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Funktsional'nyi Analiz i ego Prilozheniya, 2015, Volume 49, Issue 3, Pages 70–74
DOI: https://doi.org/10.4213/faa3203 (Mi faa3203) 		 
This article is cited in 3 scientific papers (total in 3 papers)

Brief communications

Determinantal Measures Related to Big $q$-Jacobi Polynomials

V. Gorinab, G. I. Olshanskiia

a Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevich Institute), Moscow
b Massachusetts Institute of Technology
Full-text PDF (185 kB) Citations (3)
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DOI: https://doi.org/10.4213/faa3203
Abstract: We define a novel combinatorial object—the extended Gelfand–Tsetlin graph with cotransition probabilities depending on a parameter $q$. The boundary of this graph admits an explicit description. We introduce a family of probability measures on the boundary and describe their correlation functions. These measures are a $q$-analogue of the spectral measures studied earlier in the context of the problem of harmonic analysis on the infinite-dimensional unitary group.
Keywords: Gelfand–Tsetlin graph, determinantal measures, big $q$-Jacobi polynomials, basic hypergeometric series.
Funding agency Grant number
Russian Science Foundation 14-50-00150
Received: 23.03.2015
English version:
Functional Analysis and Its Applications, 2015, Volume 49, Issue 3, Pages 214–217
DOI: https://doi.org/10.1007/s10688-015-0107-y
Bibliographic databases:
Document Type: Article
UDC: 517.587+517.588
Language: Russian
Citation: V. Gorin, G. I. Olshanskii, “Determinantal Measures Related to Big $q$-Jacobi Polynomials”, Funktsional. Anal. i Prilozhen., 49:3 (2015), 70–74; Funct. Anal. Appl., 49:3 (2015), 214–217
Citation in format AMSBIB
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\paper Determinantal Measures Related to Big $q$-Jacobi Polynomials
\jour Funktsional. Anal. i Prilozhen.
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    • This publication is cited in the following 3 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    		Функциональный анализ и его приложения Functional Analysis and Its Applications
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