English
Related papers

Related papers: Global minimization via classical tunneling assist…

200 papers

Particles in pressure-driven channel flow are often inhomogeneously distributed. Two modes of low-Reynolds number instability, absent in Poiseuille flow of clean fluid, are created by inhomogeneous particle loading, and their mechanism is…

Fluid Dynamics · Physics 2024-11-27 Anup Kumar , Rama Govindarajan

Using a non-perturbative classical approach, we study the dynamics of a mobile particle interacting with an infinite one-dimensional (1D) chain of harmonic oscillators. This minimal system is an effective model for many 1D transport…

Mesoscale and Nanoscale Physics · Physics 2023-02-02 Harshitra Mahalingam , Zhun Wai Yap , Ben A. Olsen , Aleksandr Rodin

We consider the tunneling of a wave packet through a potential barrier which is coupled to a nonintegrable classical system and study the interplay of classical chaos and dissipation in the tunneling dynamics. We show that chaos-assisted…

chao-dyn · Physics 2009-10-31 Bidhan Chandra Bag , Bikash Chandra Gupta , Debshankar Ray

Biological and social networks have recently attracted enormous attention between physicists. Among several, two main aspects may be stressed: A non trivial topology of the graph describing the mutual interactions between agents exists…

Statistical Mechanics · Physics 2015-05-19 Adriano Barra , Elena Agliari

Many networks in nature and applications have an approximate low-rank structure in the sense that their connectivity structure is dominated by a few dimensions. It is natural to expect that dynamics on such networks would also be…

Dynamical Systems · Mathematics 2026-05-29 Yue Wan , Robert Rosenbaum

The network paradigm is used to gain insight into the structural root causes of the resilience of consensus in dynamic collective behaviors, and to analyze the controllability of the swarm dynamics. Here we devise the dynamic signaling…

Physics and Society · Physics 2014-01-14 Mohammad Komareji , Roland Bouffanais

Elucidating emergent regularities in intriguing crowd dynamics is a fundamental scientific problem arising in multiple fields. In this work, based on the social force model, we simulate the typical scenario of collective escape towards a…

Soft Condensed Matter · Physics 2021-05-11 Chen Cheng , Jinglai Li , Zhenwei Yao

Clustering is one of the mayor collective phenomena observed in active matter. We study the overdamped motion of interacting active Brownian particles in two dimensions. An instability in the pair correlation function causes the onset of…

Soft Condensed Matter · Physics 2024-03-18 Rüdiger Kürsten

Slow dynamics in glassy systems is often interpreted as due to thermally activated events between "metastable" states. This emphasizes the role of nonperturbative fluctuations, which is especially dramatic when these fluctuations destroy a…

Statistical Mechanics · Physics 2015-07-10 Charlotte Rulquin , Pierfrancesco Urbani , Giulio Biroli , Gilles Tarjus , Marco Tarzia

Most real-world networks are endowed with the small-world property, by means of which the maximal distance between any two of their nodes scales logarithmically rather than linearly with their size. The evidence sparkled a wealth of studies…

Physics and Society · Physics 2023-04-21 Tanu Raghav , Stefano Boccaletti , Sarika Jalan

In most fluid models the generation mechanism and the magnetide of anomalous transport are usually treated as auxiliary terms external to the model description and are free to manipulate, the anomalous transport is indeed a noticeably…

Plasma Physics · Physics 2009-10-14 Kuang Wu Lee , Joerg Buechner

We study a minimal model of traffic flows in complex networks, simple enough to get analytical results, but with a very rich phenomenology, presenting continuous, discontinuous as well as hybrid phase transitions between a free-flow phase…

Statistical Mechanics · Physics 2015-05-13 Daniele De Martino , Luca Dall'Asta , Ginestra Bianconi , Matteo Marsili

Recurrent neural networks have been extensively studied in the context of neuroscience and machine learning due to their ability to implement complex computations. While substantial progress in designing effective learning algorithms has…

Neurons and Cognition · Quantitative Biology 2019-01-21 Francesca Mastrogiuseppe , Srdjan Ostojic

When particles move at a constant speed and have the tendency to align their directions of motion, ordered large scale movement can emerge despite significant levels of noise. Many variants of this model of self-propelled particles have…

Biological Physics · Physics 2012-12-11 Matthias Meschede , Oskar Hallatschek

The ability to achieve coordinated behavior --engineered or emergent-- on networked systems has attracted widespread interest over several fields. This has led to remarkable advances on the development of a theoretical understanding of the…

Systems and Control · Computer Science 2019-09-16 Hancheng Min , Enrique Mallada

We use path-integrals to derive a general expression for the semiclassical approximation to the partition function of a one-dimensional quantum-mechanical system. Our expression depends solely on ordinary integrals which involve the…

Quantum Physics · Physics 2007-05-23 C. A. A. de Carvalho , R. M. Cavalcanti

The existence of quantum tunneling opens the possibility of a sudden spatial relocalization of a system after a minor modification of its parameters. Such a quantum analogue of the Thom's classical catastrophe would manifest itself,…

Quantum Physics · Physics 2021-05-12 Miloslav Znojil

In recent works, we proposed a hypothesis that the turbulence in gases could be produced by particles interacting via a potential, and examined the proposed mechanics of turbulence formation in a simple model of two particles for a variety…

Fluid Dynamics · Physics 2024-06-12 Rafail V. Abramov

In recent works, we proposed a hypothesis, according to which turbulence in gases is created by the mean field effect of an intermolecular potential. We discovered that, in a numerically simulated inertial flow, turbulent solutions indeed…

Fluid Dynamics · Physics 2023-10-18 Rafail V. Abramov

We report on collective excitable events in a highly-diluted random network of non-excitable nodes. Excitability arises thanks to a self-sustained local adaptation mechanism that drives the system on a slow time-scale across a hysteretic…

Disordered Systems and Neural Networks · Physics 2025-05-29 Gabriele Paolini , Marzena Ciszak , Francesco Marino , Simona Olmi , Alessandro Torcini