Characteristic Polynomials of Random Matrices and Noncolliding Diffusion Processes

Mathematics – Probability

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

AMS_LaTeX, 26 pages, no figure

Scientific paper

We consider the noncolliding Brownian motion (BM) with $N$ particles starting from the eigenvalue distribution of Gaussian unitary ensemble (GUE) of $N \times N$ Hermitian random matrices with variance $\sigma^2$. We prove that this process is equivalent with the time shift $t \to t+\sigma^2$ of the noncolliding BM starting from the configuration in which all $N$ particles are put at the origin. In order to demonstrate nontriviality of such equivalence for determinantal processes, we show that, even from its special consequence, determinantal expressions are derived for the ensemble averages of products of characteristic polynomials of random matrices in GUE. Another determinantal process, noncolliding squared Bessel process with index $\nu >-1$, is also studied in parallel with the noncolliding BM and corresponding results for characteristic polynomials are given for random matrices in the chiral GUE as well as in the Gaussian ensembles of class C and class D.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Characteristic Polynomials of Random Matrices and Noncolliding Diffusion Processes does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Characteristic Polynomials of Random Matrices and Noncolliding Diffusion Processes, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Characteristic Polynomials of Random Matrices and Noncolliding Diffusion Processes will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-174224

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.