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High entropy waveforms exhibit desirable correlation properties in radar and sonar applications when multiple systems are used in close proximity. Unfortunately, the information content of these signals can impose high sampling requirements for digital detection techniques. Solvable chaotic oscillators have been proposed to address such issues due to their simple, matched filters, where hardware has been demonstrated with a bandwidth of 10-20 kHz. To extend applications of these systems, we present theory, design, and experimental verification of solvable chaos at 1 MHz using simple off-the-shelf components. The waveforms produced by this system were propagated over a 2.45 GHz RF link and detected with an RLC-based, purely analog matched filter. Further, we show that properties of this special class of chaotic systems can be exploited to yield RF noise sources that are generally advantageous for multi-user ranging applications when compared to conventional techniques. The result is a simple, low-cost, and potentially low-power RF ranging system that requires very little digital signal processing.
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http://dx.doi.org/10.3390/s20030774 | DOI Listing |
Phys Rev Lett
June 2025
Cornell University, Department of Physics, Ithaca, New York 14853, USA.
The late-time equilibrium behavior of generic interacting models is determined by the coupled hydrodynamic equations associated with the globally conserved quantities. In the presence of an external time-dependent drive, nonintegrable systems typically thermalize to an effectively infinite-temperature state, losing all memory of their initial states. However, in the presence of a large time-periodic Floquet drive, there exist special points in phase space where the strongly interacting system develops approximate emergent conservation laws.
View Article and Find Full Text PDFPhys Rev Lett
May 2025
Fudan University, Department of Physics, Shanghai 200438, China.
The growth of simple operators is essential for the emergence of chaotic dynamics and quantum thermalization. Recent studies have proposed different measures, including the out-of-time-order correlator and Krylov complexity. It is established that the out-of-time-order correlator serves as the signature of quantum many-body chaos, while the Krylov complexity provides its upper bound.
View Article and Find Full Text PDFChaos
March 2025
INRIA Bordeaux Sud Ouest, 33405 Talence Cedex, France.
Previously, we showed that computational mechanic's causal states-predictively equivalent trajectory classes for a stochastic dynamical system-can be cast into a reproducing kernel Hilbert space. The result is a widely applicable method that infers causal structure directly from very different kinds of observations and systems. Here, we expand this method to explicitly introduce the causal diffusion components it produces.
View Article and Find Full Text PDFChaos
January 2025
Department of Mathematics, Xi'an University of Science and Technology, Xi'an 710054, People's Republic of China.
The existing research studies on the basin stability of stochastic systems typically focus on smooth systems, or the attraction basins are pre-defined as easily solvable regular basins. In this work, we introduce a new framework to discover the basin stability from state time series in the non-smooth stochastic competition system under threshold control. Specifically, we approximate the drift and diffusion with threshold control parameters by an extended Kramers-Moyal expansion with initial state partitioning.
View Article and Find Full Text PDFChaos
January 2025
Instituto de Física, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.
We study an exactly solvable random walk model with long-range memory on arbitrary networks. The walker performs unbiased random steps to nearest-neighbor nodes and intermittently resets to previously visited nodes in a preferential way such that the most visited nodes have proportionally a higher probability to be chosen for revisit. The occupation probability can be expressed as a sum over the eigenmodes of the standard random walk matrix of the network, where the amplitudes slowly decay as power-laws at large times, instead of exponentially.
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