Random Matrix Eigenvalues (Multiple Distributions)     random-matrices

Leonid Petrov


Simulation Info

Random Matrix Eigenvalues (Multiple Distributions)     random-matrices

Leonid Petrov

Eigenvalue histogram for Wigner random matrices with selectable entry distributions (uniform, exponential, Cauchy, Bernoulli, semicircle), overlaid with the semicircle law curve. Point process scatter plots show top 10 and 20 near-zero eigenvalues. A color heatmap displays matrix entries. Adjust matrix size N and distribution type.

This simulation uses WebAssembly and the Eigen library to compute eigenvalues of an N×N random matrix whose entries are drawn from one of the following distributions: uniform, exponential, Cauchy, Bernoulli, semicircle, each normalized to have mean 0 and variance (or nominal scale) 1/sqrt(N). Select the distribution below, choose a matrix size, and hit "Generate & Plot Eigenvalues" to see the resulting spectrum, top eigenvalues, a heatmap of the matrix, etc.

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Top 5 Eigenvalues:
5 Eigenvalues around zero:
Top 10 Eigenvalues (Point Process):
20 Eigenvalues Around Zero (Point Process):
Histogram of eigenvalues:
Heatmap of matrix elements:

code

(note: parameters in the code might differ from the ones in simulation results below)

Dear colleagues:

Feel free to use code (unless otherwise specified next to the corresponding link), data, and visualizations to illustrate your research in talks and papers, with attribution (CC BY-SA 4.0 (opens in new tab)). Some images are available in very high resolution upon request. I can also produce other simulations upon request - email me at lenia.petrov@gmail.com
This material is based upon work supported by the National Science Foundation under Grant DMS-2153869