Results 321 to 330 of about 1,526,545 (357)
Some of the next articles are maybe not open access.

A First Course in Random Matrix Theory

, 2020
The real world is perceived and broken down as data, models and algorithms in the eyes of physicists and engineers. Data is noisy by nature and classical statistical tools have so far been successful in dealing with relatively smaller levels of ...
M. Potters, J. Bouchaud
semanticscholar   +1 more source

Random Matrix Theory

2017
Random matrix theory deals with the study of matrix-valued random variables. It is conventionally considered that random matrix theory dates back to the work of Wishart in 1928 [1] on the properties of matrices of the type XX † with X ε ℂ N×n a random matrix with independent Gaussian entries with zero mean and equal variance.
Couillet, Romain, Debbah, Merouane
openaire   +2 more sources

Complex Market Dynamics in the Light of Random Matrix Theory

New Economic Windows, 2018
We present a brief overview of random matrix theory (RMT) with the objectives of highlighting the computational results and applications in financial markets as complex systems.
Hirdesh K. Pharasi   +3 more
semanticscholar   +1 more source

Random Matrix Theory

1992
Before about 1956, there was no systematic statistical theory of nuclear energy level structure. There was a shortage of close spacings in experimentally obtained energy levels which was generally dismissed as being due to instrumental resolution failings.
openaire   +2 more sources

Random-Matrix Theory

2001
A wealth of empirical and numerical evidence suggests universality for local fluctuations in quantum energy or quasi-energy spectra of systems that display global chaos in their classical phase spaces. Exceptions apart, all such Hamiltonian matrices of sufficiently large dimension yield the same spectral fluctuations provided they have the same group ...
openaire   +2 more sources

Random Matrix Theory

2004
In this chapter, we will work not with \(\mathrm{GL}(n, \mathbb{C})\) but with its compact subgroup U(n). As in the previous chapters, we will consider elements of \(\mathcal{R}_{k}\) as generalized characters on S k . If \(\mathbf{f} \in \mathcal{R}_{k}\), then \(f ={ \mathrm{ch}}^{(n)}(\mathbf{f}) \in \varLambda _{k}^{(n)}\) is a symmetric polynomial
openaire   +2 more sources

Superanalysis for Random-Matrix Theory [PDF]

open access: possible, 2001
Gossip has it that the “supersymmetry technique” is difficult to learn. But quite to the contrary, representing determinants as Gaussian integrals over anticommuting alias Grassmann variables makes for great simplifications in computing averages over the underlying matrices, as we have seen in Chaps. 4 and 8. Even in the semiclassical work of Chap.
openaire   +1 more source

Bifurcations and random matrix theory

Europhysics Letters (EPL), 2001
The divergence of semiclassical amplitudes at periodic orbit bifurcations has strong effects on long-range spectral statistics. We discuss the statistical weight of such effects in parameter space, using as an example the quantised standard map as a function of the kicking strength.
Peter Pollner, Bruno Eckhardt
openaire   +2 more sources

Random Matrix Theory and Wireless Communications

Foundations and Trends in Communications and Information Theory, 2004
A. Tulino, S. Verdú
semanticscholar   +1 more source

Random matrix theory and the scaling theory of localization

Physical Review Letters, 1990
We consider the most probable value of conductance of a disordered quantum conductor in the framework of the random matrix theory developed earlier. Analytic calculations are possible in the metallic as well as strongly localized regimes. We make a simple assumption on the eigenvalue density, as suggested by numerical work, and explore the consequences
openaire   +3 more sources

Home - About - Disclaimer - Privacy