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On the deformed Pearcey determinant

  • Dan Dai
  • , Shuai-Xia Xu
  • , Lun Zhang*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

In this paper, we are concerned with the deformed Pearcey determinant det⁡ (I−γKs,ρPe), where  0 ≤ γ < 1 and Ks,ρPe stands for the trace class operator acting on L(−s,s) with the classical Pearcey kernel arising from random matrix theory. This determinant corresponds to the gap probability for the Pearcey process after thinning, which means each particle in the Pearcey process is removed independently with probability 1−γ. We establish an integral representation of the deformed Pearcey determinant involving the Hamiltonian associated with a family of special solutions to a system of nonlinear differential equations. Together with some remarkable differential identities for the Hamiltonian, this allows us to obtain the large gap asymptotics, including the exact calculation of the constant term, which complements our previous work on the undeformed case (i.e., γ=1). It comes out that the deformed Pearcey determinant exhibits a significantly different asymptotic behavior from the undeformed case, which suggests a transition will occur as the parameter γ varies. As an application of our results, we obtain the asymptotics for the expectation and variance of the counting function for the Pearcey process, and a central limit theorem as well.
Original languageEnglish
Article number108291
JournalAdvances in Mathematics
Volume400
Online published24 Feb 2022
DOIs
Publication statusPublished - 14 May 2022

Funding

We thank Christophe Charlier for helpful comments on this work. Dan Dai was partially supported by grants from the City University of Hong Kong (Project No. 7005597 and 7005252), and grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. CityU 11303016 and CityU 11300520). Shuai-Xia Xu was partially supported by National Natural Science Foundation of China under grant numbers 11971492, 11571376 and 11201493, and Natural Science Foundation for Distinguished Young Scholars of Guangdong Province of China. Lun Zhang was partially supported by National Natural Science Foundation of China under grant numbers 11822104 and 11501120, “Shuguang Program” supported by Shanghai Education Development Foundation and Shanghai Municipal Education Commission, and The Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning.

Research Keywords

  • Asymptotic analysis
  • Pearcey determinant
  • Random matrix theory
  • Riemann-Hilbert problems

RGC Funding Information

  • RGC-funded

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