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Ensuring robust and real-time obstacle avoidance is critical for the safe operation of autonomous robots in dynamic, real-world environments. This paper proposes a neural network framework for predicting the time and collision position of…

We calculate the maximal Lyapunov exponent in constant-energy molecular dynamics simulations at the melting transition for finite clusters of 6 to 13 particles (model rare-gas and metallic systems) as well as for bulk rare-gas solid. For…

chao-dyn · Physics 2009-10-30 Vishal Mehra , Ramakrishna Ramaswamy

Recent work has highlighted the potentially detectable gravitational-lensing effect of neutrino halos on cosmic-microwave-background (CMB) fluctuations with upcoming instruments like SO, CMB-S4, and CMB-HD. Accurate modeling of…

Cosmology and Nongalactic Astrophysics · Physics 2024-10-14 Keduse Worku , Nashwan Sabti , Marc Kamionkowski

We develop a workflow to use current quantum computing hardware for solving quantum many-body problems, using the example of the fermionic Hubbard model. Concretely, we study a four-site Hubbard ring that exhibits a transition from a…

Chaotic systems, such as turbulent flows, are ubiquitous in science and engineering. However, their study remains a challenge due to the large range scales, and the strong interaction with other, often not fully understood, physics. As a…

Critical heat flux is a key quantity in boiling system modeling due to its impact on heat transfer and component temperature and performance. This study investigates the development and validation of an uncertainty-aware hybrid modeling…

Machine Learning · Computer Science 2025-07-17 Aidan Furlong , Xingang Zhao , Robert Salko , Xu Wu

In the next decade, cosmological surveys will have the statistical power to detect the absolute neutrino mass scale. N-body simulations of large-scale structure formation play a central role in interpreting data from such surveys. Yet these…

Cosmology and Nongalactic Astrophysics · Physics 2021-08-31 Caio Bastos de Senna Nascimento , Marilena Loverde

Physics-based and data-driven models for remaining useful lifetime (RUL) prediction typically suffer from two major challenges that limit their applicability to complex real-world domains: (1) incompleteness of physics-based models and (2)…

Systems and Control · Electrical Eng. & Systems 2020-10-28 Manuel Arias Chao , Chetan Kulkarni , Kai Goebel , Olga Fink

In a calculation of rotated matrix elements with angular momentum projection, the generalized Wick's theorem may encounter a practical problem of combinatorial complexity when the configurations have more than four quasi-particles (qps).…

Nuclear Theory · Physics 2015-06-22 Long-Jun Wang , Fang-Qi Chen , Takahiro Mizusaki , Makito Oi , Yang Sun

It is well known that chaotic dynamic systems (such as three-body system, turbulent flow and so on) have the sensitive dependence on initial conditions (SDIC). Unfortunately, numerical noises (such as truncation error and round-off error)…

Chaotic Dynamics · Physics 2018-05-22 Xiaoming Li , Shijun Liao

In recent years many-body perturbation theory encountered a renaissance in the field of ab initio nuclear structure theory. In various applications it was shown that perturbation theory, including novel flavors of it, constitutes a useful…

Nuclear Theory · Physics 2020-01-29 Alexander Tichai , Robert Roth , Thomas Duguet

Chaotic systems, that have a small Lyapunov exponent, do not obey the common random matrix theory predictions within a wide "weak quantum chaos" regime. This leads to a novel prediction for the rate of heating for cold atoms in optical…

Quantum Physics · Physics 2010-11-26 Alexander Stotland , Louis M. Pecora , Doron Cohen

A major goal of developing high-precision control of many-body quantum systems is to realise their potential as quantum computers. Probably the most significant obstacle in this direction is the problem of "decoherence": the extreme…

In this paper, we use support vector machines (SVM) to develop a machine learning framework to discover phase space structures that distinguish between distinct reaction pathways. The SVM model is trained using data from trajectories of…

Chemical Physics · Physics 2022-01-06 Vladimír Krajňák , Shibabrat Naik , Stephen Wiggins

In this paper, a new polynomial chaos based framework for analyzing linear systems with probabilistic parameters is presented. Stability analysis and synthesis of optimal quadratically stabilizing controllers for such systems are presented…

Systems and Control · Computer Science 2015-03-30 Raktim Bhattacharya

We propose a variational scheme to represent composite quantum systems using multiple parameterized functions of varying accuracies on both classical and quantum hardware. The approach follows the variational principle over the entire…

Quantum Physics · Physics 2024-06-21 Stefano Barison , Filippo Vicentini , Giuseppe Carleo

Using direct $N$-body simulations of self-gravitating systems we study the dependence of dynamical chaos on the system size $N$. We find that the $N$-body chaos quantified in terms of the largest Lyapunov exponent $\Lambda_{\rm max}$…

Astrophysics of Galaxies · Physics 2020-03-18 Pierfrancesco Di Cintio , Lapo Casetti

A chaotic system is a highly volatile system characterized by its sensitive dependence on initial conditions and outside factors. Chaotic systems are prevalent throughout the world today: in weather patterns, disease outbreaks, and even…

Predicting chaotic dynamical systems is critical in many scientific fields, such as weather forecasting, but challenging due to the characteristic sensitive dependence on initial conditions. Traditional modeling approaches require extensive…

Machine Learning · Computer Science 2025-03-12 Christof Schötz , Alistair White , Maximilian Gelbrecht , Niklas Boers

The study of information scrambling has profoundly deepened our understanding of many-body quantum systems. Much recent research has been devote to understanding the interplay between scrambling and decoherence in open systems. Continuing…

Quantum Physics · Physics 2025-11-04 Emanuel Dallas , Faidon Andreadakis , Paolo Zanardi