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In this paper, we show a large deviation principle for certain sequences of static Schr\"{o}dinger bridges, typically motivated by a scale-parameter decreasing towards zero, extending existing large deviation results to cover a wider range…

Probability · Mathematics 2025-06-23 Viktor Nilsson , Pierre Nyquist

We study local features, and provide a topological insight into the global structure of the probability density distribution and of the pattern of the optimal paths for large rare fluctuations away from a stable state. In contrast to…

Condensed Matter · Physics 2009-10-22 Mark I. Dykman , Mark M. Millonas , Vadim N. Smelyanskiy

We consider a Jackson network with regenerative input flows in which every server is subject to a random environment influence generating breakdowns and repairs. They occur in accordance with two independent sequences of i.i.d. random…

Probability · Mathematics 2020-10-29 Elena Bashtova , Elena Lenena

We examine a Wong-Zakai type approximation of a family of stochastic differential equations driven by a general cadlag semimartingale. For such an approximation, compared with the pointwise convergence result by Kurtz, Pardoux and Protter…

Probability · Mathematics 2019-02-19 Xianming Liu , Guangyue Han

We present upper and lower bounds for the tail distribution of the stationary waiting time $D$ in the stable $GI/GI/s$ FCFS queue. These bounds depend on the value of the traffic load $\rho$ which is the ratio of mean service and mean…

Probability · Mathematics 2013-03-20 Sergey Foss , Dmitry Korshunov

A large deviation principle is established for a general class of stochastic flows in the small noise limit. This result is then applied to a Bayesian formulation of an image matching problem, and an approximate maximum likelihood property…

Statistics Theory · Mathematics 2010-02-24 Amarjit Budhiraja , Paul Dupuis , Vasileios Maroulas

Heavy-tailed distributions are found throughout many naturally occurring phenomena. We have reviewed the models of stochastic dynamics that lead to heavy-tailed distributions (and power law distributions, in particular) including the…

Mathematical Physics · Physics 2011-05-09 Ph. Blanchard , T. Krueger , D. Volchenkov

We consider quantum stochastic processes and discuss a level 2.5 large deviation formalism providing an explicit and complete characterisation of fluctuations of time-averaged quantities, in the large-time limit. We analyse two classes of…

Statistical Mechanics · Physics 2021-08-03 Federico Carollo , Juan P. Garrahan , Robert L. Jack

Topological defects, which are singular points in a director field, play a major role in shaping active systems. Here, we experimentally study topological defects and the flow patterns around them, that are formed during the highly rapid…

Soft Condensed Matter · Physics 2024-03-20 Victor Yashunsky , Daniel J. G. Pearce , Gil Ariel , Avraham Be'er

We present methodology for estimating the stochastic intensity of a doubly stochastic Poisson process. Statistical and theoretical analyses of traffic traces show that these processes are appropriate models of high intensity traffic…

Machine Learning · Statistics 2020-07-24 Ruixin Wang , Prateek Jaiwal , Harsha Honnappa

We establish maximal concentration bounds for the iterates generated by stochastic approximation algorithms with general step sizes, where the noise has a finite-state Markovian component plus a Martingale-difference component. When the…

Probability · Mathematics 2026-05-21 Shubhada Agrawal , Siva Theja Maguluri , Martin Zubeldia

The paper deals with a family of jump Markov process defined in a medium with a periodic or locally periodic microstructure. We assume that the generator of the process is a zero order convolution type operator with rapidly oscillating…

Probability · Mathematics 2020-06-22 Andrey Piatnitski , Sergei Pirogov , Elena Zhizhina

A recent line of empirical studies has demonstrated that SGD might exhibit a heavy-tailed behavior in practical settings, and the heaviness of the tails might correlate with the overall performance. In this paper, we investigate the…

Machine Learning · Computer Science 2023-10-31 Krunoslav Lehman Pavasovic , Alain Durmus , Umut Simsekli

Significant correlations between arrivals of load-generating events make the numerical evaluation of the workload of a system a challenging problem. In this paper, we construct highly accurate approximations of the workload distribution of…

Probability · Mathematics 2014-05-02 Eleni Vatamidou , Ivo J. B. F. Adan , Maria Vlasiou , Bert Zwart

We study a single server FIFO queue that offers general service. Each of n customers enter the queue at random time epochs that are inde- pendent and identically distributed. We call this the random scattering traffic model, and the…

Probability · Mathematics 2017-08-21 Peter W. Glynn , Harsha Honnappa

We propose a new model and estimation framework for spatiotemporal streamflow exceedances above a threshold that flexibly captures asymptotic dependence and independence in the tail of the distribution. We model streamflow using a mixture…

Methodology · Statistics 2026-02-19 Ryan Li , Emily C. Hector , Brian J. Reich , Reetam Majumder

In this paper we study the stationary workload distribution of a fluid tandem queue in heavy traffic. We consider different types of L\'evy input, covering compound Poisson, $\alpha$-stable L\'evy motion (with $1<\alpha<2$), and Brownian…

Probability · Mathematics 2017-03-14 David T. Koops , Onno J. Boxma , Michel R. H. Mandjes

For one-dimensional Jump-Drift and Jump-Diffusion processes converging towards some steady state, the large deviations of a long dynamical trajectory are described from two perspectives. Firstly, the joint probability of the empirical…

Statistical Mechanics · Physics 2021-08-17 Cecile Monthus

Understanding transport processes in complex nanoscale systems, like ionic conductivities in nanofluidic devices or heat conduction in low dimensional solids, poses the problem of examining fluctuations of currents within nonequilibrium…

Mesoscale and Nanoscale Physics · Physics 2021-08-04 David T. Limmer , Chloe Y. Gao , Anthony R. Poggioli

This paper presents a new, short proof of the computation of the upper tail large deviation rate function for the Brownian directed percolation model. Through a distributional equivalence between the last passage time in this model and the…

Probability · Mathematics 2019-07-08 Christopher Janjigian