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We discuss the physics of momentum diffusion in a charged plasma. Following the holographic strategy outlined in arXiv:2012.03999 we construct an open effective field theory for the low-lying modes of the conserved currents. The charged…

High Energy Physics - Theory · Physics 2022-05-10 Temple He , R. Loganayagam , Mukund Rangamani , Julio Virrueta

We study the general problem of mixing for ab-initio quantum-mechanical problems. Guided by general mathematical principles and the underlying physics, we propose a multisecant form of Broydens second method for solving the self-consistent…

Materials Science · Physics 2025-06-05 L. D. Marks , D. R. Luke

We develop methods to learn the correlation potential for a time-dependent Kohn-Sham (TDKS) system in one spatial dimension. We start from a low-dimensional two-electron system for which we can numerically solve the time-dependent…

Machine Learning · Statistics 2022-12-08 Harish S. Bhat , Kevin Collins , Prachi Gupta , Christine M. Isborn

Spatially correlated noise (SCN), i.e. the thermal noise that affects neighbouring particles in a similar manner, is ubiquitous in soft matter systems. In this work, we apply the over-damped SCN-driven Langevin equations as an effective,…

Soft Condensed Matter · Physics 2019-12-30 M. Majka , P. F. Góra

Atomic partial charges appear in the Coulomb term of many force-field models and can be derived from electronic structure calculations with a myriad of atoms-in-molecules (AIM) methods. More advanced models have also been proposed, using…

Highly accurate measurements of quantum level energies in molecular systems provide a test ground for new physics, as such effects could manifest themselves as minute shifts in the quantum level structures of atoms and molecules. For the…

High Energy Physics - Phenomenology · Physics 2015-03-17 Beatriz Gato-Rivera

We present a hybrid continuum-atomistic scheme which combines molecular dynamics (MD) simulations with on-the-fly machine learning techniques for the accurate and efficient prediction of multiscale fluidic systems. By using a Gaussian…

Fluid Dynamics · Physics 2016-03-16 David Stephenson , James R Kermode , Duncan A Lockerby

Absolute binding energies of core electrons in molecules and bulk materials can be efficiently calculated by spin paired density-function theory employing a $\Delta$ Kohn-Sham ($\Delta$KS) scheme corrected by offsets that are highly…

Materials Science · Physics 2016-08-03 Michael Walter , Michael Moseler , Lars Pastewka

Metal-organic frameworks show both fundamental interest and great promise for applications in adsorption-based technologies, such as the separation and storage of gases. The flexibility and complexity of the molecular scaffold poses a…

We present a method aimed at sampling charge density fluctuations in Coulomb systems. The derivation follows from a functional integral representation of the partition function in terms of charge density fluctuations. Starting from the…

Soft Condensed Matter · Physics 2016-03-21 Frédéric Poitevin , Marc Delarue , Henri Orland

Rechargeable battery electrodes have highly complex microstructures, consisting of nonuniform electrode particles, tortuous electrolyte channels, and irregular particle-electrolyte interfaces. Moreover, the electrochemical processes involve…

Materials Science · Physics 2026-03-26 Hui-Chia Yu , Bernardo Orvananos , Scott Cronin , Martin Bazant , Scott Barnett , K. Thornton

Graph-based linear scaling electronic structure theory for quantum-mechanical molecular dynamics simulations is adapted to the most recent shadow potential formulations of extended Lagrangian Born-Oppenheimer molecular dynamics, including…

Chemical Physics · Physics 2023-03-08 Christian F. A. Negre , Michael E. Wall , Anders M. N. Niklasson

We study the long-time behavior of the (critical) Kohn--Sham equation in two and three dimensions, i.e.,\[ \mathrm{i} \partial_t {\gamma} = \Big[-\frac{1}{2}\Delta + \lambda \, |\cdot|^{-1} \ast \rho_{{\gamma}} + \mu \,…

Analysis of PDEs · Mathematics 2026-05-29 Masaki Kawamoto , Jinyeop Lee , Changhun Yang , Chanjin You

We present the extension of the quantum/classical polarizable fluctuating charge model to the calculation of single residues of quadratic response functions, as required for the computational modeling of two-photon absorption…

Computational Physics · Physics 2022-10-28 Roberto Di Remigio , Tommaso Giovannini , Matteo Ambrosetti , Chiara Cappelli , Luca Frediani

Nuclear shadowing in DIS at moderately small $x$ is suppressed by the nuclear formfactor and depends on the effective mass of a hadronic fluctuation of the virtual photon. We propose a solution to the problems (i) of how to combine a…

High Energy Physics - Phenomenology · Physics 2009-10-31 B. Z. Kopeliovich , J. Raufeisen , A. V. Tarasov

Atomic Force Microscopy (AFM) combined with electrical modes provides a powerful contactless approach to characterize material electrical properties at the nanoscale. However, conventional electrostatic models often overlook dynamic charge…

Mesoscale and Nanoscale Physics · Physics 2025-08-26 Mario Navarro-Rodriguez , Paul Philip Schmidt , Regina Hoffmann-Vogel , Andres M. Somoza , Elisa Palacios-Lidon

We revisit the statistical mechanics of charge fluctuations in capacitors. In constant-potential classical molecular simulations, the atomic charge of electrode atoms are treated as additional degrees of freedom which evolve in time so as…

We introduce two approaches to modeling the quantum dynamics of optical $\chi^{(3)}$ solitons. Taking an open-system viewpoint, we project the underlying quantum field into system (soliton) and residual reservoir components. The reservoir…

Quantum Physics · Physics 2026-05-25 Chris Gustin , Ryotatsu Yanagimoto , Edwin Ng , Hideo Mabuchi

We propose a hybrid model, coupling Lattice Boltzmann and Molecular Dynamics models, for the simulation of dense fluids. Time and length scales are decoupled by using an iterative Schwarz domain decomposition algorithm. The MD and LB…

Soft Condensed Matter · Physics 2015-06-25 A. Dupuis , E. M. Kotsalis , P. Koumoutsakos

Dynamic Mode Decomposition (DMD) is a data-driven method for approximating the spatiotemporal modes of a system. The eigenvectors and eigenvalues of the system are approximated from a series of time-snapshots of the state variables. The…

Computational Engineering, Finance, and Science · Computer Science 2026-04-17 William Bennett , Ryan G. McClarren , Ethan Smith , Melek Derman