We study moments of characteristic polynomials of truncated Haar distributed matrices from the three classical compact groups O(N), U(N) and Sp(2N). For finite matrix size we calculate the moments in terms of hypergeometric functions of matrix argument and give explicit integral representations highlighting the duality between the moment and the matrix size as well as the duality between the orthogonal and symplectic cases. Asymptotic expansions in strong and weak non-unitarity regimes are obtained. Using the connection to matrix hypergeometric functions, we establish limit theorems for the log-modulus of the characteristic polynomial evaluated on the unit circle
10 pages, latexIn a recent article we have discussed the connections between averages of powers of R...
In this article, we study the large N asymptotics of complex moments of the absolute value of the ch...
We study the ‘critical moments’ of subcritical Gaussian multiplicative chaos (GMCs) in dimensions d≤...
We establish formulae for the moments of the moments of the characteristic polynomials of random ort...
We calculate the moments of the characteristic polynomials of N × N matrices drawn from the Hermitia...
Denoting by PN(A, θ) = det (I- Ae-iθ) the characteristic polynomial on the unit circle in the comple...
An asymptotic formula for the 2kth moment of a sum of multiplicative Steinahus variables is given. T...
In this note, we give a combinatorial and noncomputational proof of the asymptotics of the integer m...
Abstract. We present a simple technique to compute moments of derivatives of unitary characteristic ...
This is the author accepted manuscript. The final version is available from World Scientific Publish...
Based on the multivariate saddle point method we study the asymptotic behavior of the characteristic...
We study moments of the logarithmic derivative of characteristic polynomials of orthogonal and sympl...
We establish the asymptotics of the joint moments of the characteristic polynomial of a random unita...
Motivated by recent results in random matrix theory we will study the distributions arising from pro...
Following the work of Conrey, Rubinstein, and Snaith [Commun. Math. Phys. 267, 611 (2006)] and Forre...
10 pages, latexIn a recent article we have discussed the connections between averages of powers of R...
In this article, we study the large N asymptotics of complex moments of the absolute value of the ch...
We study the ‘critical moments’ of subcritical Gaussian multiplicative chaos (GMCs) in dimensions d≤...
We establish formulae for the moments of the moments of the characteristic polynomials of random ort...
We calculate the moments of the characteristic polynomials of N × N matrices drawn from the Hermitia...
Denoting by PN(A, θ) = det (I- Ae-iθ) the characteristic polynomial on the unit circle in the comple...
An asymptotic formula for the 2kth moment of a sum of multiplicative Steinahus variables is given. T...
In this note, we give a combinatorial and noncomputational proof of the asymptotics of the integer m...
Abstract. We present a simple technique to compute moments of derivatives of unitary characteristic ...
This is the author accepted manuscript. The final version is available from World Scientific Publish...
Based on the multivariate saddle point method we study the asymptotic behavior of the characteristic...
We study moments of the logarithmic derivative of characteristic polynomials of orthogonal and sympl...
We establish the asymptotics of the joint moments of the characteristic polynomial of a random unita...
Motivated by recent results in random matrix theory we will study the distributions arising from pro...
Following the work of Conrey, Rubinstein, and Snaith [Commun. Math. Phys. 267, 611 (2006)] and Forre...
10 pages, latexIn a recent article we have discussed the connections between averages of powers of R...
In this article, we study the large N asymptotics of complex moments of the absolute value of the ch...
We study the ‘critical moments’ of subcritical Gaussian multiplicative chaos (GMCs) in dimensions d≤...