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Related papers: Rank-based stochastic differential inclusions and …

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We consider a family of branching-selection particle systems in which particles branch at time dependent rate $r$ and are killed with a probability which is dependent on their rank via some function $\psi$. We show that, under fairly…

Probability · Mathematics 2026-05-07 Jacob Mercer

Stochastic efficiency is evaluated in five case studies: driven Brownian motion, effusion with a thermo-chemical and thermo-velocity gradient, a quantum dot and a model for information to work conversion. The salient features of stochastic…

Statistical Mechanics · Physics 2015-06-03 Karel Proesmans , Christian Van den Broeck

A novel probabilistic framework for modelling anomalous diffusion is presented. The resulting process is Markovian, non-homogeneous, non-stationary, non-ergodic, and state-dependent. The fundamental law governing this process is driven by…

Mathematical Physics · Physics 2025-03-07 Nestor Barraza , Gabriel Pena , Juliana Gambini , Florencia Carusela

Queueing networks are notoriously difficult to analyze sans both Markovian and stationarity assumptions. Much of the theoretical contribution towards performance analysis of time-inhomogeneous single class queueing networks has focused on…

Probability · Mathematics 2017-08-22 Harsha Honnappa , Rahul Jain

Recently a new theory for the transport of energetic particles across a mean magnetic field was presented. Compared to other non-linear theories the new approach has the advantage that it provides a full time-dependent description of the…

Plasma Physics · Physics 2017-09-20 Jordan Lasuik , Andreas Shalchi

Stochastic network calculus is a theory for stochastic service guarantee analysis of computer communication networks. In the current stochastic network calculus literature, its traffic and server models are typically based on the cumulative…

Networking and Internet Architecture · Computer Science 2009-06-11 J. Xie , Y. Jiang

Entropy production in stochastic mechanical systems is examined here with strict bounds on its rate. Stochastic mechanical systems include pure diffusions in Euclidean space or on Lie groups, as well as systems evolving on phase space for…

Mathematical Physics · Physics 2022-01-12 Gregory S. Chirikjian

Stochastic differential equations of Langevin-diffusion form have received significant attention, thanks to their foundational role in both Bayesian sampling algorithms and optimization in machine learning. In the latter, they serve as a…

Optimization and Control · Mathematics 2024-05-14 Fabio V. Difonzo , Vyacheslav Kungurtsev , Jakub Marecek

In this work, we study the stationary distribution of the scaled queue length vector process in multiclass queueing networks operating under static buffer priority service policies. We establish that when subjected to a multi-scale heavy…

Probability · Mathematics 2024-11-06 J. G. Dai , Dongyan Huo

Stochastic network calculus is a newly developed theory for stochastic service guarantee analysis of computer networks. In the current stochastic network calculus literature, its fundamental models are based on the cumulative amount of…

Performance · Computer Science 2011-12-14 Jing Xie , Yuming Jiang , Min Xie

In a balancing network each processor has an initial collection of unit-size jobs (tokens) and in each round, pairs of processors connected by balancers split their load as evenly as possible. An excess token (if any) is placed according to…

Data Structures and Algorithms · Computer Science 2010-06-09 Tobias Friedrich , Thomas Sauerwald , Dan Vilenchik

Stochastic models of varying complexity have been proposed to describe the dispersion of particles in turbulent flows, from simple Brownian motion to complex temporally and spatially correlated models. A method is needed to compare…

Fluid Dynamics · Physics 2022-07-13 Martin T. Brolly , James R. Maddison , Aretha L. Teckentrup , Jacques Vanneste

We determine rates of convergence of rank-based interacting diffusions and semimartingale reflecting Brownian motions to equilibrium. Convergence rate for the total variation metric is derived using Lyapunov functions. Sharp fluctuations of…

Probability · Mathematics 2011-08-02 Tomoyuki Ichiba , Soumik Pal , Mykhaylo Shkolnikov

In previous papers we developed a deterministic fluid approximation for an overloaded Markovian queueing system having two customer classes and two service pools, known in the call-center literature as the X model. The system uses the…

Probability · Mathematics 2013-01-24 Ohad Perry , Ward Whitt

Consider a system of identical server pools where tasks with exponentially distributed service times arrive as a time-inhomogenenous Poisson process. An admission threshold is used in an inner control loop to assign incoming tasks to server…

Probability · Mathematics 2024-04-08 Diego Goldsztajn , Sem C. Borst , Johan S. H. van Leeuwaarden

We consider a load balancing system comprised of a fixed number of single server queues, operating under the well-known Join-the-Shortest Queue policy, and where jobs/customers are impatient and abandon if they do not receive service after…

Probability · Mathematics 2023-04-05 Prakirt Raj Jhunjhunwala , Martin Zubeldia , Siva Theja Maguluri

We look at the equilibrium of a Brownian particle in an inhomogeneous space following the alternative approach proposed in ref.[1]. We consider a coordinate dependent damping that makes the stochastic dynamics the one with multiplicative…

Statistical Mechanics · Physics 2014-10-07 Avik Biswas , A. Bhattacharyay

We prove the existence of solutions to a non-linear, non-local, degenerate equation which was previously derived as the formal hydrodynamic limit of an active Brownian particle system, where the particles are endowed with a position and an…

Analysis of PDEs · Mathematics 2023-10-02 Martin Burger , Simon Schulz

In this paper we present some new asymptotic results for high frequency statistics of Brownian semi-stationary processes. More precisely, we will show that singularities in the weight function, which is one of the ingredients of a BSS…

Probability · Mathematics 2014-03-27 Kerstin Gaertner , Mark Podolskij

We propose new limiting dynamics for stochastic gradient descent in the small learning rate regime called stochastic modified flows. These SDEs are driven by a cylindrical Brownian motion and improve the so-called stochastic modified…

Probability · Mathematics 2023-02-15 Benjamin Gess , Sebastian Kassing , Vitalii Konarovskyi
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