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In this paper, we study the optimal control of a discrete-time stochastic differential equation (SDE) of mean-field type, where the coefficients can depend on both a function of the law and the state of the process. We establish a new…

Optimization and Control · Mathematics 2022-10-05 Arzu Ahmadova , Nazim I. Mahmudov

Directed paths have been used extensively in the scientific literature as a model of a linear polymer. Such paths models in particular the conformational entropy of a linear polymer and the effects it has on the free energy. These directed…

Soft Condensed Matter · Physics 2015-05-13 E J Janse van Rensburg , T Prellberg , A Rechnitzer

The paper presents a short overview of the theoretical, numerical and experimental works on the critical behavior of a dilute polymer solution of long-flexible polymer chains confined in semi-infinite space restricted by a surface or in a…

Soft Condensed Matter · Physics 2018-01-08 Zoryana Usatenko , Krzysztof S. Danel

The conformational states of a semiflexible polymer enclosed in a compact domain of typical size $a$ are studied as stochastic realizations of paths defined by the Frenet equations under the assumption that stochastic "curvature" satisfies…

Soft Condensed Matter · Physics 2019-07-17 Pavel Castro-Villarreal , J. E. Ramírez

We introduce a stochastic partial differential equation (SPDE) with elliptic operator in divergence form, with measurable and bounded coefficients and driven by space-time white noise. Such SPDEs could be used in mathematical modelling of…

Probability · Mathematics 2020-01-09 Mounir Zili , Eya Zougar

We investigate conformations and dynamics of a polymer considering its monomers to be active Brownian particles. This active polymer shows very intriguing physical behavior which is absent in an active Rouse chain. The chain initially…

Soft Condensed Matter · Physics 2020-04-13 Shalabh K. Anand , Sunil P. Singh

We propose and analyze a conservative drifting method for one-step generative modeling. The method replaces the original displacement-based drifting velocity by a kernel density estimator (KDE)-gradient velocity, namely the difference of…

Machine Learning · Statistics 2026-05-26 Krishnakumar Balasubramanian

We study geometric stochastic differential equations (SDEs) and their approximations on Riemannian manifolds. In particular, we introduce a simple new construction of geometric SDEs, using which with bounded curvature. In particular, we…

Probability · Mathematics 2023-11-22 Xiang Cheng , Jingzhao Zhang , Suvrit Sra

A variational framework is developed to examine the equilibrium states of a semi-flexible polymer that is constrained to lie on a fixed surface. As an application the confinement of a closed polymer loop of fixed length $2\pi R$ within a…

Soft Condensed Matter · Physics 2012-02-17 Jemal Guven , Pablo Vázquez-Montejo

We present strongly convergent explicit and semi-implicit adaptive numerical schemes for systems of stiff stochastic differential equations (SDEs) where both the drift and diffusion are non-globally Lipschitz continuous. This stiffness may…

Numerical Analysis · Mathematics 2021-06-02 Cónall Kelly , Gabriel Lord

This paper provides an analytical examination of non-radial geodesics within the context of the spatially flat Friedmann Lema\^itre Robertson Walker (FLRW) spacetime. Using the symmetry properties of the system, two constants of motion…

General Relativity and Quantum Cosmology · Physics 2024-02-13 Omar Nemoul , Hichem Guergouri , Jamal Mimouni

Dense, disordered packings of particles are useful models of low-temperature amorphous phases of matter, biological systems, granular media, and colloidal systems. The study of dense packings of nonspherical particles enables one to…

Soft Condensed Matter · Physics 2022-05-09 Charles Emmett Maher , Frank H. Stillinger , Salvatore Torquato

A low frequency approximation of the discrete Sommerfeld diffraction problems, involving the scattering of a time harmonic lattice wave incident on square lattice by a discrete Dirichlet or a discrete Neumann half-plane, is investigated. It…

Analysis of PDEs · Mathematics 2019-08-08 Basant Lal Sharma

Stochastic differential equations (SDEs) are established tools to model physical phenomena whose dynamics are affected by random noise. By estimating parameters of an SDE intrinsic randomness of a system around its drift can be identified…

Computation · Statistics 2012-05-03 Umberto Picchini , Susanne Ditlevsen

Multiscale stochastic dynamical systems have been widely adopted to a variety of scientific and engineering problems due to their capability of depicting complex phenomena in many real world applications. This work is devoted to…

Machine Learning · Statistics 2024-01-02 Lingyu Feng , Ting Gao , Min Dai , Jinqiao Duan

Propagation characteristics of a wave are defined by the dispersion relationship, from which the governing partial differential equation (PDE) can be recovered. PDEs are commonly solved numerically using the finite-difference (FD) method,…

Numerical Analysis · Mathematics 2021-07-29 Edward Caunt

Using a lattice-based Monte Carlo code for simulating self-avoiding flexible polymers in three dimensions in the absence of explicit hydrodynamics, we study their Rouse modes. For self-avoiding polymers, the Rouse modes are not expected to…

Soft Condensed Matter · Physics 2009-10-20 Debabrata Panja , Gerard T. Barkema

Stochastic dynamical systems with slow or metastable behavior evolve, on long time scales, on an unknown low-dimensional manifold in high-dimensional ambient space. Building a reduced simulator from short-burst ambient ensembles is a…

Machine Learning · Computer Science 2026-04-20 Sean Hill , Felix X. -F. Ye

Drawing an analogy to the paradigm of quasi-elastic neutron scattering, we present a general approach for quantitatively investigating the spatiotemporal dependence of structural anisotropy relaxation in deformed polymers by using…

This paper deals with the numerical approximation of semilinear parabolic stochastic partial differential equation (SPDE) driven simultaneously by Gaussian noise and Poisson random measure, more realistic in modeling real world phenomena.…

Numerical Analysis · Mathematics 2020-11-19 Jean Daniel Mukam , Antoine Tambue
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