scholarly journals Isospectral Twirling and Quantum Chaos

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 1073
Author(s):  
Lorenzo Leone ◽  
Salvatore F. E. Oliviero ◽  
Alioscia Hamma
Keyword(s):  
Random Matrix ◽  
Finite Time ◽  
Quantum Chaos ◽  
Matrix Theory ◽  
Time Behavior ◽  
Unified Framework ◽  
Expectation Value ◽  
Gaussian Unitary Ensemble ◽  
Loschmidt Echo ◽  
Unitary Ensemble

We show that the most important measures of quantum chaos, such as frame potentials, scrambling, Loschmidt echo and out-of-time-order correlators (OTOCs), can be described by the unified framework of the isospectral twirling, namely the Haar average of a k-fold unitary channel. We show that such measures can then always be cast in the form of an expectation value of the isospectral twirling. In literature, quantum chaos is investigated sometimes through the spectrum and some other times through the eigenvectors of the Hamiltonian generating the dynamics. We show that thanks to this technique, we can interpolate smoothly between integrable Hamiltonians and quantum chaotic Hamiltonians. The isospectral twirling of Hamiltonians with eigenvector stabilizer states does not possess chaotic features, unlike those Hamiltonians whose eigenvectors are taken from the Haar measure. As an example, OTOCs obtained with Clifford resources decay to higher values compared with universal resources. By doping Hamiltonians with non-Clifford resources, we show a crossover in the OTOC behavior between a class of integrable models and quantum chaos. Moreover, exploiting random matrix theory, we show that these measures of quantum chaos clearly distinguish the finite time behavior of probes to quantum chaos corresponding to chaotic spectra given by the Gaussian Unitary Ensemble (GUE) from the integrable spectra given by Poisson distribution and the Gaussian Diagonal Ensemble (GDE).

scholarly journals Replica approach in random matrix theory

2018 ◽  
Author(s):  
Thomas Guhr
Keyword(s):  
Partition Function ◽  
Random Matrix Theory ◽  
Random Matrix ◽  
Matrix Theory ◽  
Field Theories ◽  
Partition Functions ◽  
Gaussian Unitary Ensemble ◽  
Integrable Theory ◽  
Unitary Ensemble ◽  
Replica Approach

This article examines the replica method in random matrix theory (RMT), with particular emphasis on recently discovered integrability of zero-dimensional replica field theories. It first provides an overview of both fermionic and bosonic versions of the replica limit, along with its trickery, before discussing early heuristic treatments of zero-dimensional replica field theories, with the goal of advocating an exact approach to replicas. The latter is presented in two elaborations: by viewing the β = 2 replica partition function as the Toda lattice and by embedding the replica partition function into a more general theory of τ functions. The density of eigenvalues in the Gaussian Unitary Ensemble (GUE) and the saddle point approach to replica field theories are also considered. The article concludes by describing an integrable theory of replicas that offers an alternative way of treating replica partition functions.

scholarly journals Distribution of the Dirac modes in QCD

2018 ◽  
Vol 175 ◽  
pp. 04005
Author(s):  
M. Catillo ◽  
L. Ya. Glozman
Keyword(s):  
Dirac Operator ◽  
Random Matrix Theory ◽  
Random Matrix ◽  
General Property ◽  
Matrix Theory ◽  
Spontaneous Breaking ◽  
Gaussian Unitary Ensemble ◽  
Zero Modes ◽  
Dynamical Simulations ◽  
Unitary Ensemble

It was established that distribution of the near-zero modes of the Dirac operator is consistent with the Chiral Random Matrix Theory (CRMT) and can be considered as a consequence of spontaneous breaking of chiral symmetry (SBCS) in QCD. The higherlying modes of the Dirac operator carry information about confinement physics and are not affected by SBCS. We study distributions of the near-zero and higher-lying modes of the overlap Dirac operator within NF = 2 dynamical simulations. We find that distributions of both near-zero and higher-lying modes are the same and follow the Gaussian Unitary Ensemble of Random Matrix Theory. This means that randomness, while consistent with SBCS, is not a consequence of SBCS and is related to some more general property of QCD in confinement regime.

scholarly journals Distribution law of the Dirac eigenmodes in QCD

2018 ◽  
Vol 33 (10) ◽  
pp. 1850054
Author(s):  
Marco Catillo ◽  
Leonid Ya. Glozman
Keyword(s):  
Dirac Operator ◽  
Random Matrix Theory ◽  
Random Matrix ◽  
Matrix Theory ◽  
Spontaneous Breaking ◽  
Distribution Law ◽  
Gaussian Unitary Ensemble ◽  
Zero Modes ◽  
Dynamical Simulations ◽  
Unitary Ensemble

