Fluctuations of eigenvalues for random Toeplitz and related matrices
Consider random symmetric Toeplitz matrices Tn=(ai−j)[superscript n]i,j=1 with matrix entries aj,j=0,1,2,⋯, being independent real random variables such that E[aj]=0, E[|aj|2]=1 for j=0,1,2,⋯, (homogeneity of 4-th moments) κ=E[|aj|4], and further (uniform boundedness) supj≥0E[|aj|k]=Ck<∞ for...
| Main Authors: | , , |
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| Format: | Article |
| Language: | en_US |
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Institute of Mathematical Statistics
2014
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| Online Access: | http://hdl.handle.net/1721.1/89526 https://orcid.org/0000-0002-8579-1686 |
| Summary: | Consider random symmetric Toeplitz matrices Tn=(ai−j)[superscript n]i,j=1 with matrix entries aj,j=0,1,2,⋯, being independent real random variables such that E[aj]=0, E[|aj|2]=1 for j=0,1,2,⋯, (homogeneity of 4-th moments) κ=E[|aj|4], and further (uniform boundedness) supj≥0E[|aj|k]=Ck<∞ for k≥3. Under the assumption of a0≡0, we prove a central limit theorem for linear statistics of eigenvalues for a fixed polynomial with degree at least 2. Without this assumption, the CLT can be easily modified to a possibly non-normal limit law. In a special case where aj's are Gaussian, the result has been obtained by Chatterjee for some test functions. Our derivation is based on a simple trace formula for Toeplitz matrices and fine combinatorial analysis. Our method can apply to other related random matrix models, including Hermitian Toeplitz and symmetric Hankel matrices. Since Toeplitz matrices are quite different from Wigner and Wishart matrices, our results enrich this topic. |
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