Results 231 to 240 of about 8,430,397 (275)
Resource-Efficient Quantum Algorithms for Selected Hamiltonian Subspace Diagonalization. [PDF]
J Chem Theory ComputGraves V +3 more
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Reducing acquisition time and radiation damage: data-driven subsampling for spectro-microscopy. [PDF]
J Synchrotron RadiatMeier M +4 more
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LibppRPA: An open-source library for particle-particle random phase approximation. [PDF]
J Chem PhysYu J, Li J, Zhang C, Zhu T, Yang W.
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CrystalGRW: generative modeling of crystal structures with targeted crystallographic properties via geodesic random walks. [PDF]
Sci RepTangsongcharoen K +8 more
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Occupancy Statistics and Entropy in Bose Systems. [PDF]
Entropy (Basel)Spalvieri A.
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, 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
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2016
In this chapter the Gaussian random matrix ensembles are investigated. We determine their Green’s functions and show that for small energy differences a soft mode appears. As a consequence, the non-linear sigma-model is introduced and the level correlations are determined.
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In this chapter the Gaussian random matrix ensembles are investigated. We determine their Green’s functions and show that for small energy differences a soft mode appears. As a consequence, the non-linear sigma-model is introduced and the level correlations are determined.
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Acta Numerica, 2005
Random matrix theory is now a big subject with applications in many disciplines of science, engineering and finance. This article is a survey specifically oriented towards the needs and interests of a numerical analyst. This survey includes some original material not found anywhere else.
Alan Edelman, N. Raj Rao
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Random matrix theory is now a big subject with applications in many disciplines of science, engineering and finance. This article is a survey specifically oriented towards the needs and interests of a numerical analyst. This survey includes some original material not found anywhere else.
Alan Edelman, N. Raj Rao
openaire +1 more source
RANDOM MATRIX THEORY AND FINANCIAL CORRELATIONS
International Journal of Theoretical and Applied Finance, 2000We 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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