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Moreillon, P. (2024). Density of the Free Additive Convolution of Multi-cut Measures. International mathematics research notices, 2024(23), 14178-14218
Open this publication in new window or tab >>Density of the Free Additive Convolution of Multi-cut Measures
2024 (English)In: International mathematics research notices, ISSN 1073-7928, E-ISSN 1687-0247, Vol. 2024, no 23, p. 14178-14218Article in journal (Refereed) Published
Abstract [en]

We consider the free additive convolution semigroup {μ<sup>t</sup> : t ≥ 1} and determine the local behavior of the density of μ<sup>t</sup> at the endpoints and at any singular point of its support. We then study the free additive convolution of two multi-cut probability measures and show that its density decays either as a square root or as a cubic root at any endpoint of its support. The probability measures considered in this paper satisfy a power law behavior with exponents strictly between −1 and 1 at the endpoints of their supports.

Place, publisher, year, edition, pages
Oxford University Press (OUP), 2024
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:kth:diva-366557 (URN)10.1093/imrn/rnae229 (DOI)001338010900001 ()2-s2.0-105008231930 (Scopus ID)
Note

QC 20250710

Available from: 2025-07-10 Created: 2025-07-10 Last updated: 2025-07-10Bibliographically approved
Charlier, C. & Moreillon, P. (2023). ON THE GENERATING FUNCTION OF THE PEARCEY PROCESS. The Annals of Applied Probability, 33(4), 3240-3277
Open this publication in new window or tab >>ON THE GENERATING FUNCTION OF THE PEARCEY PROCESS
2023 (English)In: The Annals of Applied Probability, ISSN 1050-5164, E-ISSN 2168-8737, Vol. 33, no 4, p. 3240-3277Article in journal (Refereed) Published
Abstract [en]

The Pearcey process is a universal point process in random matrix theory. In this paper, we study the generating function of the Pearcey process on any number m of intervals. We derive an integral representation for it in terms of a Hamiltonian that is related to a system of 6m + 2 coupled nonlinear equations. We also obtain asymptotics for the generating function as the size of the intervals get large, up to and including the constant term. This work generalizes some results of Dai, Xu, and Zhang, which correspond to m = 1.

Place, publisher, year, edition, pages
Institute of Mathematical Statistics, 2023
Keywords
Pearcey point process, generating function asymptotics, Hamiltonian, Riemann-Hilbert problems
National Category
Mathematics
Identifiers
urn:nbn:se:kth:diva-333738 (URN)10.1214/22-AAP1890 (DOI)001031710500020 ()2-s2.0-85166146889 (Scopus ID)
Note

QC 20230810

Available from: 2023-08-10 Created: 2023-08-10 Last updated: 2023-08-10Bibliographically approved
Moreillon, P.Density of the free additive convolution of multi-cut measures.
Open this publication in new window or tab >>Density of the free additive convolution of multi-cut measures
(English)Manuscript (preprint) (Other academic)
Abstract [en]

We consider the free additive convolution semigroup  and determine the local behavior of its density at the endpoints and at any singular pointof its support. We then study the free additive convolution of two multi-cut probability measures and show that its density decays either as a square root or as a cubic root at any endpoints of its support. The probability measures considered in this paper satisfy a power law behavior with exponents strictly between −1 and 1 at the endpoints of their supports.

National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:kth:diva-319638 (URN)
Note

QC 20221005

Available from: 2022-10-04 Created: 2022-10-04 Last updated: 2022-10-05Bibliographically approved
Moreillon, P. & Charlier, C.On the generating function of the Pearcey process.
Open this publication in new window or tab >>On the generating function of the Pearcey process
(English)Manuscript (preprint) (Other academic)
Abstract [en]

The Pearcey process is a universal point process in random matrix theory. In this paper, we study the generating function of the Pearcey process on any number m of intervals. We derive an integral representation for it in terms of a Hamiltonian that is related to a system of 6m + 2 coupled nonlinear equations. We also obtain asymptotics for the generating function as the size of the intervals get large, up to and including the constant term. This work generalizes some results of Dai, Xu and Zhang, which correspond to m= 1.

National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:kth:diva-319636 (URN)
Note

QC 20221005

Available from: 2022-10-04 Created: 2022-10-04 Last updated: 2022-10-05Bibliographically approved
Moreillon, P. & Schnelli, K.The support of the free additive convolution of multi-cut measures.
Open this publication in new window or tab >>The support of the free additive convolution of multi-cut measures
(English)Manuscript (preprint) (Other academic)
Abstract [en]

We consider the free additive convolution of two probability measures, supported on respectively n and m disjoint bounded intervals on the real line, and derive a lower bound and an upper bound that is strictly smaller than 2nm, on the number of connected components in its support. We also obtain the corresponding results for the free additive convolution semi-group. Throughout the paper,we consider classes of probability measures with power law behaviors at the endpoints of their supports with exponents ranging from −1 to 1. Our main theorem generalizes a result of Bao, Erdös and Schnelli to the multi-cut setup.

National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:kth:diva-319633 (URN)
Note

QC 20221005

Available from: 2022-10-04 Created: 2022-10-04 Last updated: 2022-10-05Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-8353-0733

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