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The Hawkes process is a versatile stochastic model for point patterns that exhibit self-excitation, that is, the property that an event occurrence increases the rate of occurrence for some period of time in the future. We present a Bayesian…

Methodology · Statistics 2025-12-01 Hyotae Kim , Athanasios Kottas

The stochastic self-propagating star-formation (SSPSF) model is an important theoretical framework for explaining how localised star-formation events trigger subsequent activity across galactic discs. While widely used to interpret spiral…

Astrophysics of Galaxies · Physics 2025-08-19 Qihan Zou

We construct a four-parameter family of Markov processes on infinite Gelfand-Tsetlin schemes that preserve the class of central (Gibbs) measures. Any process in the family induces a Feller Markov process on the infinite-dimensional boundary…

Probability · Mathematics 2013-03-04 Alexei Borodin , Grigori Olshanski

We introduce a Markovian single point process model, with random intensity regulated through a buffer mechanism and a self-exciting effect controlling the arrival stream to the buffer. The model applies the principle of the Hawkes process…

Probability · Mathematics 2017-10-12 Ingemar Kaj , Mine Caglar

In this paper, we investigate the asymptotic behavior of nearly unstable Hawkes processes whose regression kernel has $L^1$ norm strictly greater than one and close to one as time goes to infinity. We find that,the scaling size determines…

Probability · Mathematics 2026-01-14 Chenguang Liu , Liping Xu , An Zhang

We study the Wiener-Hopf factorization for L\'evy processes $X_t$ with completely monotone jumps. Extending previous results of L.C.G. Rogers, we prove that the space-time Wiener-Hopf factors are complete Bernstein functions of both the…

Probability · Mathematics 2018-11-19 Mateusz Kwaśnicki

The path-integral approach to the double well has long been limited by the dilute instanton gas approximation. We show that if the finite Euclidean-time structure is taken seriously by using exact saddles, the dilute gas can be sidestepped,…

High Energy Physics - Theory · Physics 2026-04-17 Aurélien Dersy , Matthew D. Schwartz

Asynchronous events sequences are widely distributed in the natural world and human activities, such as earthquakes records, users activities in social media and so on. How to distill the information from these seemingly disorganized data…

Machine Learning · Computer Science 2021-12-30 Lu-ning Zhang , Jian-wei Liu , Zhi-yan Song , Xin Zuo

In the L\'evy construction of Brownian motion, a Haar-derived basis of functions is used to form a finite-dimensional process $W^{N}$ and to define the Wiener process as the almost sure path-wise limit of $W^{N}$ when $N$ tends to infinity.…

Probability · Mathematics 2008-06-10 Thibaud Taillefumier

We apply the multiconfigurational time-dependent Hartree method for indistinguishable particles (MCTDH-X) to systems of bosons or fermions in lattices described by Hubbard type Hamiltonians with long-range or short-range interparticle…

Quantum Gases · Physics 2016-07-27 Axel U. J. Lode , Christoph Bruder

We consider a multivariate non-linear Hawkes process in a multi-class setup where particles are organised within two populations of possibly different sizes, such that one of the populations acts excitatory on the system while the other…

Probability · Mathematics 2020-04-07 Mads Bonde Raad , Eva Löcherbach

Several stochastic processes related to transient L\'evy processes with potential densities $u(x,y)=u(y-x)$, that need not be symmetric nor bounded on the diagonal, are defined and studied. They are real valued processes on a space of…

Probability · Mathematics 2013-11-11 Yves Le Jan , Michael B. Marcus , Jay Rosen

We propose a new Kalikow decomposition for continuous time multivariate counting processes, on potentially infinite networks. We prove the existence of such a decomposition in various cases. This decomposition allows us to derive simulation…

Probability · Mathematics 2022-05-03 Tien Cuong Phi , Eva Löcherbach , Patricia Reynaud-Bouret

The one-dimensional totally asymmetric simple exclusion process (TASEP), a Markov process describing classical hard-core particles hopping in the same direction, is considered on a periodic lattice of $L$ sites. The relaxation to the…

Statistical Mechanics · Physics 2016-03-09 Sylvain Prolhac

Genuinely critical dynamics have been proposed to organize many natural and social systems, yet exact criticality is usually thought to preclude stationarity because the mean activity diverges. I show that this conclusion is not generally…

General Physics · Physics 2026-05-26 Didier Sornette

Although nonsingular spacetimes and those containing black holes are qualitatively quite different, there are continuous families of configurations that connect the two. In this paper we use self-gravitating monopole solutions as tools for…

High Energy Physics - Theory · Physics 2009-10-31 Arthur Lue , Erick J. Weinberg

Multi-dimensional Hawkes process (MHP) is a class of self and mutually exciting point processes that find wide range of applications -- from prediction of earthquakes to modelling of order books in high frequency trading. This paper makes…

Machine Learning · Statistics 2020-06-05 Sobin Joseph , Lekhapriya Dheeraj Kashyap , Shashi Jain

In this paper, we give a topological version of Scott convergence theorem for locally hypercompact spaces. We introduce the notion of $\mathcal{S}^*_X$-convergence on a $T_0$ topological space $X$, and define the notion of finitely…

General Topology · Mathematics 2023-08-09 Yuxu Chen , Hui Kou

We construct a class of discontinuous superprocesses with dependent spatial motion and general branching mechanism. The process arises as the weak limit of critical interacting-branching particle systems where the spatial motions of the…

Probability · Mathematics 2008-07-02 Hui He

As a powerful tool of asynchronous event sequence analysis, point processes have been studied for a long time and achieved numerous successes in different fields. Among various point process models, Hawkes process and its variants attract…

Machine Learning · Statistics 2017-08-31 Hongteng Xu , Hongyuan Zha