Convergence analysis of Padé approximations for Helmholtz frequency response problems

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Augmented Lagrangian Methods for Provable and Scalable Machine Learning

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Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

LDP and CLT for SPDEs with transport noise

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In this work we consider solutions to stochastic partial differential equations with transport noise, which are known to converge, in a suitable scaling limit, to solution of the corresponding deterministic PDE with an additional viscosity term. Large devi ...

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Gyrokinetic simulations of plasma turbulence in a Z-pinch using a moment-based approach and advanced collision operators

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The first nonlinear gyrokinetic simulations obtained using a moment approach based on the Hermite-Laguerre decomposition of the distribution function are presented, implementing advanced models for the collision operator. Turbulence in a two-dimensional Z- ...

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Localization errors of the stochastic heat equation

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In this thesis, we study the stochastic heat equation (SHE) on bounded domains and on the whole Euclidean space

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We confirm the intuition that as the bounded domain increases to the whole space, both solutions become arbitrarily close to one another ...

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Compact, Spatial-mode-interaction-free, Ultralow-loss, Nonlinear photonic integrated circuits

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We implement Euler bends to build compact high-Q Si3N4 racetrack microresonators, featuring a small footprint of only 0.21 mm(2) for 19.8 GHz FSR. We demonstrate that these multi-mode microresonators can be operated in the single-mode regime and generate a ...

IEEE2022

Fredholm transformation on Laplacian and rapid stabilization for the heat equation

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We study the rapid stabilization of the heat equation on the 1-dimensional torus using the backstepping method with a Fredholm transformation. This classical framework allows us to present the backstepping method with Fredholm transformations for the Lapla ...

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Sharpness-Aware Minimization (SAM) is a recent training method that relies on worst-case weight perturbations which significantly improves generalization in various settings. We argue that the existing justifications for the success of SAM which are based ...

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Reduced basis methods for numerical room acoustic simulations with parametrized boundaries

Jan Sickmann Hesthaven, Hermes Sampedro Llopis

The use of model-based numerical simulations of wave propagation in rooms for engineering applications requires that acoustic conditions for multiple parameters are evaluated iteratively, which is computationally expensive. We present a reduced basis metho ...

ACOUSTICAL SOC AMER AMER INST PHYSICS2022

Estimate on the Dimension of the Singular Set of the Supercritical Surface Quasigeostrophic Equation

Maria Carola Colombo, Silja Noëmi Aline Haffter

We consider the SQG equation with dissipation given by a fractional Laplacian of order α

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Data-Driven Convergence Prediction of Astrobots Swarms

Denis Gillet, Jean-Paul Richard Kneib, Matin Macktoobian, Francesco Basciani

Astrobots are robotic artifacts whose swarms are used in astrophysical studies to generate the map of the observable universe. These swarms have to be coordinated with respect to various desired observations. Such coordination\footnote{\z{A coordination sa ...

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