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Related papers: Information Flow in Finite Flocks

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We study flocking in one dimension, introducing a lattice model in which particles can move either left or right. We find that the model exhibits a continuous nonequilibrium phase transition from a condensed phase, in which a single `flock'…

Statistical Mechanics · Physics 2009-10-31 O. J. O'Loan , M. R. Evans

The transient behavior of an ecosystem with N random interacting species in the presence of a multiplicative noise is analyzed. The multiplicative noise mimics the interaction with the environment. We investigate different asymptotic…

Statistical Mechanics · Physics 2009-11-10 B. Spagnolo , D. Valenti , A. Fiasconaro

A wide variety of complex systems exhibit large fluctuations both in space and time that often can be attributed to the presence of some kind of critical phenomena. Under such critical scenario it is well known that the properties of the…

Disordered Systems and Neural Networks · Physics 2019-05-29 Dante R. Chialvo , Sergio A. Cannas , Dietmar Plenz , Tomas S. Grigera

We propose a comprehensive dynamical model for cooperative motion of self-propelled particles, e.g., flocking, by combining well-known elements such as velocity-alignment interactions, spatial interactions, and angular noise into a unified…

Statistical Mechanics · Physics 2009-05-20 V. Dossetti , F. J. Sevilla , V. M. Kenkre

Inspired by current research on measurement-induced quantum phase transitions, we analyze the nonunitary Floquet transverse-field Ising model with complex nearest-neighbor couplings and complex transverse fields. Unlike its unitary…

Quantum Physics · Physics 2024-02-02 Lei Su , Aashish Clerk , Ivar Martin

We study the dynamics of dephasing in a quantum two-level system by modeling both 1/f and high-frequency noise by random telegraph processes. Our approach is based on a so-called spin-fluctuator model in which a noisy environment is modeled…

Quantum Physics · Physics 2014-12-01 Alexander I. Nesterov , Gennady P. Berman

Attribution methods provide insights into the decision-making of machine learning models like artificial neural networks. For a given input sample, they assign a relevance score to each individual input variable, such as the pixels of an…

Machine Learning · Statistics 2020-05-26 Karl Schulz , Leon Sixt , Federico Tombari , Tim Landgraf

We concentrate on kinetic models for swarming with individuals interacting through self-propelling and friction forces, alignment and noise. We assume that the velocity of each individual relaxes to the mean velocity. In our present case,…

Analysis of PDEs · Mathematics 2019-12-03 Mihaï Bostan , José Antonio Carrillo

Fish, birds, insects and robots frequently swim or fly in groups. During their 3 dimensional collective motion, these agents do not stop, they avoid collisions by strong short-range repulsion, and achieve group cohesion by weak long-range…

Soft Condensed Matter · Physics 2018-07-04 Illes J. Farkas , Shuo-Hong Wang

Robots that work close to humans need to understand and use social cues to act in a socially acceptable manner. Social cues are a form of communication (i.e., information flow) between people. In this paper, a framework is introduced to…

Robotics · Computer Science 2023-12-15 Haoyang Jiang , Elizabeth A. Croft , Michael G. Burke

We theoretically investigate the flow of information in an interacting two-skyrmion system confined in a box at finite temperature. By numerical simulations based on the Thiele-Langevin equation, we demonstrate that the skyrmion motion…

Mesoscale and Nanoscale Physics · Physics 2026-03-10 Tenta Tani , Soma Miki , Hiroki Mori , Minori Goto , Yoshishige Suzuki , Eiiti Tamura

Transfer entropy measures the strength and direction of information flow between different time series. We study the information flow networks of the Chinese stock market and identify important sectors and information flow paths. This paper…

Statistical Finance · Quantitative Finance 2020-04-21 Peng Yue , Qing Cai , Wanfeng Yan , Wei-Xing Zhou

In this article, we review a general theoretical framework of thermodynamics of information on the basis of Bayesian networks. This framework can describe a broad class of nonequilibrium dynamics of multiple interacting systems with complex…

Statistical Mechanics · Physics 2018-07-23 Sosuke Ito , Takahiro Sagawa

Information flow between components of a system takes many forms and is key to understanding the organization and functioning of large-scale, complex systems. We demonstrate three modalities of information flow from time series X to time…

Statistical Mechanics · Physics 2018-08-22 Ryan G. James , Blanca Daniella Mansante Ayala , Bahti Zakirov , James P. Crutchfield

Transferring knowledge from one neural network to another has been shown to be helpful for learning tasks with few training examples. Prevailing fine-tuning methods could potentially contaminate pre-trained features by comparably high…

Machine Learning · Computer Science 2019-07-15 Farshid Varno , Behrouz Haji Soleimani , Marzie Saghayi , Lisa Di Jorio , Stan Matwin

The entropic sampling dynamics based on the reversible information transfer to and from the environment is applied to the globally coupled Ising model in the presence of an oscillating magnetic field. When the driving frequency is low…

Statistical Mechanics · Physics 2007-05-23 Beom Jun Kim , M. Y. Choi

Noise, through its interaction with the nonlinearity of the living systems, can give rise to counter-intuitive phenomena such as stochastic resonance, noise-delayed extinction, temporal oscillations, and spatial patterns. In this paper we…

Populations and Evolution · Quantitative Biology 2007-05-23 B. Spagnolo , D. Valenti , A. Fiasconaro

Non-parallel voice conversion (VC) is typically achieved using lossy representations of the source speech. However, ensuring only speaker identity information is dropped whilst all other information from the source speech is retained is a…

Audio and Speech Processing · Electrical Eng. & Systems 2022-03-16 Thomas Merritt , Abdelhamid Ezzerg , Piotr Biliński , Magdalena Proszewska , Kamil Pokora , Roberto Barra-Chicote , Daniel Korzekwa

Noise-induced phase transitions are common in various complex systems, from physics to biology. In this article, we investigate the emergence of crucial events in noise-induced phase transition processes and their potential significance for…

Data Analysis, Statistics and Probability · Physics 2023-06-28 Jacob D. Baxley , David R. Lambert , Mauro Bologna , Bruce J. West , Paolo Grigolini

When monitoring the dynamics of stochastic systems, such as interacting particles agitated by thermal noise, disentangling deterministic forces from Brownian motion is challenging. Indeed, we show that there is an information-theoretic…

Soft Condensed Matter · Physics 2020-04-16 Anna Frishman , Pierre Ronceray