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We study in this paper a variation of the acclaimed CSMA random access protocol. We will focus on the case where back-off rates at each node is polynomial in the size of the queue. Under a condition relating the exponent in the polynomial…

Probability · Mathematics 2021-06-08 Eyal Castiel

We introduce stochastic normalizing flows, an extension of continuous normalizing flows for maximum likelihood estimation and variational inference (VI) using stochastic differential equations (SDEs). Using the theory of rough paths, the…

Machine Learning · Statistics 2020-02-27 Liam Hodgkinson , Chris van der Heide , Fred Roosta , Michael W. Mahoney

In this paper, we consider the underdamped Langevin diffusion (ULD) and propose a numerical approximation using its associated ordinary differential equation (ODE). When used as a Markov Chain Monte Carlo (MCMC) algorithm, we show that the…

Numerical Analysis · Mathematics 2021-01-26 James Foster , Terry Lyons , Harald Oberhauser

We propose an efficient threshold dynamics method for topology optimization for fluids modeled with the Stokes equation. The proposed algorithm is based on minimization of an objective energy function that consists of the dissipation power…

Optimization and Control · Mathematics 2018-12-27 Huangxin Chen , Haitao Leng , Dong Wang , Xiao-Ping Wang

We study the global existence of solutions of a discrete (ODE based) model on a graph describing the formation of biological transportation networks, introduced by Hu and Cai. We propose an adaptation of this model so that a macroscopic…

Analysis of PDEs · Mathematics 2021-02-18 Jan Haskovec , Lisa Maria Kreusser , Peter Markowich

For the ordinary differential equation (ODE) $\dot{x}(t) = f(t,x)$, $x(0) = x_0$, $t\geq 0$, $x\in R^d$, assume $f$ to be at least continuous in $t$ and locally Lipshitz in $x$, and if necessary, several times continuously differentiable in…

Dynamical Systems · Mathematics 2007-05-23 Divakar Viswanath

We describe stochastic calculus in the context of processes that are driven by an adapted point process of locally finite intensity and are differentiable between jumps. This includes Markov chains as well as non-Markov processes. By…

Probability · Mathematics 2016-07-26 Eric Foxall

We consider a nonlinear differential equation under the combined influence of small state-dependent Brownian perturbations of size $\varepsilon$, and fast periodic sampling with period $\delta$; $0<\varepsilon, \delta \ll 1$. Thus, state…

Probability · Mathematics 2022-05-20 Shivam Dhama , Chetan D. Pahlajani

We consider a stochastic fluid queue served by a constant rate server and driven by a process which is the local time of a certain Markov process. Such a stochastic system can be used as a model in a priority service system, especially when…

Probability · Mathematics 2007-09-11 Takis Konstantopoulos , Andreas Kyprianou , Marina Sirvio , Paavo Salminen

The energy method, also known as the Reynolds-Orr equation, is widely utilized in predicting the unconditional stability threshold of shear flows owing to the zero contribution of nonlinear terms to the time derivative of perturbation…

Fluid Dynamics · Physics 2023-11-01 Péter Tamás Nagy

We study the time-bounded reachability problem for continuous-time Markov decision processes (CTMDPs) and games (CTMGs). Existing techniques for this problem use discretisation techniques to break time into discrete intervals, and optimal…

Computer Science and Game Theory · Computer Science 2011-07-11 John Fearnley , Markus Rabe , Sven Schewe , Lijun Zhang

It is well known, mainly because of the work of Kurtz, that density dependent Markov chains can be approximated by sets of ordinary differential equations (ODEs) when their indexing parameter grows very large. This approximation cannot…

Performance · Computer Science 2014-04-04 Marco Beccuti , Enrico Bibbona , Andras Horvath , Roberta Sirovich , Alessio Angius , Gianfranco Balbo

Imprecise continuous-time Markov chains are a robust type of continuous-time Markov chains that allow for partially specified time-dependent parameters. Computing inferences for them requires the solution of a non-linear differential…

Probability · Mathematics 2018-10-11 Alexander Erreygers , Jasper De Bock

We analyze the behavior of closed product-form queueing networks when the number of customers grows to infinity and remains proportionate on each route (or class). First, we focus on the stationary behavior and prove the conjecture that the…

Probability · Mathematics 2014-04-11 Jonatha Anselmi , Bernardo D'Auria , Neil Walton

This paper is dedicated to the investigation of a new numerical method to approximate the optimal stopping problem for a discrete-time continuous state space Markov chain under partial observations. It is based on a two-step discretization…

Optimization and Control · Mathematics 2016-02-16 Benoîte de Saporta , François Dufour , Christophe Nivot

A fluid queue is a stochastic process which moves linearly with a rate that is determined by the state of a continuous-time Markov chain (CTMC). In this paper we construct an approximation to a fluid queue using a quasi birth-and-death…

Probability · Mathematics 2025-04-25 Nigel Bean , Angus Lewis

Motivated by queues with many servers, we study Brownian steady-state approximations for continuous time Markov chains (CTMCs). Our approximations are based on diffusion models (rather than a diffusion limit) whose steady-state, we prove,…

Probability · Mathematics 2014-09-12 Itai Gurvich

This paper considers the queueing performance of a system that transmits coded data over a time-varying erasure channel. In our model, the queue length and channel state together form a Markov chain that depends on the system parameters.…

Information Theory · Computer Science 2021-03-26 Parimal Parag , Jean-Francois Chamberland , Henry D. Pfister , Krishna R. Narayanan

In this work, the synchronization problem of a master-slave system of autonomous ordinary differential equations (ODEs) is considered. Here, the systems are, chaotic with a nonlinearity represented by a piecewise linear function,…

Chaotic Dynamics · Physics 2021-12-16 J. Telenchana , A. Acosta , P. Garcia

The developments over the last five decades concerning numerical discretisations of the incompressible Navier--Stokes equations have lead to reliable tools for their approximation: those include stable methods to properly address the…

Numerical Analysis · Mathematics 2025-08-12 Dominic Breit , Andreas Prohl , Jörn Wichmann
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