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TASEP and generalizations: method for exact solution
Indexado
WoS WOS:000788953200001
Scopus SCOPUS_ID:85129204271
DOI 10.1007/S00440-022-01129-W
Año 2023
Tipo artículo de investigación

Citas Totales

Autores Afiliación Chile

Instituciones Chile

% Participación
Internacional

Autores
Afiliación Extranjera

Instituciones
Extranjeras


Abstract



The explicit biorthogonalization method, developed in [24] for continuous time TASEP, is generalized to a broad class of determinantal measures which describe the evolution of several interacting particle systems in the KPZ universality class. The method is applied to sequential and parallel update versions of each of the four variants of discrete time TASEP (with Bernoulli and geometric jumps, and with block and push dynamics) which have determinantal transition probabilities; to continuous time PushASEP; and to a version of TASEP with generalized update. In all cases, multipoint distribution functions are expressed in terms of a Fredholm determinant with an explicit kernel involving hitting times of certain random walks to a curve defined by the initial data of the system. The method is further applied to systems of interacting caterpillars, an extension of the discrete time TASEP models which generalizes sequential and parallel updates.

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Disciplinas de Investigación



WOS
Statistics & Probability
Scopus
Sin Disciplinas
SciELO
Sin Disciplinas

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Publicaciones WoS (Ediciones: ISSHP, ISTP, AHCI, SSCI, SCI), Scopus, SciELO Chile.

Colaboración Institucional



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Autores - Afiliación



Ord. Autor Género Institución - País
1 Matetski, Konstantin Hombre Columbia Univ - Estados Unidos
Columbia University - Estados Unidos
2 Remenik, Daniel Hombre Universidad de Chile - Chile

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Financiamiento



Fuente
National Science Foundation
Fondo Nacional de Desarrollo Científico y Tecnológico
NSF
FONDECYT grant
Programa Iniciativa Cientifica Milenio
Programa Iniciativa Cientifica Milenio through Nucleus Millennium Stochastic Models of Complex and Disordered Systems
Centro de Modelamiento Matematico
ANID-Chile
Centro de Modelamiento Matematico (CMM) Basal Funds from ANID-Chile

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Agradecimientos



Agradecimiento
The authors would like to thank Alexei Borodin for discussions several years ago which motivated some of the results of this paper; Patrik Ferrari for pointing out to us the connection between sequential and parallel updates at the level of Markov chains on Gelfand-Tsetlin patterns [5]; and Jeremy Quastel for many valuable discussions related to this work. KM was partially supported by NSF grant DMS-1953859. The also thank an anonymous referee for a very detailed and helpful report. DR was supported by Centro de Modelamiento Matematico (CMM) Basal Funds FB210005 from ANID-Chile, by Fondecyt Grant 1201914, and by Programa Iniciativa Cientifica Milenio grant number NC120062 through Nucleus Millennium Stochastic Models of Complex and Disordered Systems.
The authors would like to thank Alexei Borodin for discussions several years ago which motivated some of the results of this paper; Patrik Ferrari for pointing out to us the connection between sequential and parallel updates at the level of Markov chains on Gelfand-Tsetlin patterns []; and Jeremy Quastel for many valuable discussions related to this work. KM was partially supported by NSF grant DMS-1953859. The also thank an anonymous referee for a very detailed and helpful report. DR was supported by Centro de Modelamiento Matemático (CMM) Basal Funds FB210005 from ANID-Chile, by Fondecyt Grant 1201914, and by Programa Iniciativa Científica Milenio grant number NC120062 through Nucleus Millennium Stochastic Models of Complex and Disordered Systems.

Muestra la fuente de financiamiento declarada en la publicación.