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The Liouville equation differs from the von Neumann equation 'only' by a characteristic superoperator. We demonstrate this for Hamiltonian dynamics, in general, and for the Jaynes-Cummings model, in particular. -- Employing superspace…

Quantum Physics · Physics 2011-04-11 Hans-Thomas Elze , Giovanni Gambarotta , Fabio Vallone

This paper introduces a space-continuous force-based model for simulating pedestrian dynamics. The main interest of this work is the quantitative description of pedestrian movement through a bottleneck. Measurements of flow and density will…

Physics and Society · Physics 2016-11-15 Mohcine Chraibi , Armin Seyfried , Andreas Schadschneider , Wolfgang Mackens

The core of this thesis is the path-integral formulation of quantum field theory and its ability to describe strongly-coupled quantum many-body systems of finite size. Collective behaviors can be efficiently described in such systems…

Strongly Correlated Electrons · Physics 2025-03-17 Kilian Fraboulet

Predicting pedestrian motion trajectories is critical for the path planning and motion control of autonomous vehicles. Recent diffusion-based models have shown promising results in capturing the inherent stochasticity of pedestrian behavior…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Yu Liu , Zhijie Liu , Xiao Ren , You-Fu Li , He Kong

Stochastic mechanics---the study of classical stochastic systems governed by things like master equations and Fokker-Planck equations---exhibits striking mathematical parallels to quantum mechanics. In this article, we make those parallels…

Statistical Mechanics · Physics 2019-10-01 John J. Vastola , William R. Holmes

Quantum mechanics in conical space is studied by the path integral method. It is shown that the curvature effect gives rise to an effective potential in the radial path integral. It is further shown that the radial path integral in conical…

Mathematical Physics · Physics 2011-11-28 Akira Inomata , Georg Junker

Representations based on random walks can exploit discrete data distributions for clustering and classification. We extend such representations from discrete to continuous distributions. Transition probabilities are now calculated using a…

Machine Learning · Computer Science 2012-12-12 Chen-Hsiang Yeang , Martin Szummer

We consider particle transport under the influence of time-varying driving forces, where fluctuation relations connect the statistics of pairs of time reversed evolutions of physical observables. In many "mesoscopic" transport processes,…

Statistical Mechanics · Physics 2010-09-29 A. Altland , A. De Martino , R. Egger , B. Narozhny

Surprisingly the looking natural random walk leading to Brownian motion occurs to be often biased in a very subtle way: usually refers to only approximate fulfillment of thermodynamical principles like maximizing uncertainty. Recently, a…

Quantum Physics · Physics 2015-06-03 Jarek Duda

The path integral formalism gives a very illustrative and intuitive understanding of quantum mechanics but due to its difficult sum over phases one usually prefers Schr\"odinger's approach. We will show that it is possible to calculate…

Quantum Physics · Physics 2007-05-23 A. Dullweber , E. R. Hilf , E. Mendel

Accurate pedestrian trajectory prediction is crucial for various applications, and it requires a deep understanding of pedestrian motion patterns in dynamic environments. However, existing pedestrian trajectory prediction methods still need…

Computer Vision and Pattern Recognition · Computer Science 2024-03-14 Pranav Singh Chib , Pravendra Singh

We calculate the propagator of a particle caught in a Paul trap and subject to the continuous quantum measurement of its position. The probabilities of the measurement outputs, the possible trajectories of the particle, are also found. This…

Quantum Physics · Physics 2009-10-31 A. Camacho , A. Camacho-Galvan

A path integral method, combined with atomistic spin dynamics simulations, has been developed to calculate thermal quantum expectation values using a classical approach. In this study, we show how to treat Hamiltonians with non-linear…

Quantum Physics · Physics 2024-08-12 Thomas Nussle , Pascal Thibaudeau , Stam Nicolis

We describe how to construct and compute unambiguously path integrals for particles moving in a curved space, and how these path integrals can be used to calculate Feynman graphs and effective actions for various quantum field theories with…

High Energy Physics - Theory · Physics 2007-05-23 Fiorenzo Bastianelli

For simulation models of pedestrian dynamics there are always the issues of calibration and validation. These are usually done by comparing measured properties of the dynamics found in observation, experiments and simulation in certain…

Physics and Society · Physics 2014-02-10 Tobias Kretz

This contribution investigates situations in pedestrian dynamics, where trying to walk the shortest path leads to largely different results than trying to walk the quickest path. A heuristic one-shot method to model the influence of the…

Multiagent Systems · Computer Science 2010-01-20 Tobias Kretz

Random walk is a fundamental concept with applications ranging from quantum physics to econometrics. Remarkably, one specific model of random walks appears to be ubiquitous across many fields as a tool to analyze transport phenomena in…

Statistical Mechanics · Physics 2015-06-12 V. Zaburdaev , S. Denisov , J. Klafter

We introduce a path sampling method for obtaining statistical properties of an arbitrary stochastic dynamics. The method works by decomposing a trajectory in time, estimating the probability of satisfying a progress constraint, modifying…

Statistical Mechanics · Physics 2015-06-04 Nicholas Guttenberg , Aaron R. Dinner , Jonathan Weare

We have developed a proper path integral formalism consistent with the deformed version of the quantum mechanics which contains a maximum observable length scale at the order of the Cosmological particle horizon, existing in cosmology.…

High Energy Physics - Theory · Physics 2022-09-28 Souvik Pramanik

In crowd scenarios, predicting trajectories of pedestrians is a complex and challenging task depending on many external factors. The topology of the scene and the interactions between the pedestrians are just some of them. Due to…

Machine Learning · Computer Science 2022-09-12 Raphael Korbmacher , Antoine Tordeux