Can One Hear a Matrix? Recovering a Real Symmetric Matrix from Its Spectral Data

Tomasz Maciazek*, Uzy Smilansky

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

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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.
Original languageEnglish
JournalAnnales Henri Poincaré
Early online date17 Dec 2021
Publication statusE-pub ahead of print - 17 Dec 2021

Bibliographical note

Funding Information:
TM’s funding was provided by the University of Bristol (Vice-Chancellor’s fellowship).

Publisher Copyright:
© 2021, The Author(s).


  • Inverse methods
  • spectral analysis


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