Accuracy of approximate projection to the semidefinite cone

08/05/2019
by   Paul J. Goulart, et al.
0

When a projection of a symmetric or Hermitian matrix to the positive semidefinite cone is computed approximately (or to working precision on a computer), a natural question is to quantify its accuracy. A straightforward bound invoking standard eigenvalue perturbation theory (e.g. Davis-Kahan and Weyl bounds) suggests that the accuracy would be inversely proportional to the spectral gap, implying it can be poor in the presence of small eigenvalues. This work shows that a small gap is not a concern for projection onto the semidefinite cone, by deriving error bounds that are gap-independent.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/12/2021

Matrix pencils with coefficients that have positive semidefinite Hermitian part

We analyze when an arbitrary matrix pencil is equivalent to a dissipativ...
research
06/06/2022

New lower bounds on crossing numbers of K_m,n from permutation modules and semidefinite programming

In this paper, we use semidefinite programming and representation theory...
research
04/18/2023

Optimal Eigenvalue Approximation via Sketching

Given a symmetric matrix A, we show from the simple sketch GAG^T, where ...
research
05/19/2017

A lower bound on the positive semidefinite rank of convex bodies

The positive semidefinite rank of a convex body C is the size of its sma...
research
06/12/2019

A Strengthening of the Perron-Frobenius Theorem

It is well known from the Perron-Frobenius theory that the spectral gap ...
research
06/12/2019

Spectral Ratio for Positive Matrices

It is well known from the Perron-Frobenius theory that the spectral gap ...

Please sign up or login with your details

Forgot password? Click here to reset