Polynomial-factor concentration conjecture for determinants of random matrices

Let cCc \le C be positive constants. Let AA be the random matrix of size nn whose entries are independent random variables with mean zero and variances between cc and CC. Polynomial-factor concentration conjecture. With probability tending to one,

detA=nO(1)EdetA,detA2=nO(1)E(detA2).|{\rm {\det}} A| = n^{O(1)}\mathop{\mathbf{E}} |{\rm {\det}} A|, \qquad {\rm {\det}} A^2 = n^{O(1)}\mathop{\mathbf{E}}({\rm {\det}} A^2).

The conjecture would strengthen the paper's sub-exponential-factor estimate for determinant-based permanent estimators to a polynomial-factor approximation. It is motivated by the corresponding Gaussian result, while the analogous general central-limit statement attributed to Girko is described as believed but unproved by the authors.

Sources & referencesView supporting material

Primary source

Kevin P. Costello and Van Vu, “Concentration of random determinants and permanent estimators”, arXiv:0905.1909 (2009).

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