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In this work, we introduce a new class of neural network operators designed to handle problems where memory effects and randomness play a central role. In this work, we introduce a new class of neural network operators designed to handle…

Machine Learning · Computer Science 2025-05-22 Rômulo Damasclin Chaves dos Santos , Jorge Henrique de Oliveira Sales

We consider estimation and control of the cylinder wake at low Reynolds numbers. A particular focus is on the development of efficient numerical algorithms to design optimal linear feedback controllers when there are many inputs…

Optimization and Control · Mathematics 2022-05-11 Bo Jin , Simon J. Illingworth , Richard D. Sandberg

This paper synthesizes anytime algorithms, in the form of continuous-time dynamical systems, to solve monotone variational inequalities. We introduce three algorithms that solve this problem: the projected monotone flow, the safe monotone…

Optimization and Control · Mathematics 2025-02-18 Ahmed Allibhoy , Jorge Cortés

For the Bjorken flow we investigate the hydrodynamization of different modes of the one-particle distribution function by analyzing its relativistic kinetic equations. We calculate the constitutive relations of each mode written as a…

High Energy Physics - Theory · Physics 2019-09-23 Alireza Behtash , C. N. Cruz-Camacho , Syo Kamata , M. Martinez

The energy method, also known as the Reynolds-Orr equation, is widely utilized in predicting the unconditional stability threshold of shear flows owing to the zero contribution of nonlinear terms to the time derivative of perturbation…

Fluid Dynamics · Physics 2023-11-01 Péter Tamás Nagy

For low enough flow rates, turbulent channel flow displays spatial modulations of large wavelengths. This phenomenon has recently been interpreted as a linear instability of the turbulent flow. We question here the ability of linear…

Fluid Dynamics · Physics 2024-06-21 P. V. Kashyap , Y. Duguet , O. Dauchot

Recently, there has been a great interest in analysing dynamical flows, where the stationary limit is the minimiser of a convex energy. Particular flows of great interest have been continuous limits of Nesterov's algorithm and the Fast…

Optimization and Control · Mathematics 2021-06-29 Radu Boţ , Guozhi Dong , Peter Elbau , Otmar Scherzer

Normalizing flows learn a diffeomorphic mapping between the target and base distribution, while the Jacobian determinant of that mapping forms another real-valued function. In this paper, we show that the Jacobian determinant mapping is…

Machine Learning · Computer Science 2021-02-18 Huadong Liao , Jiawei He

Graphical flows add further structure to normalizing flows by encoding non-trivial variable dependencies. Previous graphical flow models have focused primarily on a single flow direction: the normalizing direction for density estimation, or…

Machine Learning · Computer Science 2022-04-27 Jacobie Mouton , Steve Kroon

In a previous paper [I. Bena, M. Malek Mansour, and F. Baras, ``Hydrodynamic fluctuations in the Kolmogorov flow: Linear regime", Phys. Rev. E 59, 5503 - 5510 (1999)] the statistical properties of the linearized Kolmogorov flow have been…

Condensed Matter · Physics 2009-11-07 I. Bena , F. Baras , M. Malek Mansour

We study the effectiveness of the time-localised principal resolvent forcing mode at actuating the near wall cycle of turbulence. The mode is restricted to a wavelet pulse and computed from an SVD of the windowed wavelet-based resolvent…

Fluid Dynamics · Physics 2025-08-06 Eric Ballouz , Scott T. M. Dawson , H. Jane Bae

Regression on function spaces is typically limited to models with Gaussian process priors. We introduce the notion of universal functional regression, in which we aim to learn a prior distribution over non-Gaussian function spaces that…

Machine Learning · Computer Science 2024-11-28 Yaozhong Shi , Angela F. Gao , Zachary E. Ross , Kamyar Azizzadenesheli

We provide resolvent asymptotics as well as various operator-norm estimates for the system of linear partial differential equations describing the thin infinite elastic rod with material coefficients which periodically highly oscillate…

Analysis of PDEs · Mathematics 2023-04-12 Kirill Cherednichenko , Igor Velčić , Josip Žubrinić

Chaotic convective flows arise in many real-world systems, such as microfluidic devices and chemical reactors. Stabilizing these flows is highly desirable but remains challenging, particularly in chaotic regimes where conventional control…

Machine Learning · Computer Science 2025-11-04 Michiel Straat , Thorben Markmann , Sebastian Peitz , Barbara Hammer

Subwavelength resonators are small scaled objects that exhibit contrasting medium properties (eigher in intensity or sign) while compared to the ones of a uniform background. Such contrasts allow them to resonate at specific frequencies.…

Analysis of PDEs · Mathematics 2026-01-21 Long Li , Mourad Sini

Stochastic resonance (SR) is a prominent phenomenon in many natural and engineered noisy system, whereby the response to a periodic forcing is greatly amplified when the intensity of the noise is tuned to within a specific range of values.…

Statistical Mechanics · Physics 2019-12-25 Valerio Lucarini

In the present study, the efficiency of preconditioners for solving linear systems associated with the discretized variable-density incompressible Navier-Stokes equations with semiimplicit second-order accuracy in time and spectral accuracy…

In this paper we develop linear transfer Perron Frobenius operator-based approach for optimal stabilization of stochastic nonlinear system. One of the main highlight of the proposed transfer operator based approach is that both the theory…

Optimization and Control · Mathematics 2019-03-20 Apurba Kumar Das , Arvind Raghunathan , Umesh Vaidya

In this article, we provide a methodology to reconstruct high-Reynolds number turbulent mean-flows from few time-averaged measurements. A turbulent flow over a backward-facing step at Re = 28275 is considered to illustrate the potential of…

Fluid Dynamics · Physics 2020-09-23 Lucas Franceschini , Denis Sipp , Olivier Marquet

Recent numerical simulations showed that the mean flow is generated in inhomogeneous turbulence of an incompressible fluid accompanied with helicity and system rotation. In order to investigate the mechanism of this phenomenon, we carry out…

Fluid Dynamics · Physics 2024-09-16 K. Inagaki , N. Yokoi , F. Hamba
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