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This paper introduces a Monte Carlo method for maximum likelihood inference in the context of discretely observed diffusion processes. The method gives unbiased and a.s.\@ continuous estimators of the likelihood function for a family of…

Statistics Theory · Mathematics 2009-03-03 Alexandros Beskos , Omiros Papaspiliopoulos , Gareth Roberts

Employing a classical density-functional description of liquid environments, we introduce a rigorous method for the diffusion quantum Monte Carlo calculation of free energies and thermodynamic averages of solvated systems that requires…

Deposits of dipolar particles are investigated by means of extensive Monte Carlo simulations. We found that the effect of the interactions is described by an initial, non-universal, scaling regime characterized by orientationally ordered…

Statistical Mechanics · Physics 2009-11-10 F. de los Santos , J. M. Tavares , M. Tasinkevych , M. M. Telo da Gama

We study lithium systems over a range of number of atoms, e.g., atomic anion, dimer, metallic cluster, and body-centered cubic crystal by the diffusion Monte Carlo method. The calculations include both core and valence electrons in order to…

Computational Physics · Physics 2015-07-29 Kevin Rasch , Lubos Mitas

We investigate the phase behaviour of random copolymers melts via large scale Monte Carlo simulations. We observe macrophase separation into A and B--rich phases as predicted by mean field theory only for systems with a very large…

Soft Condensed Matter · Physics 2009-11-07 J. Houdayer , M. Mueller

Over the past decade, experimental microscopy and spectroscopy have made significant progress in the study of the morphological, optical, electronic and transport properties of materials. These developments include higher spatial…

Materials Science · Physics 2025-02-12 Simone Taioli , Maurizio Dapor

Diffusion in an evolving environment is studied by continuos-time Monte Carlo simulations. Diffusion is modelled by continuos-time random walkers on a lattice, in a dynamic environment provided by bubbles between two one-dimensional…

Soft Condensed Matter · Physics 2010-11-22 Janne Juntunen , Juha Merikoski

We discuss the successes of the dynamical mean field (DMF) approach to metal insulator transitions in both the clean and the disordered limit. In the latter case, standard DMF equations are generalized in order to incorporate both the…

Disordered Systems and Neural Networks · Physics 2009-10-30 V. Dobrosavljevic , G. Kotliar

We present a Monte Carlo approach to incorporating the effect of thermal fluctuations in field theories of polymeric fluids. This method is applied to a field-theoretic model of a ternary blend of AB diblock copolymers with A and B…

Materials Science · Physics 2009-11-10 Dominik Düchs , Venkat Ganesan , Glenn H. Fredrickson , Friederike Schmid

Diffusion-driven processes are important phenomena of materials science in the field of energy conversion and transmission. During the conversion from chemical energy to electrical energy, the species diffusion is generally linked to the…

Applied Physics · Physics 2021-02-23 Jay Santoki

We propose an algorithm for molecular dynamics or Monte Carlo simulations that uses an interpolation procedure to estimate potential energy values from energies and gradients evaluated previously at points of a simplicial mesh. We chose an…

Computational Physics · Physics 2020-01-07 Konstantin Karandashev , Jiri Vanicek

Several models for the Monte Carlo simulation of Compton scattering on electrons are quantitatively evaluated with respect to a large collection of experimental data retrieved from the literature. Some of these models are currently…

The off-resonant hyperpolarizability is calculated using the dipole-free sum-over-stats expression from a randomly chosen set of energies and transition dipole moments that are forced to be consistent with the sum rules. The process is…

Optics · Physics 2009-11-13 Mark C. Kuzyk , Mark G. Kuzyk

Tracer diffusion of all constituting elements is studied at various temperatures in a series of (CoCrFeMn)$_{100-x}$Ni$_x$ alloys with compositions ranging from pure Ni to the equiatomic CoCrFeMnNi high-entropy alloy. At a given homologous…

We employ a simple and mostly accurate dimensional interpolation formula using dimensional limits $D=1$ and $D=\infty$ to obtain $D=3$ ground-state energy of metallic hydrogen. We also present results describing the phase transitions for…

Strongly Correlated Electrons · Physics 2020-11-19 Kumar J. B. Ghosh , Sabre Kais , Dudley R. Herschbach

A combination of reaction-diffusion models with moving-boundary problems yields a system in which the diffusion (spreading and penetration) and reaction (transformation) evolve the system's state and geometry over time. These systems can be…

Computational Engineering, Finance, and Science · Computer Science 2020-08-26 Mojtaba Barzegari , Liesbet Geris

Understanding the physical origin of deformation mechanisms in random alloys requires an understanding of their average behavior and, equally important, the role of local fluctuations around the average. Material properties of random alloys…

Computational Physics · Physics 2024-11-08 Max Hodapp

A high-resolution investigation of the electron spectra close to the metal-to-insulator transition in dynamic mean-field theory is presented. An all-numerical, consistent confirmation of a smooth transition at zero temperature is provided.…

Strongly Correlated Electrons · Physics 2007-05-23 Michal Karski , Carsten Raas , Götz S. Uhrig

Highly energetic ions that impact materials have applications from semiconductor industry to medicine, and are fundamentally interesting as they trigger multi-length and time-scale processes. In particular, they excite electrons into…

Materials Science · Physics 2025-07-24 Cheng-Wei Lee , André Schleife

In this paper, a diffusion-aggregation equation with delta potential is introduced. Based on the global existence and uniform estimates of solutions to the diffusion-aggregation equation, we also provide the rigorous derivation from a…

Analysis of PDEs · Mathematics 2019-12-13 Li Chen , Simone Göttlich , Stephan Knapp