Concept

Théorie spectrale

Publications associées (107)

A Spectral Ansatz for The Long-Time Homogenization of The Wave Equation

Matthias Ruf

Consider the wave equation with heterogeneous coefficients in the homogenization regime. At large times, the wave interacts in a nontrivial way with the heterogeneities, giving rise to effective dispersive effects. The main achievement of the present wor ...

Ecole Polytechnique2024

Transition to chaos in extended systems and their quantum impurity models

Camille Didier Georges Aron

Chaos sets a fundamental limit to quantum-information processing schemes. We study the onset of chaos in spatially extended quantum many-body systems that are relevant to quantum optical devices. We consider an extended version of the Tavis-Cummings model ...

Bristol2024

Turbulence in the Strongly Heterogeneous Near-Surface Boundary Layer over Patchy Snow

Michael Lehning, Dylan Stewart Reynolds, Michael Haugeneder

The near-surface boundary layer above patchy snow cover in mountainous terrain is characterized by a highly complex interplay of various flows on multiple scales. In this study, we present data from a comprehensive field campaign that cover a period of 21 ...

2024

Critical Schrodinger Cat Qubit

Vincenzo Savona, Fabrizio Minganti, Luca Gravina

Encoding quantum information onto bosonic systems is a promising route to quantum error correc-tion. In a cat code, this encoding relies on the confinement of the dynamics of the system onto the two-dimensional manifold spanned by Schrodinger cats of oppos ...

AMER PHYSICAL SOC2023

An optimal preconditioned FFT-accelerated finite element solver for homogenization

Till Junge, Ali Falsafi, Martin Ladecký

We generalize and provide a linear algebra-based perspective on a finite element (FE) ho-mogenization scheme, pioneered by Schneider et al. (2017)[1] and Leuschner and Fritzen (2018)[2]. The efficiency of the scheme is based on a preconditioned, well-scale ...

ELSEVIER SCIENCE INC2023

Deep Learning Meets Sparse Regularization

Rahul Parhi

Deep learning (DL) has been wildly successful in practice, and most of the state-of-the-art machine learning methods are based on neural networks (NNs). Lacking, however, is a rigorous mathematical theory that adequately explains the amazing performance of ...

2023

Spectral analysis for transmission eigenvalue problems with and without the complementing conditions

Jean Louis-Alexandre Fornerod

The interior transmission eigenvalue problem is a system of partial differential equations equipped with Cauchy data on the boundary: the transmission conditions. This problem appears in the inverse scattering theory for inhomogeneous media when, for some ...

EPFL2022

Weak nonlinearity for strong non-normality

François Gallaire, Edouard Boujo, Yves-Marie François Ducimetière

We propose a theoretical approach to derive amplitude equations governing the weakly nonlinear evolution of non-normal dynamical systems, when they experience transient growth or respond to harmonic forcing. This approach reconciles the non-modal nature of ...

2022

Spectral Hypergraph Sparsifiers of Nearly Linear Size

Mikhail Kapralov, Jakab Tardos

Graph sparsification has been studied extensively over the past two decades, culminating in spectral sparsifiers of optimal size (up to constant factors). Spectral hypergraph sparsification is a natural analogue of this problem, for which optimal bounds on ...

IEEE COMPUTER SOC2022

Unified Green's function approach for spectral and thermodynamic properties from algorithmic inversion of dynamical potentials

Nicola Marzari, Tommaso Chiarotti, Andrea Ferretti

Dynamical potentials appear in many advanced electronic-structure methods, including self-energies from many-body perturbation theory, dynamical mean-field theory, electronic-transport formulations, and many embedding approaches. Here, we propose a novel t ...

AMER PHYSICAL SOC2022

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