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Following the recent development of a stable event-detection algorithm for hard-sphere systems, the implications of more complex interaction models are examined. The relative location of particles leads to ambiguity when it is used to…

Computational Physics · Physics 2016-03-22 Severin Strobl , Marcus N. Bannerman , Thorsten Poeschel

Event-driven molecular dynamics is a valuable tool in condensed and soft matter physics when particles can be modeled as hard objects or more generally if their interaction potential can be modeled in a stepwise fashion. Hard spheres model…

Computational Physics · Physics 2015-05-19 Cristiano De Michele

Although event-driven algorithms have been shown to be far more efficient than time-driven methods such as conventional molecular dynamics, they have not become as popular. The main obstacle seems to be the difficulty of parallelizing…

Computational Physics · Physics 2015-06-26 S. Miller , S. Luding

Hard spheres are arguably one of the most fundamental model systems in soft matter physics, and hence a common topic of simulation studies. Event-driven simulation methods provide an efficient method for studying the phase behavior and…

Soft Condensed Matter · Physics 2022-01-05 Frank Smallenburg

The problem of quickest detection of dynamic events in networks is studied. At some unknown time, an event occurs, and a number of nodes in the network are affected by the event, in that they undergo a change in the statistics of their…

Signal Processing · Electrical Eng. & Systems 2018-07-18 Shaofeng Zou , Venugopal V. Veeravalli , Jian Li , Don Towsley

We present, in a unifying way, the main components of three asynchronous event-driven algorithms for simulating physical systems of interacting particles. The first example, hard-particle molecular dynamics, is well-known. We also present a…

Other Computer Science · Computer Science 2008-09-09 Aleksandar Donev

A simple and efficient algorithm of the molecular-dynamics simulation of the hard disk system based on the Event-Driven method is developed. From the analysis of algorithm, the complexity is O(log N) per 1 event, and the constant…

Computational Physics · Physics 2009-10-31 Masaharu Isobe

Detectability has been introduced as a generalization of state-estimation properties of discrete event systems studied in the literature. It asks whether the current and subsequent states of a system can be determined based on observations.…

Formal Languages and Automata Theory · Computer Science 2020-05-19 Jiří Balun , Tomáš Masopust

We introduce an event-driven simulation scheme for overdamped dynamics of frictionless hard spheres subjected to external forces, neglecting hydrodynamic interactions. Our event-driven approach is based on an exact equation of motion which…

Soft Condensed Matter · Physics 2015-06-03 Edan Lerner , Gustavo Düring , Matthieu Wyart

Several physical systems in condensed matter have been modeled approximating their constituent particles as hard objects. The hard spheres model has been indeed one of the cornerstones of the computational and theoretical description in…

Computational Physics · Physics 2015-05-13 Cristiano De Michele

An important task in the simulation of hard spheres and other hard particles is structure prediction via equilibration. Event-driven molecular dynamics is efficient because its Newtonian dynamics equilibrates fluctuations with the speed of…

Soft Condensed Matter · Physics 2019-05-07 Marco Klement , Michael Engel

We present an algorithm for finding the probabilities of rare events in nonequilibrium processes. The algorithm consists of evolving the system with a modified dynamics for which the required event occurs more frequently. By keeping track…

Statistical Mechanics · Physics 2011-04-07 Anupam Kundu , Sanjib Sabhapandit , Abhishek Dhar

Automated event detection has emerged as one of the fundamental practices to monitor the behavior of technical systems by means of sensor data. In the automotive industry, these methods are in high demand for tracing events in time series…

Machine Learning · Computer Science 2023-10-18 Bahareh Medghalchi , Andreas Vogel

Model-based algorithms are deeply rooted in modern control and systems theory. However, they usually come with a critical assumption - access to an accurate model of the system. In practice, models are far from perfect. Even precisely tuned…

Systems and Control · Electrical Eng. & Systems 2022-04-06 Sebastian Schlor , Friedrich Solowjow , Sebastian Trimpe

In complex plasmas, the behavior of freely floating micrometer sized particles is studied. The particles can be directly visualized and recorded by digital video cameras. To analyze the dynamics of single particles, reliable algorithms are…

Plasma Physics · Physics 2018-02-14 Daniel P. Mohr , Christina A. Knapek , Peter Huber , Erich Zaehringer

We consider the problem of estimating a vector of unknown constant parameters for a class of hybrid dynamical systems -- that is, systems whose state variables exhibit both continuous (flow) and discrete (jump) evolution. Using a hybrid…

Optimization and Control · Mathematics 2023-08-16 Ryan S. Johnson , Stefano Di Cairano , Ricardo G. Sanfelice

Molecular-dynamics algorithms for systems of particles interacting through discrete or "hard" potentials are fundamentally different to the methods for continuous or "soft" potential systems. Although many software packages have been…

Computational Physics · Physics 2013-09-30 M. N. Bannerman , R. Sargant , L. Lue

Event-driven programming is widely used for implementing user interfaces, web applications, and non-blocking I/O. An event-driven program is organized as a collection of event handlers whose execution is triggered by events. Traditional…

Programming Languages · Computer Science 2019-10-30 Ming-Ho Yee , Ayaz Badouraly , Ondřej Lhoták , Frank Tip , Jan Vitek

Detectability of discrete event systems (DESs) is a question whether the current and subsequent states can be determined based on observations. Shu and Lin designed a polynomial-time algorithm to check strong (periodic) detectability and an…

Systems and Control · Computer Science 2017-10-09 Tomáš Masopust

The abundance of data affords researchers to pursue more powerful computational tools to learn the dynamics of complex system, such as neural networks, engineered systems and social networks. Traditional machine learning approaches capture…

Machine Learning · Computer Science 2024-05-16 Yan Shen , Fan Yang , Mingchen Gao , Wen Dong
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