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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
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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.
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RANDOM MATRIX THEORY AND FINANCIAL CORRELATIONS

International Journal of Theoretical and Applied Finance, 2000
We show that results from the theory of random matrices are potentially of great interest when trying to understand the statistical structure of the empirical correlation matrices appearing in the study of multivariate financial time series. We find a remarkable agreement between the theoretical prediction (based on the assumption that the correlation
Laloux, Laurent   +3 more
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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 ...
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On Random Matrix Theory for stationary processes

2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 2010
Random Matrix Theory has generated tremendous interest in recent years, partly from powerful results developed for multi-user detection theory but also for growing applications in statistics, signal processing and econometrics. However the current theory has emphasized white noise data.
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On Random Matrix Theory and Autoregressive Modeling

2019 IEEE 58th Conference on Decision and Control (CDC), 2019
Random matrix theory has attracted growing interest in signal processing and communications over the last one or two decades. It has gained further impetus due to the upsurge in the occurrence of ’big data’. However so far little of this interest has seeped into system identification.
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Test of the Eigenstate Thermalization Hypothesis Based on Local Random Matrix Theory

Physical Review Letters, 2021
Shoki Sugimoto   +2 more
exaly  

Eigenstate Thermalization Hypothesis and Its Deviations from Random-Matrix Theory beyond the Thermalization Time

Physical Review Letters, 2022
Jiaozi Wang   +2 more
exaly  

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