2016
DOI: 10.1007/s00220-016-2805-6
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Local Law of Addition of Random Matrices on Optimal Scale

Abstract: Abstract:The eigenvalue distribution of the sum of two large Hermitian matrices, when one of them is conjugated by a Haar distributed unitary matrix, is asymptotically given by the free convolution of their spectral distributions. We prove that this convergence also holds locally in the bulk of the spectrum, down to the optimal scales larger than the eigenvalue spacing. The corresponding eigenvectors are fully delocalized. Similar results hold for the sum of two real symmetric matrices, when one is conjugated … Show more

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Cited by 40 publications
(86 citation statements)
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References 34 publications
(78 reference statements)
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“…Finally, we remark that the local stability result is also a key ingredient in [3], where we were able to prove a local law down to the smallest possible scale η ≫ N −1 , but with a weaker error bound than in Theorem 2.8; see Remark 2.4 for details. Acknowledgment.…”
Section: Introductionmentioning
confidence: 76%
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“…Finally, we remark that the local stability result is also a key ingredient in [3], where we were able to prove a local law down to the smallest possible scale η ≫ N −1 , but with a weaker error bound than in Theorem 2.8; see Remark 2.4 for details. Acknowledgment.…”
Section: Introductionmentioning
confidence: 76%
“…Comparing with (2.28), we see that we can choose η in (2.31) almost as small as N −1 at the price of losing a factor √ N . The stability and perturbation analysis in [3] rely on the optimal results in Theorem 2.5 and Theorem 2.7 as well as in Sections 3-5 of the present paper.…”
Section: 32mentioning
confidence: 99%
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“…(iv) The convolution model D 1 + U * D 2 U , where D 1 , D 2 are diagonal and U is uniform on O(N ), appears in free probability theory. Its empirical spectral measure in understood up to the optimal scale [10], and GOE bulk statistics were proved in [34].…”
mentioning
confidence: 99%