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We describe an improved version of the quantum simulation method based on the implementation of a truncated Taylor series of the evolution operator. The idea is to add an extra step to the previously known algorithm which implements an…

Quantum Physics · Physics 2017-06-05 Leonardo Novo , Dominic W. Berry

In this paper we consider point processes specified on directed linear networks, i.e. linear networks with associated directions. We adapt the so-called conditional intensity function used for specifying point processes on the time line to…

Statistics Theory · Mathematics 2019-01-03 Jakob G. Rasmussen , Heidi S. Christensen

The rapid growth of social media has been witnessed during recent years as a result of the prevalence of the internet. This trend brings an increasing interest in simulating social media which can provide valuable insights to both academic…

Social and Information Networks · Computer Science 2021-08-11 Ao Qu , Ismael Lemhadri

We propose a method for efficient simulations in extended ensembles, useful, e.g., for the study of problems with complex energy landscapes and for free energy calculations. The main difficulty in such simulations is the estimation of the a…

Statistical Mechanics · Physics 2012-05-29 Jack Lidmar

We propose an extension to Hawkes processes by treating the levels of self-excitation as a stochastic differential equation. Our new point process allows better approximation in application domains where events and intensities accelerate…

Machine Learning · Computer Science 2016-09-23 Young Lee , Kar Wai Lim , Cheng Soon Ong

A point process for event arrivals in high frequency trading is presented. The intensity is the product of a Hawkes process and high dimensional functions of covariates derived from the order book. Conditions for stationarity of the process…

Trading and Market Microstructure · Quantitative Finance 2026-05-12 Luca Mucciante , Alessio Sancetta

This study examines the use of a recurrent neural network for estimating the parameters of a Hawkes model based on high-frequency financial data, and subsequently, for computing volatility. Neural networks have shown promising results in…

Statistical Finance · Quantitative Finance 2023-04-25 Kyungsub Lee

The phase estimation algorithm is a powerful quantum algorithm with applications in cryptography, number theory, and simulation of quantum systems. We use this algorithm to simulate the time evolution of a system of two spin-1/2 particles…

Quantum Physics · Physics 2021-05-12 Scott Johnstun , Jean-François Van Huele

This paper investigates the asymptotic behavior of suitably time-modulated Hawkes processes with heavy-tailed kernels in a nearly unstable regime. We show that, under appropriate scaling, both the intensity processes and the rescaled Hawkes…

Probability · Mathematics 2026-02-12 Emmanuel Gnabeyeu , Gilles Pagès , Mathieu Rosenbaum

We introduce a method that ensures efficient computation of one-dimensional quantum systems with long-range interactions across all temperatures. Our algorithm operates within a quasi-polynomial runtime for inverse temperatures up to…

Quantum Physics · Physics 2025-05-19 Rakesh Achutha , Donghoon Kim , Yusuke Kimura , Tomotaka Kuwahara

A computer simulation has to be fast to be helpful, if it is employed to study the behavior of a multicomponent dynamic system. This paper discusses modeling concepts and algorithmic techniques useful for creating such fast simulations.…

Data Structures and Algorithms · Computer Science 2007-05-23 Boris D. Lubachevsky

The purpose of this paper is to present a recursive algorithm and its implementation in Maple and Mathematica for the computation of joint moments and cumulants of Hawkes processes with exponential kernels. Numerical results and computation…

Machine Learning · Computer Science 2021-10-27 Nicolas Privault

When the sample path of a Hawkes process is observed discretely, such that only the total event counts in disjoint time intervals are known, the likelihood function becomes intractable. To overcome the challenge of likelihood-based…

Methodology · Statistics 2025-06-24 Jason J. Lambe , Feng Chen , Tom Stindl , Tsz-Kit Jeffrey Kwan

Multivariate Hawkes Processes (MHPs) are a class of point processes that can account for complex temporal dynamics among event sequences. In this work, we study the accuracy and computational efficiency of three classes of algorithms which,…

Computation · Statistics 2025-02-24 Alex Ziyu Jiang , Abel Rodríguez

Trawl processes are continuous-time, stationary and infinitely divisible processes which can describe a wide range of possible serial correlation patterns in data. In this paper, we introduce new simulation algorithms for trawl processes…

Methodology · Statistics 2022-08-19 Dan Leonte , Almut E. D. Veraart

We describe an efficient numerical method for simulating the dynamics of interacting spin ensembles in the presence of dephasing and decay. The method builds on the discrete truncated Wigner approximation for isolated systems, which…

Quantum Physics · Physics 2022-02-01 Julian Huber , Ana Maria Rey , Peter Rabl

Particle dynamics and multi-agent systems provide accurate dynamical models for studying and forecasting the behavior of complex interacting systems. They often take the form of a high-dimensional system of differential equations…

Machine Learning · Computer Science 2023-08-09 Yuxuan Liu , Scott G. McCalla , Hayden Schaeffer

The Hawkes process is a popular point process model for event sequences that exhibit temporal clustering. The intensity process of a Hawkes process consists of two components, the baseline intensity and the accumulated excitation effect due…

Statistics Theory · Mathematics 2024-08-20 Tsz-Kit Jeffrey Kwan , Feng Chen , William Dunsmuir

In this paper, we establish a large deviations principle for a multivariate compound process induced by a multivariate Hawkes process with random marks. Our proof hinges on showing essential smoothness of the limiting cumulant of the…

Probability · Mathematics 2023-06-29 Raviar S. Karim , Roger J. A. Laeven , Michel R. H. Mandjes

We introduce the Hyperedge-triggered Hawkes (HTH) process for inferring higher-order interaction structure in multi-cellular systems from asynchronous event-time data. Beyond standard pairwise excitation, the HTH intensity includes a term…

Methodology · Statistics 2026-05-27 Zihan Xu