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Ferroelectricity in atomically thin bilayer structures has been recently predicted1 and measured[2-4] in two-dimensional (2D) materials with hexagonal non-centrosymmetric unit-cells. Interestingly, the crystal symmetry translates lateral…

Intracellular recordings of cortical neurons in vivo display intense subthreshold membrane potential (Vm) activity. The power spectral density (PSD) of the Vm displays a power-law structure at high frequencies (>50 Hz) with a slope of about…

Neurons and Cognition · Quantitative Biology 2009-11-13 Claude Bedard , Alain Destexhe

The electrophoretic behaviour of flexible polyelectrolyte chains ranging from single monomers up to long fragments of hundred repeat units is studied by a mesoscopic simulation approach. Abstracting from the atomistic details of the…

Soft Condensed Matter · Physics 2015-05-13 Kai Grass , Christian Holm

Computational prediction of protein structures is a difficult task, which involves fast and accurate evaluation of candidate model structures. We propose to enhance single model quality assessment with a functionality evaluation phase for…

Biomolecules · Quantitative Biology 2016-01-12 Witold Dyrka , Monika Kurczyńska , Bogumił M. Konopka , Małgorzata Kotulska

This note outlines the exact solution to the power flow problem in AC electrical networks under the assumption of 'flat' or uniform voltage profiles. This solution generalises the common 'DC power flow' approach to electrical network…

History and Overview · Mathematics 2022-07-26 Anthony B. Morton

We study ionic liquids interacting with electrified interfaces. The ionic fluid is modeled as a Coulomb lattice gas. We compare the ionic density profiles calculated using a popular modified Poisson-Boltzmann equation with the explicit…

Soft Condensed Matter · Physics 2017-12-21 Matheus Girotto , Thiago Colla , Alexandre P. dos Santos , Yan Levin

Chemical potential is an effective way to drive phase transition or express wettability. In this letter, we present a chemical-potential-based lattice Boltzmann model to simulate multiphase flows. The nonideal force is directly evaluated by…

Computational Physics · Physics 2017-06-21 Binghai Wen , Xuan Zhou , Bing He , Chaoying Zhang , Haiping Fang

Neural network models are known to reinforce hidden data biases, making them unreliable and difficult to interpret. We seek to build models that `know what they do not know' by introducing inductive biases in the function space. We show…

Machine Learning · Computer Science 2021-12-21 Lassi Meronen , Martin Trapp , Arno Solin

We analyze the optical pump-probe reflection and transmission coefficients when the photoinduced response depends nonlinearly on the incident pump intensity. Under these conditions, we expect the photoconductivity depth profile to change…

Strongly Correlated Electrons · Physics 2024-10-30 Leya Lopez , Derek G. Sahota , J. Steven Dodge

It is a common assumption that the activation of different layers in neural networks follow Gaussian distribution. This distribution can be transformed using normalization techniques, such as batch-normalization, increasing convergence…

Machine Learning · Computer Science 2020-10-19 Andras Horvath , Jalal Al-afandi

Multiconfiguration expansions frequently target valence correlation and correlation between valence electrons and the outermost core electrons. Correlation within the core is often neglected. A large orbital basis is needed to saturate both…

Atomic Physics · Physics 2010-04-20 S. Verdebout , P. Jönsson , G. Gaigalas , M. Godefroid , C. Froese Fischer

A coarse-grained version of the Lattice Boltzmann (LB) method is developed with the intent of enhancing its geometrical flexibility so as to be able to tackle a wider class of flows of engineering interest. To this purpose, the original…

comp-gas · Physics 2015-06-24 Giorgio Amati , Sauro Succi , Roberto Benzi

We present polarisation profiles for 48 southern pulsars observed with the new 10-cm receiver at the Parkes telescope. We have exploited the low system temperature and high bandwidth of the receiver to obtain profiles which have good signal…

Astrophysics · Physics 2009-11-10 A. Karastergiou , S. Johnston , R. N. Manchester

We introduce a direct Boltzmann inversion method to infer the interaction potential in particle systems using as input particle configurations generated at an arbitrary state point of the system. Unlike iterative Boltzmann inversion, the…

Statistical Mechanics · Physics 2026-05-25 Olivier Coquand , Davide Paolino , Ludovic Berthier

An approach based on a lattice version of the Boltzmann kinetic equation for describing multi-phase flows in nano- and micro-corrugated devices is proposed. We specialize it to describe the wetting/dewetting transition of fluids in presence…

Cellular Automata and Lattice Gases · Physics 2007-06-13 R. Benzi , L. Biferale , M. Sbragaglia , S. Succi , F. Toschi

The observed polarization of radio pulsars involves several peculiar effects, such as comparable amount of orthogonal polarization modes (OPMs) which often bear the same handedness of circular polarisation V. In the average profiles of…

High Energy Astrophysical Phenomena · Physics 2018-08-22 J. Dyks

We map molecular dynamics simulations of fluid-fluid interfaces onto mesoscale continuum theories for partially miscible fluids. Unlike most previous work, we examine not only the interface order parameter and density profiles, but also the…

Soft Condensed Matter · Physics 2009-11-10 Colin Denniston , Mark O. Robbins

Motivated by the fact that full diversity order is achieved using the "best-relay" selection technique, we consider opportunistic amplify-and-forward and decode-and-forward relaying systems. We focus on the outage probability of such a…

Information Theory · Computer Science 2016-11-15 Ashkan Kalantari , Mohammadali Mohammadi , Mehrdad Ardebilipour

We introduce a novel mesoscopic computational model based on a multiphase-multicomponent lattice Boltzmann method for the simulation of self-phoretic particles in the presence of liquid-liquid interfaces. Our model features fully resolved…

Soft Condensed Matter · Physics 2022-06-22 Lucas Palacios , Andrea Scagliarini , Ignacio Pagonabarraga

Methodologies for training machine learning potentials (MLPs) to quantum-mechanical simulation data have recently seen tremendous progress. Experimental data has a very different character than simulated data, and most MLP training…

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