English

How many matrices can be spectrally balanced simultaneously?

Functional Analysis 2016-06-07 v1 Probability

Abstract

We prove that any \ell positive definite d×dd \times d matrices, M1,,MM_1,\ldots,M_\ell, of full rank, can be simultaneously spectrally balanced in the following sense: for any k<dk < d such that d1k1\ell \leq \lfloor \frac{d-1}{k-1} \rfloor, there exists a matrix AA satisfying λ1(ATMiA)Tr(ATMiA)<1k\frac{\lambda_1(A^T M_i A) }{ \mathrm{Tr}( A^T M_i A ) } < \frac{1}{k} for all ii, where λ1(M)\lambda_1(M) denotes the largest eigenvalue of a matrix MM. This answers a question posed by Peres, Popov and Sousi and completes the picture described in that paper regarding sufficient conditions for transience of self-interacting random walks. Furthermore, in some cases we give quantitative bounds on the transience of such walks.

Keywords

Cite

@article{arxiv.1606.01680,
  title  = {How many matrices can be spectrally balanced simultaneously?},
  author = {Ronen Eldan and Fedor Nazarov and Yuval Peres},
  journal= {arXiv preprint arXiv:1606.01680},
  year   = {2016}
}
R2 v1 2026-06-22T14:18:29.193Z