have proven extremely useful in many signal processing and machine learning applications. However, they often require either to store a very large random matrix, or to use a different, structured matrix to reduce the…

Emerging Technologies · Computer Science 2016-08-26 Alaa Saade , Francesco Caltagirone , Igor Carron , Laurent Daudet , Angélique Drémeau , Sylvain Gigan , Florent Krzakala

We study the problem of reconstructing interaction kernels in systems of interacting agents from macroscopic measurements when posed as an optimization problem. The reconstruction procedure depends on the formulation of the forward model,…

Numerical Analysis · Mathematics 2026-04-03 Peiyi Chen , Qin Li , Li Wang , Yunan Yang

We relate the memory kernel in the Nakajima-Zwanzig-Mori time-convolution approach to the reduced system propagator which is often used to obtain the kernel in the Tokuyama-Mori time-convolutionless approach. The connection provides a…

Other Condensed Matter · Physics 2018-09-14 Lyran Kidon , Haobin Wang , Michael Thoss , Eran Rabani

Incoherent neutron scattering experiments are simulated for simple dynamic models: a glass (with a smooth distribution of harmonic vibrations) and a viscous liquid (described by schematic mode-coupling equations). In most situations…

Soft Condensed Matter · Physics 2009-10-31 Joachim Wuttke

We investigate the quality of structural models generated by the Reverse Monte Carlo (RMC) method in a typical application to amorphous systems. To this end we calculate surrogate diffraction data from a Li2O-SiO2 molecular dynamics (MD)…

Materials Science · Physics 2009-09-08 Christian R. Mueller , Vindu Kathriarachchi , Michael Schuch , Philipp Maass , Valeri Petkov

Fractionally integrated time series, exhibiting long memory with slowly decaying autocorrelations, are frequently encountered in economics, finance, and related fields. Since the seminal work of Robinson (1995), a variety of semiparametric…

Econometrics · Economics 2025-12-17 Jason R. Blevins

Exact expressions are derived for the intermediate scattering function (ISF) of a quantum particle diffusing in a harmonic potential and linearly coupled to a harmonic bath. The results are valid for arbitrary strength and spectral density…

Quantum Physics · Physics 2018-08-15 Peter S. M. Townsend , Alex W. Chin

The complex behavior of confined fluids arising due to a competition between layering and local packing can be disentangled by considering quasi-confined liquids, where periodic boundary conditions along the confining direction restore…

Soft Condensed Matter · Physics 2020-09-03 Lukas Schrack , Charlotte F. Petersen , Gerhard Jung , Michele Caraglio , Thomas Franosch

Given additional distributional information in the form of moment restrictions, kernel density and distribution function estimators with implied generalised empirical likelihood probabilities as weights achieve a reduction in variance due…

Methodology · Statistics 2019-10-08 Vitaliy Oryshchenko , Richard J. Smith

Studies of the dynamics of a quantum system coupled to baths are typically performed by utilizing the Nakajima-Zwanzig memory kernel (${\mathcal{K}}$) or the influence functions ($\mathbf{{I}}$), especially when the dynamics exhibit memory…

Quantum Physics · Physics 2024-06-05 Felix Ivander , Lachlan P. Lindoy , Joonho Lee