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Lately, a novel swarm intelligence model, namely the consensus-based optimization (CBO) algorithm, was introduced to deal with the global optimization problems. Limited by the conditions of Ito's formula, the convergence analysis of the…

Optimization and Control · Mathematics 2025-01-14 Jiazhen Wei , Wei Bian

We consider a particle system in 1D, interacting via repulsive or attractive Coulomb forces. We prove the trajectorial propagation of molecular chaos towards a nonlinear SDE associated to the Vlasov-Poisson-Fokker-Planck equation. We obtain…

Analysis of PDEs · Mathematics 2015-11-16 Maxime Hauray , Samir Salem

This paper focus on investigating the explicit rate of convergence for the propagation of chaos, in a pathwise sense a family of interacting stochastic particle related to some Brownian driven McKean-Vlasov dynamics. Precisely the McKean…

Probability · Mathematics 2019-07-23 Jean-Francois Jabir

New quantitative propagation of chaos results for mean field diffusion are proved via local and global entropy estimates. In the first result we work on the torus and consider singular, divergence free interactions $K\in L^p$, $p>d$. We…

Probability · Mathematics 2023-08-02 Yi Han

Consider the metric space $(\mathcal{P}_2(\mathbb{R}^d),W_2)$ of square integrable laws on $\mathbb{R}^d$ with the topology induced by the 2-Wasserstein distance $W_2$. Let $\Phi: \mathcal{P}_2( \mathbb{R}^d) \to \mathbb{R}$ be a function…

Probability · Mathematics 2022-06-02 Jean-François Chassagneux , Lukasz Szpruch , Alvin Tse

The Kac model is a simplified model of an $N$-particle system in which the collisions of a real particle system are modeled by random jumps of pairs of particle velocities. Kac proved propagation of chaos for this model, and hence provided…

Mathematical Physics · Physics 2015-06-18 Eric Carlen , Dawan Mustafa , Bernt Wennberg

We study zeroth-order optimisation under context distributional uncertainty, a setting commonly tackled using Bayesian optimisation (BO). A prevailing strategy to make BO more robust to the complex and noisy nature of data is to employ an…

Machine Learning · Computer Science 2026-05-11 Tigran Ramazyan , Denis Derkach

Out-of-time-ordered correlators (OTOCs) describe information scrambling under unitary time evolution, and provide a useful probe of the emergence of quantum chaos. Here we calculate OTOCs for a model of disorder-free localization whose…

Strongly Correlated Electrons · Physics 2019-08-27 Adam Smith , Johannes Knolle , Roderich Moessner , Dmitry L. Kovrizhin

We propose Discrete Consensus-Based Optimization (DCBO), a fully discrete version of the Consensus-Based Optimization (CBO) framework. DCBO is a multi-agent method for the global optimization of possibly non-convex and non-differentiable…

Optimization and Control · Mathematics 2024-04-17 Junhyeok Byeon , Seung-Yeal Ha , Joong-Ho Won

In this paper we obtain uniform propagation estimates for systems of interacting diffusions. We adopt a general model, satisfying various conditions which ensure that the decay resulting from the internal dynamics term dominates the…

Probability · Mathematics 2017-02-24 Jamil Salhi , James MacLaurin , Salwa Toumi

We introduce a novel first-order stochastic swarm intelligence (SI) model in the spirit of consensus formation models, namely a consensus-based optimization (CBO) algorithm, which may be used for the global optimization of a function in…

Probability · Mathematics 2017-10-06 René Pinnau , Claudia Totzeck , Oliver Tse , Stephan Martin

We consider Kac's 1D N-particle system coupled to an ideal thermostat at temperature T, introduced by Bonetto, Loss, and Vaidyanathan in 2014. We obtain a propagation of chaos result for this system, with explicit and uniform-in-time rates…

Probability · Mathematics 2021-05-19 Roberto Cortez , Hagop Tossounian

In this paper, we analyse the rate of convergence of a system of $N$ interacting particles with mean-field rank based interaction in the drift coefficient and constant diffusion coefficient. We first adapt arguments by Kolli and Shkolnikhov…

Probability · Mathematics 2020-11-13 Oumaima Bencheikh , Benjamin Jourdain

We study in this paper the weak propagation of chaos for McKean--Vlasov diffusions with branching, whose induced marginal measures are nonnegative finite measures but not necessary probability measures. The flow of marginal measures…

Probability · Mathematics 2026-01-14 Wenjing Cao , Zhenjie Ren , Xiaolu Tan

Out-of-time-order correlators (OTOC), vigorously being explored as a measure of quantum chaos and information scrambling, is studied here in the natural and simplest multi-particle context of bipartite systems. We show that two strongly…

Quantum Physics · Physics 2020-03-18 Ravi Prakash , Arul Lakshminarayan

The out of time order correlator (OTOC) serves as a powerful tool for investigating quantum information spreading and chaos in complex systems. We present a method employing non-equilibrium dynamical mean-field theory (DMFT) and coherent…

Strongly Correlated Electrons · Physics 2026-02-20 Chakradhar Rangi , Juana Moreno , Ka-Ming Tam

We derive quantitative estimates proving the propagation of chaos for large stochastic systems of interacting particles. We obtain explicit bounds on the relative entropy between the joint law of the particles and the tensorized law at the…

Analysis of PDEs · Mathematics 2018-10-17 Pierre-Emmanuel Jabin , Zhenfu Wang

Entanglement growth and out-of-time-order correlators (OTOC) are used to assess the propagation of information in isolated quantum systems. In this work, using large scale exact time-evolution we show that for weakly disordered…

Disordered Systems and Neural Networks · Physics 2017-07-19 David J. Luitz , Yevgeny Bar Lev

In this paper, we introduce a novel variant of the CBO method that incorporates jumps according to an $\alpha$-stable stochastic process in a kinetic framework. This extension gives rise to nonlocal stochastic effects, which improve the…

Optimization and Control · Mathematics 2026-04-08 Pedro Aceves-Sanchez , Giacomo Albi , Federica Ferrarese , Michael Herty

We study the mean field Langevin dynamics and the associated particle system. By assuming the functional convexity of the energy, we obtain the $L^p$-convergence of the marginal distributions towards the unique invariant measure for the…

Probability · Mathematics 2025-11-06 Fan Chen , Zhenjie Ren , Songbo Wang
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