Publications related to Low rank differential equations for Hamiltonian matrix nearness problems

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

Given a family of nearly commuting symmetric matrices, we consider the task of computing an orthogonal matrix that nearly diagonalizes every matrix in the family. In this paper, we propose and analyze randomized joint diagonalization (RJD) for performing t ...

Philadelphia2024

Asymmetric phase modulation of light with parity-symmetry broken metasurfaces

Karim Achouri, Jean-Yves Duboz

The design of wavefront-shaping devices is conventionally approached using real-frequency modeling. However, since these devices interact with light through radiative channels, they are by default non-Hermitian objects having complex eigenvalues (poles and ...

Washington2023

Singular quadratic eigenvalue problems: linearization and weak condition numbers

Daniel Kressner, Ivana Sain Glibic

The numerical solution of singular eigenvalue problems is complicated by the fact that small perturbations of the coefficients may have an arbitrarily bad effect on eigenvalue accuracy. However, it has been known for a long time that such perturbations are ...

SPRINGER2023

Finding stationary points on bounded-rank matrices: a geometric hurdle and a smooth remedy

Nicolas Boumal

We consider the problem of provably finding a stationary point of a smooth function to be minimized on the variety of bounded-rank matrices. This turns out to be unexpectedly delicate. We trace the difficulty back to a geometric obstacle: On a nonsmooth se ...

SPRINGER HEIDELBERG2022

TimeEvolver: A program for time evolution with improved error bound

Sebastian Zell

We present TimeEvolver, a program for computing time evolution in a generic quantum system. It relies on well-known Krylov subspace techniques to tackle the problem of multiplying the exponential of a large sparse matrix iH, where His the Hamiltonian, with ...

ELSEVIER2022

Robust Differentiable SVD

Pascal Fua, Mathieu Salzmann, Zheng Dang, Wei Wang, Yinlin Hu

Eigendecomposition of symmetric matrices is at the heart of many computer vision algorithms. However, the derivatives of the eigenvectors tend to be numerically unstable, whether using the SVD to compute them analytically or using the Power Iteration (PI) ...

2021

Symplectic dynamical low rank approximation of wave equations with random parameters

Fabio Nobile, Eleonora Musharbash, Eva Vidlicková

In this paper we propose a dynamical low-rank strategy for the approximation of second order wave equations with random parameters. The governing equation is rewritten in Hamiltonian form and the approximate solution is expanded over a set of 2S dynamical ...

2020

Symplectic Dynamical Low Rank approximation of wave equations with random parameters

Fabio Nobile, Eleonora Musharbash

In this paper we propose a dynamical low-rank strategy for the approximation of second order wave equations with random parameters. The governing equation is rewritten in Hamiltonian form and the approximate solution is expanded over a set of

2S

dynamica ...

2017

MATHICSE Technical Report : Symplectic dynamical low rank approximation of wave equations with random parameters

Fabio Nobile, Eleonora Musharbash, Eva Vidlicková

In this paper we propose a dynamical low-rank strategy for the approximation of second order wave equations with random parameters. The governing equation is rewritten in Hamiltonian form and the approximate solution is expanded over a set of 2S dynamical ...

MATHICSE2017

Dynamical Low Rank approximation of PDEs with random parameters

Eleonora Musharbash

In this work, we focus on the Dynamical Low Rank (DLR) approximation of PDEs equations with random parameters. This can be interpreted as a reduced basis method, where the approximate solution is expanded in separable form over a set of few deterministic b ...

EPFL2017

Low rank differential equations for Hamiltonian matrix nearness problems

Graph Chatbot

Chat with Graph Search

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

Asymmetric phase modulation of light with parity-symmetry broken metasurfaces

Singular quadratic eigenvalue problems: linearization and weak condition numbers

Finding stationary points on bounded-rank matrices: a geometric hurdle and a smooth remedy

TimeEvolver: A program for time evolution with improved error bound

Robust Differentiable SVD

Symplectic dynamical low rank approximation of wave equations with random parameters

Symplectic Dynamical Low Rank approximation of wave equations with random parameters

MATHICSE Technical Report : Symplectic dynamical low rank approximation of wave equations with random parameters

Dynamical Low Rank approximation of PDEs with random parameters

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

TimeEvolver: A program for time evolution with improved error bound

Robust Differentiable SVD

Asymmetric phase modulation of light with parity-symmetry broken metasurfaces

Symplectic dynamical low rank approximation of wave equations with random parameters

Singular quadratic eigenvalue problems: linearization and weak condition numbers

Symplectic Dynamical Low Rank approximation of wave equations with random parameters

Finding stationary points on bounded-rank matrices: a geometric hurdle and a smooth remedy

MATHICSE Technical Report : Symplectic dynamical low rank approximation of wave equations with random parameters

Dynamical Low Rank approximation of PDEs with random parameters