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The purpose of this paper is to implement a random death process into a persistent random walk model which produces subballistic superdiffusion (L\'{e}vy walk). We develop a Markovian model of cell motility with the extra residence variable…

Statistical Mechanics · Physics 2015-05-20 Sergei Fedotov , Abby Tan , Andrey Zubarev

Deterministic flow models, such as rectified flows, offer a general framework for learning a deterministic transport map between two distributions, realized as the vector field for an ordinary differential equation (ODE). However, they are…

Machine Learning · Computer Science 2024-10-04 Saurabh Singh , Ian Fischer

The Stochastic Partial Differential Equation (SPDE) approach, now commonly used in spatial statistics to construct Gaussian random fields, is revisited from a mechanistic perspective based on the movement of microscopic particles, thereby…

Methodology · Statistics 2021-11-11 Lionel Roques , Denis Allard , Samuel Soubeyrand

A new stochastic theory of a foreign exchange markets dynamics is developed. As a result we have the new probability distribution which well describes statistical and scaling dependencies ''experimentally'' observed in foreign exchange…

Condensed Matter · Physics 2007-05-23 Nikolai Laskin

The theta process is a stochastic process of number theoretical origin arising as a scaling limit of quadratic Weyl sums. It can be described in terms of the geodesic flow and an automorphic function on a homogeneous space. This process has…

Probability · Mathematics 2025-02-25 Francesco Cellarosi , Zachary Selk

A stochastic theory is developed to predict the spectral signature of proton-transfer processes and applied to infrared spectra computed from ab initio molecular-dynamics simulations of a single H$_5$O$_2{}^{+}$ cation. By constraining the…

Chemical Physics · Physics 2022-11-23 Florian N. Brünig , Paul Hillmann , Won Kyu Kim , Jan O. Daldrop , Roland R. Netz

Transition path sampling (TPS), which involves finding probable paths connecting two points on an energy landscape, remains a challenge due to the complexity of real-world atomistic systems. Current machine learning approaches use…

Machine Learning · Computer Science 2025-06-27 Sanjeev Raja , Martin Šípka , Michael Psenka , Tobias Kreiman , Michal Pavelka , Aditi S. Krishnapriyan

We study nonequilibrium properties of small and chaotic quantum systems, i.e., non-integrable systems whose size is small in the sense that the separations of energy levels are non-negligible as compared with other relevant energy scales.…

chao-dyn · Physics 2007-05-23 Yasuhiro Higashiyama , Akira Shimizu

In a physical system, changing parameters such as temperature can induce a phase transition: an abrupt change from one state of matter to another. Analogous phenomena have recently been observed in large language models. Typically, the task…

Machine Learning · Computer Science 2024-05-28 Julian Arnold , Flemming Holtorf , Frank Schäfer , Niels Lörch

This work aims at making a comprehensive contribution in the general area of parametric inference for discretely observed diffusion processes. Established approaches for likelihood-based estimation invoke a time-discretisation scheme for…

Methodology · Statistics 2024-01-30 Yuga Iguchi , Alexandros Beskos , Matthew M. Graham

Reaction-diffusion systems driven far from thermodynamic equilibrium through the injection of energy can support multiple distinct spatial patterns that persist as long-lived dynamical phases. The stability of these metastable phases is not…

Statistical Mechanics · Physics 2026-03-13 Eric R. Heller , David T. Limmer

Consider the linear stochastic differential equation (SDE) on $\mathbb{R}^n$: \[\mathrm {d}{X}_t=AX_t\,\mathrm{d}t+B\,\mathrm{d}L_t,\] where $A$ is a real $n\times n$ matrix, $B$ is a real $n\times d$ real matrix and $L_t$ is a L\'{e}vy…

Probability · Mathematics 2012-01-06 Feng-Yu Wang

We consider the passage time problem for L\'evy processes, emphasising heavy tailed cases. Results are obtained under quite mild assumptions, namely, drift to $-\infty$ a.s. of the process, possibly at a linear rate (the finite mean case),…

Probability · Mathematics 2016-03-24 Ron Doney , Claudia Klüppelberg , Ross Maller

This study in centered on models accounting for stochastic deformations of sample paths of random walks, embedded either in $\mathbb{Z}^2$ or in $\mathbb{Z}^3$. These models are immersed in multi-type particle systems with exclusion.…

Statistical Mechanics · Physics 2007-05-23 Guy Fayolle , Cyril Furtlehner

We consider the problem of approximating the stationary distribution of an ergodic Markov chain given a set of sampled transitions. Classical simulation-based approaches assume access to the underlying process so that trajectories of…

Machine Learning · Computer Science 2020-03-03 Junfeng Wen , Bo Dai , Lihong Li , Dale Schuurmans

Stochastic difference equations and a stochastic partial differential equation (SPDE) are simultaneously derived for the time-dependent neutron angular density in a general three-dimensional medium where the neutron angular density is a…

Numerical Analysis · Mathematics 2010-04-16 Edward J. Allen

We discuss a concept of path-dependent SDE with distributional drift with possible jumps. We interpret it via a suitable martingale problem, for which we provide existence and uniqueness. The corresponding solutions are expected to be…

Probability · Mathematics 2022-11-08 Elena Bandini , Francesco Russo

We study SDE $$ d X_t = b(X_t) \, dt + A(X_{t-}) \, d Z_t, \quad X_{0} = x \in \mathbb{R}^d, \quad t \geq 0 $$ where $Z=(Z^1, \dots, Z^d)^T$, with $Z^i, i=1,\dots, d$ being independent one-dimensional symmetric jump L\'evy processes, not…

Probability · Mathematics 2022-08-16 Tadeusz Kulczycki , Oleksii Kulyk , Michał Ryznar

This paper studies stabilities of stochastic differential equation (SDE) driven by time-changed L\'evy noise in both probability and moment sense. This provides more flexibility in modeling schemes in application areas including physics,…

Probability · Mathematics 2016-04-27 Erkan Nane , Yinan Ni

In this article, we introduce a system of stochastic differential equations (SDEs) consisting of time-dependent covariates and consider both fixed and random effects set-ups. We also allow the functional part associated with the drift…

Statistics Theory · Mathematics 2017-10-16 Trisha Maitra , Sourabh Bhattacharya