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M S Santhanam

Publications and source records attributed to M S Santhanam.

5 recordsLinked to original sources

Quantum spectrum as a time series: fluctuation measures.

The fluctuations in the quantum spectrum could be treated like a time series. In this framework, we explore the statistical self-similarity in the quantum spectrum using the detrended fluctuation analysis (DFA) and random matrix theory (RMT). We calculate the Hausdorff measure for the spectra of atoms and Gaussian ensembles and study their self-affine properties. We show that DFA is equivalent to the Delta3 statistics of RMT, unifying two different approaches. We exploit this connection to obtain theoretical estimates for the Hausdorff measure.

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Spectral fluctuations and 1/f noise in the order-chaos transition regime.

Level fluctuations in a quantum system have been used to characterize quantum chaos using random matrix models. Recently time series methods were used to relate the level fluctuations to the classical dynamics in the regular and chaotic limit. In this, we show that the spectrum of the system undergoing order to chaos transition displays a characteristic f(-gamma) noise and gamma is correlated with the classical chaos in the system. We demonstrate this using a smooth potential and a time-dependent system modeled by Gaussian and circular ensembles, respectively, of random matrix theory. We show the effect of short periodic orbits on these fluctuation measures.

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Random matrix approach to multivariate correlations: some limiting cases.

Recent advances have shown that the empirical correlation matrices of dynamical systems can be modeled as random matrices, for most part, chosen from an appropriate ensemble of the random matrix theory (RMT). In this work, we study certain limiting cases where this approach could potentially break down. Using a combination of analytical and numerical tools, we especially study the eigenvalue density and its spacing distribution. We show that the correlation matrices obtained from multivariate spatiotemporal timeseries, in a regime of spatiotemporal chaos, lead to strong deviations from RMT. We illustrate the results with time-series data drawn from coupled map lattices. We also explore the transition to the RMT regime from the limiting cases.

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Statistics of atmospheric correlations.

For a large class of quantum systems, the statistical properties of their spectrum show remarkable agreement with random matrix predictions. Recent advances show that the scope of random matrix theory is much wider. In this work, we show that the random matrix approach can be beneficially applied to a completely different classical domain, namely, to the empirical correlation matrices obtained from the analysis of the basic atmospheric parameters that characterize the state of atmosphere. We show that the spectrum of atmospheric correlation matrices satisfy the random matrix prescription. In particular, the eigenmodes of the atmospheric empirical correlation matrices that have physical significance are marked by deviations from the eigenvector distribution.

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