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In this paper, we use a machine learning approach to predict the stationary distributions of the number of customers in a single-staiton multi server system. We consider two systems, the first is $c$ homogeneous servers, namely the…

Performance · Computer Science 2025-04-03 Eliran Sherzer

Quantum repeater chains will form the backbone of future quantum networks that distribute entanglement between network nodes. Therefore, it is important to understand the entanglement distribution performance of quantum repeater chains,…

Quantum Physics · Physics 2025-07-14 Allen Zang , Joaquin Chung , Rajkumar Kettimuthu , Martin Suchara , Tian Zhong

In this paper, we analyze the sojourn of an entire batch in a processor sharing $M^{[X]}/M/1$ processor queue, where geometrically distributed batches arrive according to a Poisson process and jobs require exponential service times. By…

Probability · Mathematics 2020-09-29 Fabrice Guillemin , Alain Simonian , Ridha Nasri , Veronica Quintuna Rodriguez

In this paper we consider the problem of computing the stationary distribution of nearly completely decomposable Markov processes, a well-established area in the classical theory of Markov processes with broad applications in the design,…

Numerical Analysis · Mathematics 2025-06-19 Vasileios Kalantzis , Mark S. Squillante , Chai Wah Wu

The main target of this paper is to present the Markov chain C that, not giving explicitly the queue lengths stationary probabilities, has the necessary information to its determination for open networks of queues with several classes of…

Probability · Mathematics 2021-10-19 Manuel Alberto M. Ferreira

We study three non-equivalent queueing models in continuous time that each generalise the classical M/M/1 queue in a different way. Inter-event times in all models are Mittag-Leffler distributed, which is a heavy tail distribution with no…

Probability · Mathematics 2022-11-24 Jacob Butt , Nicos Georgiou , Enrico Scalas

Bayesian nonparametric inferential procedures based on Markov chain Monte Carlo marginal methods typically yield point estimates in the form of posterior expectations. Though very useful and easy to implement in a variety of statistical…

Statistics Theory · Mathematics 2016-05-04 Julyan Arbel , Antonio Lijoi , Bernardo Nipoti

It is a very hard task to compute an exact solution for the differential equations, with differences, system that allows the determination of the M|M|m|m system transient probabilities. The respective complexity grows with m. The…

Probability · Mathematics 2023-12-08 Manuel Alberto M. Ferreira

The joint probability distribution in the full counting statistics (FCS) for noninteracting electrons is discussed for an arbitrary number of initially separate subsystems which are connected at t=0 and separated at a later time. A simple…

Mesoscale and Nanoscale Physics · Physics 2015-05-13 L. Inhester , K. Schonhammer

Expectations of marginals conditional on the total risk of a portfolio are crucial in risk-sharing and allocation. However, computing these conditional expectations may be challenging, especially in critical cases where the marginal risks…

Applications · Statistics 2025-02-25 Christopher Blier-Wong , Hélène Cossette , Etienne Marceau

For a widely used hub-and-spoke closed product-form network consisting of an infinite-server node and several single-server queues, we characterize the maximum queue-length distribution in various operational regimes by leveraging a novel…

Probability · Mathematics 2025-12-09 Predrag Jelenkovic , Petar Momcilovic

We study from a theoretical viewpoint the fundamental problem of efficiently computing the stationary distribution of general classes of structured Markov processes. In strong contrast with previous work, we consider this fundamental…

Quantum Physics · Physics 2025-06-18 Vasileios Kalantzis , Mark S. Squillante , Shashanka Ubaru

Closed queuing networks with finite capacity buffers and skip-over policies are fundamental models in the performance evaluation of computer and communication systems. This technical report presents the details of computational algorithms…

Performance · Computer Science 2024-09-13 Gianfranco Balbo , Andrea Marin , Diletta Olliaro , Matteo Sereno

We describe an exact approach for calculating transition probabilities and waiting times in finite-state discrete-time Markov processes. All the states and the rules for transitions between them must be known in advance. We can then…

Other Condensed Matter · Physics 2009-11-11 Semen A. Trygubenko , David J. Wales

This paper presents a Markov chain Monte Carlo method to generate approximate posterior samples in retrospective multiple changepoint problems where the number of changes is not known in advance. The method uses conjugate models whereby the…

Computation · Statistics 2010-11-15 Jason Wyse , Nial Friel

This paper is concerned with the detection of multiple change-points in the joint distribution of independent categorical variables. The procedures introduced rely on model selection and are based on a penalized least-squares criterion.…

Statistics Theory · Mathematics 2008-01-08 Nathalie Akakpo

We investigate a processor sharing queue with renewal arrivals and generally distributed service times. Impatient jobs may abandon the queue, or renege, before completing service. The corresponding stochastic processes are represented by…

Probability · Mathematics 2009-08-25 Christian H. Gromoll , Philippe Robert , Bert Zwart

Due to the widespread applicability of discrete-time queues in wireless networks or telecommunication systems, this paper analyzes an infinite-buffer batch-service queue with single and multiple vacation where customers/messages arrive…

Probability · Mathematics 2020-05-25 N Nandy , S Pradhan

We present a new framework for designing nonpreemptive and job-size oblivious scheduling policies in the multiserver-job queueing model. The main requirement is to identify a static and balanced sub-partition of the server set and ensure…

Performance · Computer Science 2025-02-04 Jonatha Anselmi , Josu Doncel

These lecture notes introduce the statistical analysis of continuous-time generative models built from Markov dynamics. We begin with the stochastic-calculus foundations of score-based diffusion models, including time reversal, score…

Statistics Theory · Mathematics 2026-04-27 Eddie Aamari , Arthur Stéphanovitch