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The Kuramoto model for an ensemble of coupled oscillators provides a paradigmatic example of non-equilibrium transitions between an incoherent and a synchronized state. Here we analyze populations of almost identical oscillators in…

Disordered Systems and Neural Networks · Physics 2013-05-30 Luce Prignano , Albert Diaz Guilera

In this paper the focus is on subsampling as well as reconstructing the second-order statistics of signals residing on nodes of arbitrary undirected graphs. Second-order stationary graph signals may be obtained by graph filtering zero-mean…

Information Theory · Computer Science 2018-05-08 Sundeep Prabhakar Chepuri , Geert Leus

We explore oscillatory behaviour in a family of periodically driven spin chains which are subject to a weak measurement followed by post-selection. We discover a transition to an oscillatory phase as the strength of the measurement is…

Quantum Physics · Physics 2023-06-23 Vikram Ravindranath , Xiao Chen

We investigated the locking behaviors of coupled limit-cycle oscillators with phase and amplitude dynamics. We focused on how the dynamics are affected by inhomogeneous coupling strength and by angular and radial shifts in the coupling…

Dynamical Systems · Mathematics 2021-01-19 Jae Hyung Woo , Christopher J. Honey , Joon-Young Moon

We present a framework based on spectral graph theory that captures the interplay among network topology, system inertia, and generator and load damping in determining the overall grid behavior and performance. Specifically, we show that…

Systems and Control · Computer Science 2018-08-07 Linqi Guo , Changhong Zhao , Steven H. Low

This paper investigates transient performance of inverter-based microgrids in terms of the resistive power losses incurred in regulating frequency under persistent stochastic disturbances. We model the inverters as second-order oscillators…

Optimization and Control · Mathematics 2016-03-22 Emma Tegling , Martin Andreasson , John W. Simpson-Porco , Henrik Sandberg

We investigate how correlations between the diversity of the connectivity of networks and the dynamics at their nodes affect the macroscopic behavior. In particular, we study the synchronization transition of coupled stochastic phase…

Disordered Systems and Neural Networks · Physics 2013-01-22 Bernard Sonnenschein , Francesc Sagués , Lutz Schimansky-Geier

Time-varying graph signals are alternative representation of multivariate (or multichannel) signals in which a single time-series is associated with each of the nodes or vertex of a graph. Aided by the graph-theoretic tools, time-varying…

Signal Processing · Electrical Eng. & Systems 2023-01-10 Naveed ur Rehman

For a large class of dynamical systems, the optimally time-dependent (OTD) modes, a set of deformable orthonormal tangent vectors that track directions of instabilities along any trajectory, are known to depend "pointwise" on the state of…

Computational Physics · Physics 2020-01-08 Antoine Blanchard , Themistoklis P. Sapsis

The dynamics of a non-autonomous oscillator in which the phase and frequency of the external force depend on the dynamical variable is studied. Such a control of the phase and frequency of the external force leads to the appearance of…

Chaotic Dynamics · Physics 2020-03-18 Darina Krylosova , Evgeny Seleznev , Nataliya Stankevich

In this paper, the notion of contraction is used to solve the trajectory-tracking problem for a class of mechanical systems. Additionally, we propose a dynamic extension to remove velocity measurements from the controller while rejecting…

Systems and Control · Electrical Eng. & Systems 2023-07-04 N. Javanmardi , P. Borja , M. J. Yazdanpanah , J. M. A. Scherpen

This paper provides a framework to evaluate the performance of single and double integrator networks over arbitrary directed graphs. Adopting vehicular network terminology, we consider quadratic performance metrics defined by the L2-norm of…

Systems and Control · Electrical Eng. & Systems 2019-11-05 H. Giray Oral , Enrique Mallada , Dennice F. Gayme

In this article, we investigate the implications of the unsupervised learning rule known as Input-Correlations (ICO) learning in the nonlinear dynamics of two linearly coupled PT-symmetric Li\'enard oscillators. The fixed points of the…

Adaptation and Self-Organizing Systems · Physics 2024-06-21 J. P. Deka , A. Govindarajan , A. K. Sarma

We analyze the nature and performance of clocks formed by stabilizing an oscillator to the phase difference between two paths of an atom interferometer. The phase evolution has been modeled as being driven by the proper-time difference…

Atomic Physics · Physics 2014-02-27 Steven Peil , Christopher R. Ekstrom

We investigate a generalised version of the recently proposed ordinal partition time series to network transformation algorithm. Firstly we introduce a fixed time lag for the elements of each partition that is selected using techniques from…

Chaotic Dynamics · Physics 2015-05-20 Michael McCullough , Michael Small , Thomas Stemler , Herbert Ho-Ching Iu

We construct an effective field theory (EFT) that captures the universal behavior of out-of-time-order correlators (OTOCs) at late times in generic quantum many-body systems with conservation laws. The EFT hinges on a generalization of the…

Strongly Correlated Electrons · Physics 2026-02-12 Ruchira Mishra , Jiaozi Wang , Silvia Pappalardi , Luca V. Delacrétaz

Time series and signals are attracting more attention across statistics, machine learning and pattern recognition as it appears widely in the industry especially in sensor and IoT related research and applications, but few advances has been…

Machine Learning · Computer Science 2018-08-15 Lu Liu , Zhiguang Wang

We investigate the real-time dynamics of the sub-Ohmic spin-boson model across a broad range of coupling strengths, using the numerically exact inchworm quantum Monte Carlo algorithm. From short- and intermediate-time dynamics starting from…

Strongly Correlated Electrons · Physics 2025-02-13 Olga Goulko , Hsing-Ta Chen , Moshe Goldstein , Guy Cohen

This paper studies the problem of designing networks of nonidentical coupled oscillators in order to achieve a desired level of phase cohesiveness, defined as the maximum asymptotic phase difference across the edges of the network. In…

Optimization and Control · Mathematics 2017-06-08 Mahyar Fazlyab , Florian Dörfler , Victor M. Preciado

Graph-based spatio-temporal neural networks are effective to model the spatial dependency among discrete points sampled irregularly from unstructured grids, thanks to the great expressiveness of graph neural networks. However, these models…

Machine Learning · Computer Science 2022-04-22 Haitao Lin , Guojiang Zhao , Lirong Wu , Stan Z. Li