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Exotic Synchronization in Continuous Time Crystals Outside the Symmetric Subspace.
Phys Rev Lett
December 2024
Indian Institute of Technology, Department of Physics, -Bombay, Powai, Mumbai 400076, India.
Exploring continuous time crystals (CTCs) within the symmetric subspace of spin systems has been a subject of intensive research in recent times. Thus far, the stability of the time-crystal phase outside the symmetric subspace in such spin systems has gone largely unexplored. Here, we investigate the effect of including the asymmetric subspaces on the dynamics of CTCs in a driven dissipative spin model.
View Article and Find Full Text PDFTheory for Dissipative Time Crystals in Coupled Parametric Oscillators.
Phys Rev Lett
December 2024
University of Maryland, College Park, Joint Quantum Institute, Condensed Matter Theory Center and, Department of Physics, Maryland 20742-4111, USA.
Discrete time crystals are novel phases of matter that break the discrete time translational symmetry of a periodically driven system. In this Letter, we propose a classical system of weakly nonlinear parametrically driven coupled oscillators as a test bed to understand these phases. Such a system of parametric oscillators can be used to model period-doubling instabilities of Josephson junction arrays as well as semiconductor lasers.
View Article and Find Full Text PDFResonant song recognition and the evolution of acoustic communication in crickets.
iScience
February 2025
ENI-G, a Joint Initiative of the University Medical Center Göttingen and the Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany.
Cricket song recognition is thought to evolve through modifications of a shared neural network. However, the species has an unusual recognition pattern that challenges this view: females respond to both normal male song pulse periods and periods twice as long. Of the three minimal models tested, only a single-neuron model with an oscillating membrane could explain this unusual behavior.
View Article and Find Full Text PDFUnderstanding how the collective activity of neural populations relates to computation and ultimately behavior is a key goal in neuroscience. To this end, statistical methods which describe high-dimensional neural time series in terms of low-dimensional latent dynamics have played a fundamental role in characterizing neural systems. Yet, what constitutes a successful method involves two opposing criteria: (1) methods should be expressive enough to capture complex nonlinear dynamics, and (2) they should maintain a notion of interpretability often only warranted by simpler linear models.
View Article and Find Full Text PDFClimate-induced expansion of Lyme disease in east central Ohio.
Int J Environ Health Res
January 2025
School of Geosciences, University of South Florida, Tampa, FL, USA.
The geographical distribution of Lyme disease has been attributed to changes in Earth's climate and associated distribution of its vector, ticks of the genus . This study focuses on the impact of climatic and meteorological conditions on Lyme disease transmission in East Central Ohio, an emerging hotspot of cases. Using county-level data from 2001 to 2023, we analyzed the relationship between Lyme disease cases and temperature, precipitation, and the Southern Oscillation Index (SOI) using a distributed lag nonlinear model (DLNM).
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