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We combine the processes of resetting and first-passage to define \emph{first-passage resetting}, where the resetting of a random walk to a fixed position is triggered by a first-passage event of the walk itself. In an infinite domain,…

Statistical Mechanics · Physics 2021-06-22 B. De Bruyne , J. Randon-Furling , S. Redner

Consider a Markov chain on the space of rooted real binary trees that randomly removes leaves and reinserts them on a random edge and suitably rescales the lengths of edges. This chain was introduced by David Aldous who conjectured a…

Probability · Mathematics 2011-04-22 Soumik Pal

This paper studies the diffusion limit for a network of infinite-server queues operating under Markov modulation (meaning that the system's parameters depend on an autonomously evolving background process). In previous papers on (primarily…

Probability · Mathematics 2017-12-13 H. M. Jansen , M. Mandjes , K. De Turck , S. Wittevrongel

We consider large random graphs with prescribed degrees, such as those generated by the configuration model. In the regime where the empirical degree distribution approaches a limit $\mu$ with finite mean, we establish the systematic…

Probability · Mathematics 2019-02-20 Justin Salez

In this paper we investigate deterministic diffusion in systems which are spatially extended in certain directions but are restricted in size and open in other directions, consequently particles can escape. We introduce besides the…

chao-dyn · Physics 2016-08-31 Z. Kaufmann , H. Lustfeld , A. Nemeth , P. Szepfalusy

For real world systems, nonuniform medium is ubiquitous. Therefore, we investigate the diffusion-limited-aggregation process on a two dimensional directed small-world network instead of regular lattice. The network structure is established…

Computational Physics · Physics 2007-05-23 Jie Ren , Wen-Xu Wang , Gang Yan , Bing-Hong Wang

Motivated by a down-up Markov chain on cladograms, David Aldous conjectured in 1999 that there exists a "diffusion on continuum trees" whose mass partitions at any finite number of branch points evolve as Wright-Fisher diffusions with some…

Probability · Mathematics 2023-05-30 Noah Forman , Soumik Pal , Douglas Rizzolo , Matthias Winkel

We analyse diffusion dynamics on weakly-coupled networks (interconnected networks) by means of separation of time scales. Using an adiabatic approximation we reduced the system dynamics to a Markov chain with aggregated variables and…

Chaotic Dynamics · Physics 2018-12-14 Grzegorz Siudem , Janusz A. Hołyst

We present discrete-time approximation of optimal control policies for infinite horizon discounted/ergodic control problems for controlled diffusions in $\Rd$\,. In particular, our objective is to show near optimality of optimal policies…

Optimization and Control · Mathematics 2025-02-11 Somnath Pradhan , Serdar Yuksel

Collective organisation of patterns into ring-like configurations has been well-studied when patterns are subject to either weak or semi-strong interactions. However, little is known numerically or analytically about their formation when…

Dynamical Systems · Mathematics 2024-03-06 Dan J. Hill , Jason J. Bramburger , David J. B. Lloyd

Most large language models are autoregressive: they generate tokens one at a time. Discrete diffusion language models can generate multiple tokens in parallel, but sampling from them requires a denoising order: a strategy for deciding which…

Artificial Intelligence · Computer Science 2026-03-27 Daniel Israel , Tian Jin , Ellie Cheng , Guy Van den Broeck , Aditya Grover , Suvinay Subramanian , Michael Carbin

Part I of this work [2] developed the exact diffusion algorithm to remove the bias that is characteristic of distributed solutions for deterministic optimization problems. The algorithm was shown to be applicable to a larger set of…

Optimization and Control · Mathematics 2017-12-27 Kun Yuan , Bicheng Ying , Xiaochuan Zhao , Ali H. Sayed

Diffusion-based planning, learning, and control methods present a promising branch of powerful and expressive decision-making solutions. Given the growing interest, such methods have undergone numerous refinements over the past years.…

Machine Learning · Computer Science 2025-02-19 Dom Huh , Prasant Mohapatra

Diffusion models have become the go-to method for many generative tasks, particularly for image-to-image generation tasks such as super-resolution and inpainting. Current diffusion-based methods do not provide statistical guarantees…

Computer Vision and Pattern Recognition · Computer Science 2022-11-18 Eliahu Horwitz , Yedid Hoshen

We extend a Discrete Time Random Walk (DTRW) numerical scheme to simulate the anomalous diffusion of financial market orders in a simulated order book. Here using random walks with Sibuya waiting times to include a time-dependent stochastic…

Computational Finance · Quantitative Finance 2024-08-14 Derick Diana , Tim Gebbie

We propose a kind of reaction-diffusion equations for cell differentiation, which exhibits the Turing instability. If the diffusivity of some variables is set to be infinity, we get coupled competitive reaction-diffusion equations with a…

Cell Behavior · Quantitative Biology 2015-05-13 Hidetsugu Sakaguchi

Reduced order models are computationally inexpensive approximations that capture the important dynamical characteristics of large, high-fidelity computer models of physical systems. This paper applies machine learning techniques to improve…

Machine Learning · Computer Science 2015-11-11 Azam Moosavi , Razvan Stefanescu , Adrian Sandu

The focus of this article is on entropy and Markov processes. We study the properties of functionals which are invariant with respect to monotonic transformations and analyze two invariant "additivity" properties: (i) existence of a…

Data Analysis, Statistics and Probability · Physics 2013-11-12 A. N. Gorban , P. A. Gorban , G. Judge

A singularly perturbed linear system of second order ordinary differential equations of reaction-diffusion type with given boundary conditions is considered. The leading term of each equation is multiplied by a small positive parameter.…

Numerical Analysis · Mathematics 2010-04-06 M. Paramasivam , S. Valarmathi , J. J. H. Miller

Generative artificial intelligence offers a new paradigm to design matter in high-dimensional spaces. However, its underlying mechanisms remain difficult to interpret and limit adoption in computational mechanics. This gap is striking…

Computational Engineering, Finance, and Science · Computer Science 2026-05-13 Vahidullah Tac , Ellen Kuhl