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In a recent study (Ref. [1]), quantum annealing was reported to exhibit a scaling advantage for approximately solving Quadratic Unconstrained Binary Optimization (QUBO). However, this claim critically depends on the choice of classical…

Quantum Physics · Physics 2025-05-29 J. Pawlowski , P. Tarasiuk , J. Tuziemski , L. Pawela , B. Gardas

We study the convergence of Langevin-Simulated Annealing type algorithms with multiplicative noise, i.e. for $V : \mathbb{R}^d \to \mathbb{R}$ a potential function to minimize, we consider the stochastic equation $dY_t = - \sigma…

Probability · Mathematics 2022-04-26 Pierre Bras , Gilles Pagès

Eigenfunctions of 1d disordered Hamiltonian with constant imaginary vector potential are investigated. Even within the domain of complex eigenvalues the wave functions are shown to be strongly localized. However, this localization is of a…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 P. G. Silvestrov

We study a class of Landau-de Gennes energy functionals with a sextic bulk energy density in a three-dimensional domain. We examine the asymptotic behavior of uniformly bounded minimizers in two distinct scenarios: one where their energy…

Analysis of PDEs · Mathematics 2024-04-02 Wei Wang , Zhifei Zhang

The spatial Lambda-Fleming-Viot (SLFV) process (Barton, Etheridge and V\'eber, 2010) can be seen as a generalised Voter Model with configuration space $M^{R^d}$, where M is the set of probability measures on some space K. Such processes are…

Probability · Mathematics 2014-01-28 Habib Saadi

Nested sampling is a simulation method for approximating marginal likelihoods proposed by Skilling (2006). We establish that nested sampling has an approximation error that vanishes at the standard Monte Carlo rate and that this error is…

Computation · Statistics 2010-10-11 Nicolas Chopin , Christian Robert

We study the local asymptotic behavior of divergence-like functionals of a family of $d$-dimensional Infinitely Divisible Random Fields. Specifically, we derive limit theorems of surface integrals over Lipschitz manifolds for this class of…

Probability · Mathematics 2023-11-06 José Ulises Márquez-Urbina , Orimar Sauri

We provide a set of conditions which ensure the almost sure convergence of a class of simulated annealing algorithms on a bounded set $\mathcal{X}\subset\mathbb{R}^d$ based on a time-varying Markov kernel. The class of algorithms considered…

Probability · Mathematics 2017-07-07 Mathieu Gerber , Luke Bornn

We consider a directed random walk on the backbone of the supercritical oriented percolation cluster in dimensions $d+1$ with $d \ge 3$ being the spatial dimension. For this random walk we prove an annealed local central limit theorem and a…

Simulated annealing (SA) is a stochastic global optimisation technique applicable to a wide range of discrete and continuous variable problems. Despite its simplicity, the development of an effective SA optimiser for a given problem hinges…

Machine Learning · Computer Science 2024-06-27 Alvaro H. C. Correia , Daniel E. Worrall , Roberto Bondesan

Given an energy potential on the Euclidian space, a piecewise deterministic Markov process is designed to sample the corresponding Gibbs measure. In dimension one an Eyring-Kramers formula is obtained for the exit time of the domain of a…

Probability · Mathematics 2016-04-04 Pierre Monmarché

There has been much success in describing the limiting spatial fluctuations of growth models in the Kardar-Parisi-Zhang (KPZ) universality class. A proper rescaling of time should introduce a non-trivial temporal dimension to these limiting…

Probability · Mathematics 2012-10-29 Ivan Corwin , P. L. Ferrari , S. Peche

I describe how real quantum annealers may be used to perform local (in state space) searches around specified states, rather than the global searches traditionally implemented in the quantum annealing algorithm. Such protocols will have…

Quantum Physics · Physics 2017-06-26 Nicholas Chancellor

Quantum annealing is a new method for finding extrema of multidimensional functions. Based on an extension of classical, simulated annealing, this approach appears robust with respect to avoiding local minima. Further, unlike some of its…

chem-ph · Physics 2009-10-22 A. B. Finnila , M. A. Gomez , C. Sebenik , C. Stenson , J. D. Doll

In this paper, we investigate Liouville type theorems for the 3D stationary magneto-micropolar fluid equations and micropolar fluid equations. Adopting an iteration procedure, taking advantage of the special structure of the equations and…

Analysis of PDEs · Mathematics 2026-05-12 Zhibing Zhang , Qian Zu

Let ${Z_{n},n\geq 0} $ be a critical branching process in random environment and let $T$ be its moment of extinction. Under the annealed approach we prove, as $n\to \infty ,$ a limit theorem for the number of particles in the process at…

Probability · Mathematics 2010-11-19 C. Boeinghoff , E. E. Dyakonova , G. Kersting , V. A. Vatutin

We consider a random walk in an i.i.d. non-negative potential on the d-dimensional integer lattice. The walk starts at the origin and is conditioned to hit a remote location y on the lattice. We prove that the expected time under the…

Probability · Mathematics 2012-01-04 Elena Kosygina , Thomas Mountford

{}From a finite-size scaling (FSS) theory of cumulants of the order parameter at phase coexistence points, we reconstruct the scaling of the moments. Assuming that the cumulants allow a reconstruction of the free energy density no better…

High Energy Physics - Lattice · Physics 2009-10-22 Sourendu Gupta , A. Irbaeck , M. Ohlsson

We investigate the growth of the entanglement entropy $S_{\textrm{ent}}$ following global quenches in two-dimensional free fermion models with potential and bond disorder. For the potential disorder case we show that an intermediate weak…

Disordered Systems and Neural Networks · Physics 2019-07-23 Y. Zhao , J. Sirker

In this paper, we propose: (a) a restart schedule for an adaptive simulated annealer, and (b) parallel simulated annealing, with an adaptive and parameter-free annealing schedule. The foundation of our approach is the Modified Lam annealing…

Neural and Evolutionary Computing · Computer Science 2023-11-10 Vincent A. Cicirello