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| 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
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.
| 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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| 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 |
| 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. |