Jacobi ensemble

E865110

The Jacobi ensemble is a family of random matrix models whose eigenvalue distributions are supported on a finite interval and are closely connected to classical orthogonal polynomials and beta-type probability measures.

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Statements (48)

Predicate Object
instanceOf probability distribution family
random matrix ensemble
arisesFrom eigenvalues of MANOVA-type random matrices
eigenvalues of ratios of Wishart matrices
dependsOn Dyson index β>0
matrix dimension n
shape parameters α>-1, γ>-1
generalizes classical Jacobi weight
hasAlternativeName Jacobi β-ensemble NERFINISHED
hasApplication quantum transport in mesoscopic systems
random eigenvalue problems with boundary constraints
hasConnectionTo Coulomb gas models on a finite interval
Selberg integral NERFINISHED
integrable probability
hasEdgeScalingLimit hard-edge universality
soft-edge universality (in appropriate regimes)
hasEigenvalueDistribution joint density supported on a compact interval
hasJointEigenvalueDensityProportionalTo ∏_{i<j} |λ_i-λ_j|^β ∏_{i} λ_i^{α} (1-λ_i)^{γ}
hasLimitingBehavior global eigenvalue density converges to a deterministic limit as matrix size grows
hasLimitingKernel Airy-type kernels at the soft edge
Bessel-type kernels at the hard edge
sine kernel in the bulk (for β=1,2,4 under standard scaling)
hasOrthogonalPolynomialSystem Jacobi polynomials with respect to w(x)=x^{α}(1-x)^{γ}
hasParameter α (shape parameter)
β (Dyson index)
γ (shape parameter)
hasSpecialCase orthogonal Jacobi ensemble (β=1) NERFINISHED
symplectic Jacobi ensemble (β=4) NERFINISHED
unitary Jacobi ensemble (β=2)
hasSupport [0,1] (after affine rescaling)
finite interval
hasSymmetryClass orthogonal/unitary/symplectic depending on β
isAssociatedWith beta distributions
beta-type measures
orthogonal polynomials
random matrix theory
isCharacterizedBy Vandermonde determinant to the power β in joint eigenvalue density
isConnectedTo Jacobi polynomials NERFINISHED
isDefinedOn space of eigenvalues λ_1,…,λ_n in (0,1)
isPartOf β-ensembles in random matrix theory
isRelatedTo Gaussian ensemble NERFINISHED
Laguerre ensemble NERFINISHED
isUsedIn multivariate statistics
signal processing
wireless communications
isUsedToModel canonical correlations in multivariate analysis
eigenvalue statistics of truncated unitary matrices
usesWeightFunction w(x)=x^{α}(1-x)^{γ} on [0,1]

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Selberg integral relatedTo Jacobi ensemble