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A variety of enhanced statistical and numerical methods are now routinely used to extract comprehensible and relevant thermodynamic information from the vast amount of complex, high-dimensional data obtained from intensive molecular…

Soft Condensed Matter · Physics 2020-10-14 Francois Sicard , Vladimir Koskin , Alessia Annibale , Edina Rosta

Probabilistic modeling provides the capability to represent and manipulate uncertainty in data, models, predictions and decisions. We are concerned with the problem of learning probabilistic models of dynamical systems from measured data.…

Computation · Statistics 2018-03-14 Thomas B. Schön , Andreas Svensson , Lawrence Murray , Fredrik Lindsten

In this research, atomistic molecular dynamics simulations are combined with mesoscopic phase-field computational methods in order to investigate phase-transformation in polycrystalline Aluminum microstructure. In fact, microstructural…

Materials Science · Physics 2019-07-03 Mehrdad Yousefi

Two-dimensional materials and their van der Waals heterostructures enable a large range of applications, including label-free biosensing. Lattice mismatch and work function difference in the heterostructure material result in strain and…

Mesoscale and Nanoscale Physics · Physics 2021-11-19 Tetyana Ignatova , Sajedeh Pourianejad , Xinyi Li , Kirby Schmidt , Frederick Aryeetey , Shyam Aravamudhan , Slava V. Rotkin

The aim of this work is to learn models of population dynamics of physical systems that feature stochastic and mean-field effects and that depend on physics parameters. The learned models can act as surrogates of classical numerical models…

Machine Learning · Statistics 2024-10-28 Jules Berman , Tobias Blickhan , Benjamin Peherstorfer

The tube model is a central concept in polymer physics, and allows to reduce the complex many-filament problem of an entangled polymer solution to a single filament description. We investigate the probability distribution function of…

Soft Condensed Matter · Physics 2009-08-12 Hauke Hinsch , Erwin Frey

Gaussian random fields have been one of the most popular tools for analyzing spatial data. However, many geophysical and environmental processes often display non-Gaussian characteristics. In this paper, we propose a new class of spatial…

Applications · Statistics 2017-10-03 Minjie Fan , Debashis Paul , Thomas C. M. Lee , Tomoko Matsuo

Gaussian particles provide a flexible framework for modelling and simulating three-dimensional star-shaped random sets. In our framework, the radial function of the particle arises from a kernel smoothing, and is associated with an…

Propagation of charged cosmic-rays in the Galaxy depends on the transport parameters, whose number can be large depending on the propagation model under scrutiny. A standard approach for determining these parameters is a manual scan,…

Astrophysics · Physics 2009-05-13 A. Putze , L. Derome , D. Maurin , L. Perotto , R. Taillet

Random-walk Monte Carlo simulations are widely used to predict the optical properties of complex, disordered materials. In presence of large heterogeneities (e.g., spatially-extended nonscattering regions in a turbid environment), an…

Optics · Physics 2025-04-10 Loïc Tran , Benjamin Askenazi , Kevin Vynck

Accurate numerical simulations of interaction between fluid and solid play an important role in applications. The task is challenging in practical scenarios as the media are usually highly heterogeneous with very large contrast. To overcome…

Numerical Analysis · Mathematics 2020-05-15 Xia Wang , Eric Chung , Shubin Fu , Zhaoqin Huang

Biofilms are bacterial aggregates encased in a self-produced polymeric matrix which attach to moist surfaces and are extremely resistant to chemicals and antibiotics. Recent experiments show that their structure is defined by the interplay…

Soft Condensed Matter · Physics 2024-01-17 Ana Carpio , Elena Cebrian , Perfecto Vidal

The quasi-static multiple network poroelastic theory (MPET) model, first introduced in the context of geomechanics, has recently found new applications in medicine. In practice, the parameters in the MPET equations can vary over several…

Numerical Analysis · Mathematics 2022-05-16 Johannes Kraus , Philip L. Lederer , Maria Lymbery , Kevin Osthues , Joachim Schöberl

We examine the phase transition of polymer adsorption as well as the underlying kinetics of polymer binding from dilute solutions on a structureless solid surface. The emphasis is put on the properties of regular multiblock copolymers,…

Soft Condensed Matter · Physics 2009-09-03 A. Milchev , V. Rostiashvili , S. Bhattacharya , T. Vilgis

While analyzing mobile systems we often approximate the actual coverage surface and assume an ideal cell shape. In a multi-cellular network, because of its tessellating nature, a hexagon is more preferred than a circular geometry. Despite…

Information Theory · Computer Science 2013-06-04 Mouhamed Abdulla , Yousef R. Shayan

The Bouncy Particle Sampler is a Markov chain Monte Carlo method based on a nonreversible piecewise deterministic Markov process. In this scheme, a particle explores the state space of interest by evolving according to a linear dynamics…

Computation · Statistics 2020-12-24 George Deligiannidis , Daniel Paulin , Alexandre Bouchard-Côté , Arnaud Doucet

Many engineering systems are subject to spatially distributed uncertainty, i.e. uncertainty that can be modeled as a random field. Altering the mean or covariance of this uncertainty will in general change the statistical distribution of…

Optimization and Control · Mathematics 2014-07-09 Eric Dow , Qiqi Wang

Porous polymer films of Poly(ethylene oxide)(PEO) are synthesized by solution casting technique using gamma irradiated: (a) PEO powder (S-series) and (b) PEO - methanol solution (L-series). Pore phase forms instantaneously during…

Applied Physics · Physics 2018-06-13 Subir K. Patla , Madhumita Mukhopadhyay , Abhra Giri , Ruma Ray , Sujata Tarafdar

Energy carrier transport and recombination in emerging semiconductors can be directly monitored with optical microscopy, leading to the measurement of the diffusion coefficient (D), a critical property for design of efficient optoelectronic…

The Richards' equation is a model for flow of water in unsaturated soils. The coefficients of this (nonlinear) partial differential equation describe the permeability of the medium. Insufficient or uncertain measurements are commonly…

Numerical Analysis · Mathematics 2020-03-10 Andrea Barth , Andreas Stein