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For a large number of random constraint satisfaction problems, such as random k-SAT and random graph and hypergraph coloring, there are very good estimates of the largest constraint density for which solutions exist. Yet, all known…

Computational Complexity · Computer Science 2007-05-23 Dimitris Achlioptas , Federico Ricci-Tersenghi

We study the diffusive scaling limit for a chain of $N$ coupled oscillators. In order to provide the system with good ergodic properties, we perturb the Hamiltonian dynamics with random flips of velocities, so that the energy is locally…

Probability · Mathematics 2013-02-21 Marielle Simon

Stochastic gradient descent is a classic algorithm that has gained great popularity especially in the last decades as the most common approach for training models in machine learning. While the algorithm has been well-studied when…

Machine Learning · Statistics 2025-09-09 Jose Blanchet , Aleksandar Mijatović , Wenhao Yang

Computational fluid dynamics (CFD) is a cornerstone of classical scientific computing, and there is growing interest in whether quantum computers can accelerate such simulations. To date, the existing proposals for fault-tolerant quantum…

It is of broad interest to understand how the evolution of non-equilibrium systems can be triggered and the role played by external perturbations. A famous example is the origin of randomness in the laminar-turbulence transition, which is…

Fluid Dynamics · Physics 2016-12-02 Zhiliang Lin , Lipo Wang , Shijun Liao

We introduce deterministic perturbation schemes for the recently proposed random directions stochastic approximation (RDSA) [17], and propose new first-order and second-order algorithms. In the latter case, these are the first second-order…

Optimization and Control · Mathematics 2019-03-29 Prashanth L A , Shalabh Bhatnagar , Nirav Bhavsar , Michael Fu , Steven I. Marcus

This paper presents, in a unified fashion, deterministic as well as statistical Lagrangian-verification techniques. They formally quantify the behavioral robustness of any time-continuous process, formulated as a continuous-depth model. To…

Machine Learning · Computer Science 2023-08-24 Sophie A. Neubauer , Radu Grosu

Applied to statistical physics models, the random cost algorithm enforces a Random Walk (RW) in energy (or possibly other thermodynamic quantities). The dynamics of this procedure is distinct from fixed weight updates. The probability for a…

Statistical Mechanics · Physics 2009-10-31 Bernd A. Berg , Ulrich H. E. Hansmann

Iterative coarse-graining procedure based on Wyld's perturbation expansion is applied to the problem of Navier-Stokes turbulence. It is shown that the low-order calculation gives the fixed-point Reynolds number $ Re_{fp}$ (coupling…

Fluid Dynamics · Physics 2013-08-21 Victor Yakhot

We consider the flow of a Newtonian fluid in a three-dimensional domain, rotating about a vertical axis and driven by a vertically invariant horizontal body-force. This system admits vertically invariant solutions that satisfy the 2D…

Fluid Dynamics · Physics 2023-07-19 Basile Gallet

The run-and-tumble particle (RTP) is one of the simplest examples of an active particle in which the direction of constant motion randomly switches. In the one-dimensional (1D) case this means switching between rightward and leftward…

Statistical Mechanics · Physics 2024-11-26 Paul C Bressloff

We study the convergence rate of randomly truncated stochastic algorithms, which consist in the truncation of the standard Robbins-Monro procedure on an increasing sequence of compact sets. Such a truncation is often required in practice to…

Probability · Mathematics 2010-04-08 Jérôme Lelong

We study the convergence rate of randomly truncated stochastic algorithms, which consist in the truncation of the standard Robbins-Monro procedure on an increasing sequence of compact sets. Such a truncation is often required in practice to…

Probability · Mathematics 2010-03-23 Jérôme Lelong

Uniform bounds on sketched inner products of vectors or matrices underpin several important computational and statistical results in machine learning and randomized algorithms, including the Johnson-Lindenstrauss (J-L) lemma, the Restricted…

Machine Learning · Computer Science 2025-09-29 Rohan Deb , Qiaobo Li , Mayank Shrivastava , Arindam Banerjee

The transitional and well-developed regimes of turbulent shear flows exhibit a variety of remarkable scaling laws that are only now beginning to be systematically studied and understood. In the first part of this article, we summarize…

Fluid Dynamics · Physics 2017-01-04 Nigel Goldenfeld , Hong-Yan Shih

Imaginary-time evolution is fundamental for analyzing quantum many-body systems, yet classical simulation requires exponentially growing resources in both system size and evolution time. While quantum approaches reduce the system-size…

Quantum Physics · Physics 2025-12-12 Lei Zhang , Jizhe Lai , Xian Wu , Xin Wang

In random sequential covering, identical objects are deposited randomly, irreversibly, and sequentially; only attempts increasing the coverage are accepted. A finite system eventually gets congested, and we study the statistics of congested…

Probability · Mathematics 2023-03-28 P. L. Krapivsky

This work constructs Jonson-Lindenstrauss embeddings with best accuracy, as measured by variance, mean-squared error and exponential concentration of the length distortion. Lower bounds for any data and embedding dimensions are determined,…

Machine Learning · Computer Science 2021-01-05 Maciej Skorski

We investigate the incompressible flow past a square cylinder immersed in the wake of an upstream nearby splitter plate separating two streams of different velocity. The bottom stream Reynolds number, based on the square side, $Re_B=56$ is…

Fluid Dynamics · Physics 2022-11-09 Reda El Mansy , Wasim Sarwar , Josep M Bergada , Fernando Mellibovsky

We investigate a family of curve evolution equations approximating the motion of a Kirchhoff rod immersed in a low Reynolds number fluid. The rod is modeled as a framed curve whose energy consists of the bending energy of the curve and the…

Analysis of PDEs · Mathematics 2025-03-21 Dallas Albritton , Laurel Ohm