Can one hear a matrix? Recovering a real symmetric matrix from its spectral data

TL;DR

This paper investigates how to uniquely reconstruct real symmetric matrices from spectral data, identifying necessary spectral and sign information, and demonstrates the feasibility of reconstruction for banded matrices, especially pentadiagonal ones.

Contribution

It specifies the spectral and sign data needed for unique matrix reconstruction and shows how redundancy in spectral data enables reconstruction of generic banded matrices.

Findings

Unique reconstruction of general matrices with spectral and sign data.

Redundancy in spectral data guarantees reconstruction of generic banded matrices.

Detailed construction for pentadiagonal matrices.

Abstract

The spectrum of a real and symmetric $N\times N$ matrix determines the matrix up to unitary equivalence. More spectral data is needed together with some sign indicators to remove the unitary ambiguities. In the first part of this work we specify the spectral and sign information required for a unique reconstruction of general matrices. More specifically, the spectral information consists of the spectra of the $N$ nested main minors of the original matrix of the sizes $1,2,\dots,N$. However, due to the complicated nature of the required sign data, improvements are needed in order to make the reconstruction procedure feasible. With this in mind, the second part is restricted to banded matrices where the amount of spectral data exceeds the number of the unknown matrix entries. It is shown that one can take advantage of this redundancy to guarantee unique reconstruction of {\it generic} matrices, in other words, this subset of matrices is open, dense and of full measure in the set of real, symmetric and banded matrices. It is shown that one can optimize the ratio between redundancy and genericity by using the freedom of choice of the spectral information input. We demonstrate our constructions in detail for pentadiagonal matrices.