The near-zero modes of the Dirac operator are connected to spontaneous breaking of chiral symmetry in QCD (SBCS) via the Banks–Casher relation. At the same time, the distribution of the near-zero modes is well described by the Random Matrix Theory (RMT) with the Gaussian Unitary Ensemble (GUE). Then, it has become a standard lore that a randomness, as observed through distributions of the near-zero modes of the Dirac operator, is a consequence of SBCS. The higher-lying modes of the Dirac operator are not affected by SBCS and are sensitive to confinement physics and related [Formula: see text] and [Formula: see text] symmetries. We study the distribution of the near-zero and higher-lying eigenmodes of the overlap Dirac operator within [Formula: see text] dynamical simulations. We find that both the distributions of the near-zero and higher-lying modes are perfectly described by GUE of RMT. This means that randomness, while consistent with SBCS, is not a consequence of SBCS and is linked to the confining chromo-electric field.

Introduction and guide to the handbook

2018 ◽  
Author(s):  
Gernot Akemann ◽  
Jinho Baik ◽  
Philippe Di Francesco
Keyword(s):  
Random Matrices ◽  
Random Matrix Theory ◽  
Random Matrix ◽  
Matrix Theory ◽  
The Other ◽  
Random Operators ◽  
New Developments ◽  
Gaussian Unitary Ensemble ◽  
Mathematical Properties ◽  
Unitary Ensemble

This article discusses random matrix theory (RMT) in a nutshell — what it is about, what its main features are, and why it is so successful in applications. It first considers the simplest and maybe most frequently used standard example, the Gaussian Unitary Ensemble (GUE) of random matrices, before looking at several types of applications of RMT, focusing on random operators, counting devices, and RMT without matrices. It then provides a guide to the handbook, explaining how the other forty-two articles on mathematical properties and applications of random matrices are related and built one upon the other. It also lists some topics that are not covered in detail in the book and reviews recent new developments since the first edition of this handbook before concluding with a brief survey of the existing introductory literature.

Generalization of Brody distribution for statistical investigation

2014 ◽  
Vol 03 (04) ◽  
pp. 1450017 ◽  
Author(s):  
H. Sabri ◽  
Sh. S. Hashemi ◽  
B. R. Maleki ◽  
M. A. Jafarizadeh
Keyword(s):  
Nearest Neighbor ◽  
Matrix Theory ◽  
Likelihood Estimation ◽  
Statistical Investigation ◽  
Distribution Functions ◽  
Estimation Methods ◽  
General Distribution ◽  
Gaussian Unitary Ensemble ◽  
Gaussian Orthogonal Ensemble ◽  
Unitary Ensemble

In this paper, Brody distribution is generalized to explore the Poisson, Gaussian Orthogonal Ensemble and Gaussian Unitary Ensemble limits of Random Matrix Theory in the nearest neighbor spacing statistic framework. Parameters of new distribution are extracted via Maximum Likelihood Estimation technique for different sequences. This general distribution suggests more exact results in comparison with the results of other estimation methods and distribution functions.

scholarly journals Permutations Without Long Decreasing Subsequences and Random Matrices

10.37236/929 ◽  
2007 ◽  
Vol 14 (1) ◽  
Author(s):  
Piotr Šniady
Keyword(s):  
Random Matrices ◽  
Young Diagram ◽  
Random Matrix ◽  
Random Permutation ◽  
Fixed Number ◽  
Plancherel Measure ◽  
Young Diagrams ◽  
Gaussian Unitary Ensemble ◽  
Longest Increasing Subsequence ◽  
Unitary Ensemble

We study the shape of the Young diagram $\lambda$ associated via the Robinson–Schensted–Knuth algorithm to a random permutation in $S_n$ such that the length of the longest decreasing subsequence is not bigger than a fixed number $d$; in other words we study the restriction of the Plancherel measure to Young diagrams with at most $d$ rows. We prove that in the limit $n\to\infty$ the rows of $\lambda$ behave like the eigenvalues of a certain random matrix (namely the traceless Gaussian Unitary Ensemble random matrix) with $d$ rows and columns. In particular, the length of the longest increasing subsequence of such a random permutation behaves asymptotically like the largest eigenvalue of the corresponding random matrix.

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