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We analyze a class of linear partial differential equations that arise as deterministic descriptions of the scaling limits of L\'evy walks, in which transport is driven by a convex combination of fractional material derivatives and a source…

Numerical Analysis · Mathematics 2026-02-03 Łukasz Płociniczak , Marek A. Teuerle , Hubert Woszczek

In this paper we present a computation of the mean first-passage times both for a random walk in a discrete bounded lattice, between a starting site and a target site, and for a Brownian motion in a bounded domain, where the target is a…

Statistical Mechanics · Physics 2007-05-23 Sylvain Condamin , Olivier Bénichou , Michel Moreau

We establish the existence and uniqueness for a one-dimensional stochastic differential equation driven by a Brownian motion and a pure jump {\levy} process. It is shown that under fairly general conditions on the coefficients, pathwise…

Probability · Mathematics 2018-12-27 Jie Xiong , Jiayu Zheng , Xiaowen Zhou

We consider a general class of dynamic resource allocation problems within a stochastic optimal control framework. This class of problems arises in a wide variety of applications, each of which intrinsically involves resources of different…

Optimization and Control · Mathematics 2018-01-08 Xuefeng Gao , Yingdong Lu , Mayank Sharma , Mark S. Squillante , Joost W. Bosman

The dynamics of a freely jointed chain in the continuous limit is described by a field theory which closely resembles the nonlinear sigma model. The generating functional $\Psi[J]$ of this field theory contains nonholonomic constraints,…

Statistical Mechanics · Physics 2011-03-31 Franco Ferrari , Jaroslaw Paturej

Many living and complex systems exhibit second order emergent dynamics. Limited experimental access to the configurational degrees of freedom results in data that appears to be generated by a non-Markovian process. This poses a challenge in…

Quantitative Methods · Quantitative Biology 2020-07-29 Federica Ferretti , Victor Chardès , Thierry Mora , Aleksandra M. Walczak , Irene Giardina

Pedestrian trajectory prediction is a challenging task because of the complexity of real-world human social behaviors and uncertainty of the future motion. For the first issue, existing methods adopt fully connected topology for modeling…

Computer Vision and Pattern Recognition · Computer Science 2019-07-25 Lidan Zhang , Qi She , Ping Guo

To address the dynamics of a Brownian particle on a periodic symmetric substrate under high-frequency periodic forcing with a vanishing time average, we construct an effective Langevin dynamics by invoking Kapitza-Landau time window. Our…

Our investigation is specially motivated by the stochastic version of a common model of potential spread in a dendritic tree. We do not assume the noise in the junction points to be Markovian. In fact, we allow for long-range dependence in…

Probability · Mathematics 2018-12-21 Stefano Bonaccorsi , Delio Mugnolo

We consider the problem of trajectory planning in an environment comprised of a set of obstacles with uncertain locations. While previous approaches model the uncertainties with a prescribed Gaussian distribution, we consider the realistic…

Systems and Control · Computer Science 2021-01-12 Vasileios Lefkopoulos , Maryam Kamgarpour

Dynamics simulations of constrained particles can greatly aid in understanding the temporal and spatial evolution of biological processes such as lateral transport along membranes and self-assembly of viruses. Most theoretical efforts in…

Computational Physics · Physics 2017-03-03 Stefan Paquay , Remy Kusters

This paper focuses on automatic guided vehicle (AGV) trajectory planning in the presence of moving obstacles with known but complicated trajectories. In order to achieve good solution precision, optimality and unification, the concerned…

Robotics · Computer Science 2021-04-06 Bai Li , Youmin Zhang , Yakun Ouyang , Yi Liu , Xiang Zhong , Hangjie Cen , Qi Kong

We introduce a statistical mechanics formalism for the study of constrained graph evolution as a Markovian stochastic process, in analogy with that available for spin systems, deriving its basic properties and highlighting the role of the…

Disordered Systems and Neural Networks · Physics 2015-05-13 A. C. C. Coolen , A. De Martino , A. Annibale

Local time of a stochastic process quantifies the amount of time that sample trajectories $x(\tau)$ spend in the vicinity of an arbitrary point $x$. For a generic Hamiltonian, we employ the phase-space path-integral representation of random…

Mathematical Physics · Physics 2017-05-31 Vaclav Zatloukal

This paper addresses the question of how Brownian-like motion can arise from the solution of a deterministic differential delay equation. To study this we analytically study the bifurcation properties of an apparently simple differential…

Chaotic Dynamics · Physics 2013-09-26 Jinzhi Lei , Michael C. Mackey

In this paper we develop a novel, discrete-time optimal control framework for mechanical systems with uncertain model parameters. We consider finite-horizon problems where the performance index depends on the statistical moments of the…

Optimization and Control · Mathematics 2017-05-17 George I. Boutselis , Yunpeng Pan , Gerardo De La Tore , Evangelos A. Theodorou

Stiff forces, which bind objects together or otherwise confine motion, are found widely in soft-matter systems - colloids with short range attractions, ligand-receptor contacts, particles in optical traps, fibres that resist stretching,…

Soft Condensed Matter · Physics 2026-01-15 Sophie Marbach , Adam Carter , Miranda Holmes-Cerfon

For a stochastic process $(X_t)_{t\geq 0}$ we establish conditions under which the inverse first-passage time problem has a solution for any random variable $\xi >0$. For Markov processes we give additional conditions under which the…

Probability · Mathematics 2023-05-19 Alexander Klump , Mladen Savov

We study a one-dimensional Brownian motion conditioned on a self-repelling behaviour. Given a nondecreasing positive function f(t), consider the measures mu_t obtained by conditioning a Brownian path so that L_s< f(s), for all s<t, where…

Probability · Mathematics 2010-04-22 Itai Benjamini , Nathanael Berestycki

We deal with stochastic differential equations with jumps. In order to obtain an accurate approximation scheme, it is usual to replace the "small jumps" by a Brownian motion. In this paper, we prove that for every fixed time $t$, the…

Probability · Mathematics 2022-12-15 Vlad Bally , Yifeng Qin