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Related papers: Damage spreading and coupling in Markov chains

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Strongly Rayleigh distributions are natural generalizations of product and determinantal probability distributions and satisfy strongest form of negative dependence properties. We show that the "natural" Monte Carlo Markov Chain (MCMC) is…

Machine Learning · Computer Science 2016-03-25 Nima Anari , Shayan Oveis Gharan , Alireza Rezaei

We study the approach to equilibrium of the event-chain Monte Carlo (ECMC) algorithm for the one-dimensional hard-sphere model. Using the connection to the coupon-collector problem, we prove that a specific version of this local…

Statistical Mechanics · Physics 2019-04-17 Ze Lei , Werner Krauth

The failure of materials and interfaces is mediated by cracks, nearly singular dissipative structures that propagate at velocities approaching the speed of sound. Crack initiation and subsequent propagation -- the dynamic process of…

Materials Science · Physics 2015-06-15 Eran Bouchbinder , Tamar Goldman , Jay Fineberg

In this paper, a condition-based imperfect maintenance model based on piecewise deterministic Markov process (PDMP) is constructed. The degradation of the system includes two types: natural degradation and random shocks. The natural…

Systems and Control · Electrical Eng. & Systems 2025-03-25 Weikai Wang , Xian Chen

Strong interaction of closely located, nearly parallel hydraulic fractures and its influence on their propagation are studied. Both computational and physical aspects of the problem are considered. It is shown that from the computational…

Fluid Dynamics · Physics 2015-07-07 Ewa Rejwer , Aleksandr Linkov

Perturbation analysis of Markov chains provides bounds on the effect that a change in a Markov transition matrix has on the corresponding stationary distribution. This paper compares and analyzes bounds found in the literature for finite…

Probability · Mathematics 2024-04-03 Karim Abbas , Joost Berkhout , Bernd Heidergott

Metastable condensed matter typically fluctuates about local energy minima at the femtosecond time scale before transitioning between local minima after nanoseconds or microseconds. This vast scale separation limits the applicability of…

Computational Physics · Physics 2017-11-22 Brittan A Farmer , Mitchell Luskin , Petr Plecháč , Gideon Simpson

Macroscopically heterogeneous materials, characterised mostly by comparable heterogeneity lengthscale and structural sizes, can no longer be modelled by deterministic approach instead. It is convenient to introduce stochastic approach with…

Computational Engineering, Finance, and Science · Computer Science 2014-02-07 Jan Sýkora , Anna Kučerová

At fine lattice spacings, Markov chain Monte Carlo simulations of QCD and other gauge theories with or without fermions are plagued by slow modes that give rise to large autocorrelation times. This can lead to simulation runs that are…

High Energy Physics - Lattice · Physics 2024-06-12 Timo Eichhorn , Gianluca Fuwa , Christian Hoelbling , Lukas Varnhorst

This paper considers space homogenous Boltzmann kinetic equations in dimension $d$ with Maxwell collisions (and without Grad's cut-off). An explicit Markov coupling of the associated conservative (Nanbu) stochastic $N$-particle system is…

Analysis of PDEs · Mathematics 2014-02-24 Mathias Rousset

We introduce an effective field theory for the vicinity of a zero temperature quantum transition between a metallic spin glass (``spin density glass'') and a metallic quantum paramagnet. Following a mean field analysis, we perform a…

Condensed Matter · Physics 2009-10-28 Subir Sachdev , N. Read , R. Oppermann

This paper presents a novel stochastic framework to quantify the knock down in strength from out-of-plane wrinkles at the coupon level. The key innovation is a Markov Chain Monte Carlo algorithm which rigorously derives the stochastic…

Applications · Statistics 2019-01-17 Anhadjeet Sandhu , Anne Reinarz , Timothy Dodwell

Apparent critical phenomena, typically indicated by growing correlation lengths and dynamical slowing-down, are ubiquitous in non-equilibrium systems such as supercooled liquids, amorphous solids, active matter and spin glasses. It is often…

Soft Condensed Matter · Physics 2021-04-07 Huaping Li , Yuliang Jin , Ying Jiang , Jeff Z. Y. Chen

We solve the Chapman-Kolmogorov equation and study the exact splitting probabilities of the general stochastic process which describes polymer translocation through membrane pores within the broad class of Markov chains. Transition…

Statistical Mechanics · Physics 2015-05-19 Felipe Mondaini , L. Moriconi

A family $\{Q_{\beta}\}_{\beta \geq 0}$ of Markov chains is said to exhibit $\textit{metastable mixing}$ with $\textit{modes}$ $S_{\beta}^{(1)},\ldots,S_{\beta}^{(k)}$ if its spectral gap (or some other mixing property) is very close to the…

Probability · Mathematics 2021-07-01 Oren Mangoubi , Natesh S. Pillai , Aaron Smith

The technique of damage spreading is used to study the phase diagram of the easy axis anisotropic Heisenberg antiferromagnet on two geometrically frustrated lattices. The triangular and kagome systems are built up from triangular units that…

Statistical Mechanics · Physics 2009-11-10 S. Bekhechi , B. W. Southern

Density dependent families of Markov chains, such as the stochastic models of mass-action chemical kinetics, converge for large values of the indexing parameter $N$ to deterministic systems of differential equations (Kurtz, 1970). Moreover…

Probability · Mathematics 2017-07-11 Enrico Bibbona , Roberta Sirovich

We present several Monte Carlo strategies for simulating discrete-time Markov chains with continuous multi-dimensional state space; we focus on stratified techniques. We first analyze the variance of the calculation of the measure of a…

Statistics Theory · Mathematics 2016-03-22 Rana Fakhereddine , Rami El Haddad , Christian Lécot

The couplings by change of measure are applied to establish log-Harnack inequality(equivalently the entropy-cost estimate) for conditional McKean-Vlasov SDEs and derive the quantitative conditional propagation of chaos in relative entropy…

Probability · Mathematics 2024-01-11 Xing Huang

Markov chain Monte Carlo (MCMC) algorithms are based on the construction of a Markov chain with transition probabilities leaving invariant a probability distribution of interest. In this work, we look at these transition probabilities as…

Probability · Mathematics 2024-10-01 Rocco Caprio , Adam M. Johansen