2012
DOI: 10.1007/jhep08(2012)066
|View full text |Cite
|
Sign up to set email alerts
|

Level spacings for weakly asymmetric real random matrices and application to two-color QCD with chemical potential

Abstract: We consider antisymmetric perturbations of real symmetric matrices in the context of random matrix theory and two-color quantum chromodynamics. We investigate the level spacing distributions of eigenvalues that remain real or become complex conjugate pairs under the perturbation. We work out analytical surmises from small matrices and show that they describe the level spacings of large random matrices. As expected from symmetry arguments, these level spacings also apply to the overlap Dirac operator for two-co… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
7
0

Year Published

2012
2012
2016
2016

Publication Types

Select...
6

Relationship

1
5

Authors

Journals

citations
Cited by 6 publications
(7 citation statements)
references
References 61 publications
(82 reference statements)
0
7
0
Order By: Relevance
“…In investigating the (de)localization of the eigenstates, Feinberg and Zee [10], argued that imaginary eigenvalues near the real axis can attract when perturbed by a Hermitian matrix by providing a 2 × 2 example of an imaginary diagonal matrix perturbed by a 2 × 2 Hermitian matrix with zero diagonal entries. Later, Bloch et al [15] considered antisymmetric perturbations of real symmetric matrices in the context of two-color quantum chromodynamics and provided examples that a Hermitian matrix perturbed by a real antisymmetric perturbation can give rise to attraction of eigenvalues. To our knowledge, attraction of the eigenvalues and their eventual aggregation on the real line, in a general setting, has not been proved.…”
Section: A Backgroundmentioning
confidence: 99%
See 1 more Smart Citation
“…In investigating the (de)localization of the eigenstates, Feinberg and Zee [10], argued that imaginary eigenvalues near the real axis can attract when perturbed by a Hermitian matrix by providing a 2 × 2 example of an imaginary diagonal matrix perturbed by a 2 × 2 Hermitian matrix with zero diagonal entries. Later, Bloch et al [15] considered antisymmetric perturbations of real symmetric matrices in the context of two-color quantum chromodynamics and provided examples that a Hermitian matrix perturbed by a real antisymmetric perturbation can give rise to attraction of eigenvalues. To our knowledge, attraction of the eigenvalues and their eventual aggregation on the real line, in a general setting, has not been proved.…”
Section: A Backgroundmentioning
confidence: 99%
“…Later, Bloch et al [15] considered antisymmetric perturbations of real symmetric matrices in the context of two-color quantum chromodynamics and provided examples that a Hermitian matrix perturbed by a real antisymmetric perturbation can give rise to attraction of eigenvalues. To our knowledge, attraction of the eigenvalues and their eventual aggregation on the real line, in a general setting, has not been proved.…”
Section: Introductionmentioning
confidence: 99%
“…As our method adopts the level spacing and the smallest eigenvalue distributions that are extremely sensitive to the fitting parameter as primary fitting observables (see Refs. [36][37][38] for recent efforts along this line), it enjoys a clear advantage over the methods using n-level correlation functions, and presents promising applications in analyzing the numerical data of QCD-like theories.…”
Section: Introductionmentioning
confidence: 99%
“…The effect of this is best understood by first considering the impact on eigenvalues of the opposite transformation: gradually adding off-diagonal elements to a diagonal matrix. A simple perturbation analysis (e.g., Bloch et al 2012), strictly valid only when the off-diagonal entries of G are small compared to the diagonal entries, already gives the general trends, which can be confirmed numerically for larger off-diagonal entries: When exploitative interaction, where G ij and G ji (i = j) have opposite signs, dominate (as for direct predator-prey interactions), the off-diagonal entries lead to a narrowing of the eigenvalue distribution along the real axis. The general expectation, e.g., with statistically unrelated or positively correlated G ij and G ji , however, is that the distribution will be broadened, see, e.g.…”
Section: S7 Effects Of Structural Instability Of the Management Modelmentioning
confidence: 99%