2009
DOI: 10.1063/1.3093266
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Bulk asymptotics of skew-orthogonal polynomials for quartic double well potential and universality in the matrix model

Abstract: We derive bulk asymptotics of skew-orthogonal polynomials (sop) π (β) m , β = 1, 4, defined w.r.t. the weight exp(−2N V (x)), V (x) = gx 4 /4 + tx 2 /2, g > 0 and t < 0. We assume that as m, N → ∞ there exists an ǫ > 0, such that ǫ ≤ (m/N ) ≤ λcr − ǫ, where λcr is the critical value which separates sop with two cuts from those with one cut. Simultaneously we derive asymptotics for the recursive coefficients of skew-orthogonal polynomials. The proof is based on obtaining a finite term recursion relation between… Show more

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“…We would like to emphasize that the key step in deriving the asymptotic results of SOP is to obtain and solve finite term recursion relations between SOP and OP. Recently, this technique has been used to obtain bulk asymptotics of SOP corresponding to quartic double well potential [7]. Till date, this seems the easier method to study the asymptotic behavior of SOP rather than solving the 2d × 2d Riemann Hilbert problem [6,45].…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…We would like to emphasize that the key step in deriving the asymptotic results of SOP is to obtain and solve finite term recursion relations between SOP and OP. Recently, this technique has been used to obtain bulk asymptotics of SOP corresponding to quartic double well potential [7]. Till date, this seems the easier method to study the asymptotic behavior of SOP rather than solving the 2d × 2d Riemann Hilbert problem [6,45].…”
Section: Discussionmentioning
confidence: 99%
“…The second and perhaps a more enriching method is to evaluate the kernel functions directly in terms of skew-orthogonal polynomials/skew-orthogonal functions (SOP) and use asymptotic properties of these functions [27]. For this, we need to develop the theory of SOP [3][4][5][6][7][8][28][29][30][31][32] so that we can have further insight into orthogonal and symplectic ensembles of random matrices.…”
Section: Random Matricesmentioning
confidence: 99%