Chaotic Interference versus Decoherence: External Noise, State Mixing, and Quantum–Classical Correspondence

2017 ◽  
pp. 533-558 ◽  
Author(s):  
V. Sokolov Valentin ◽  
V. Zhirov Oleg
Keyword(s):  
External Noise ◽  
Classical Correspondence ◽  
State Mixing ◽  
Chaotic Interference

scholarly journals Complexity of quantum motion and quantum-classical correspondence: A phase-space approach

2020 ◽  
Vol 2 (4) ◽  
Author(s):  
Jiaozi Wang ◽  
Giuliano Benenti ◽  
Giulio Casati ◽  
Wen-ge Wang
Keyword(s):  
Phase Space ◽  
Classical Correspondence ◽  
Quantum Motion ◽  
Space Approach

scholarly journals Duplicate Detection of Spike Events: A Relevant Problem in Human Single-Unit Recordings

2021 ◽  
Vol 11 (6) ◽  
pp. 761
Author(s):  
Gert Dehnen ◽  
Marcel S. Kehl ◽  
Alana Darcher ◽  
Tamara T. Müller ◽  
Jakob H. Macke ◽  
...  
Keyword(s):  
Data Quality ◽  
Single Unit ◽  
Human Subjects ◽  
External Noise ◽  
Hospital Environment ◽  
Noise Sources ◽  
Recording Channels ◽  
Waveform Similarity ◽  
Therapeutic Procedures ◽  
Single Unit Recordings

Single-unit recordings in the brain of behaving human subjects provide a unique opportunity to advance our understanding of neural mechanisms of cognition. These recordings are exclusively performed in medical centers during diagnostic or therapeutic procedures. The presence of medical instruments along with other aspects of the hospital environment limit the control of electrical noise compared to animal laboratory environments. Here, we highlight the problem of an increased occurrence of simultaneous spike events on different recording channels in human single-unit recordings. Most of these simultaneous events were detected in clusters previously labeled as artifacts and showed similar waveforms. These events may result from common external noise sources or from different micro-electrodes recording activity from the same neuron. To address the problem of duplicate recorded events, we introduce an open-source algorithm to identify these artificial spike events based on their synchronicity and waveform similarity. Applying our method to a comprehensive dataset of human single-unit recordings, we demonstrate that our algorithm can substantially increase the data quality of these recordings. Given our findings, we argue that future studies of single-unit activity recorded under noisy conditions should employ algorithms of this kind to improve data quality.

scholarly journals Chaos for communication

2021 ◽  
Author(s):  
Murilo S. Baptista
Keyword(s):  
Information Content ◽  
Lyapunov Exponents ◽  
Communication System ◽  
Linear Superposition ◽  
Chaotic Signals ◽  
Physical Medium ◽  
Periodic Signals ◽  
Low Probability ◽  
Chaotic Interference ◽  
Source Signals

AbstractThis work shows that chaotic signals with different power spectrum and different positive Lyapunov exponents are robust to linear superposition, meaning that the superposition preserves the Lyapunov exponents and the information content of the source signals, even after being transmitted over non-ideal physical medium. This work tackles with great detail how chaotic signals and their information content are affected when travelling through medium that presents the non-ideal properties of multi-path propagation, noise and chaotic interference (linear superposition), and how this impacts on the proposed communication system. Physical media with other non-ideal properties (dispersion and interference with periodic signals) are also discussed. These wonderful properties that chaotic signals have allow me to propose a novel communication system based on chaos, where information composed from and to multiple users each operating with different base frequencies and that is carried by chaotic wavesignals, can be fully preserved after transmission in the open air wireless physical medium, and it can be trivially decoded with low probability of errors.

Phase Selective Oscillations in Two Noise Driven Synaptically Coupled Spiking Neurons

2015 ◽  
Vol 25 (07) ◽  
pp. 1540005
Author(s):  
Ilya Prokin ◽  
Ivan Tyukin ◽  
Victor Kazantsev
Keyword(s):  
Numerical Simulations ◽  
Coupled System ◽  
External Noise ◽  
Noise Signal ◽  
Feedback Mechanism ◽  
Spike Timing ◽  
Spiking Neurons ◽  
Time Lags ◽  
Tuning Parameters ◽  
Synaptic Inputs

The work investigates the influence of spike-timing dependent plasticity (STDP) mechanisms on the dynamics of two synaptically coupled neurons driven by additive external noise. In this setting, the noise signal models synaptic inputs that the pair receives from other neurons in a larger network. We show that in the absence of STDP feedbacks the pair of neurons exhibit oscillations and intermittent synchronization. When the synapse connecting the neurons is supplied with a phase selective feedback mechanism simulating STDP, induced dynamics of spikes in the coupled system resembles a phase locked mode with time lags between spikes oscillating about a specific value. This value, as we show by extensive numerical simulations, can be set arbitrary within a broad interval by tuning parameters of the STDP feedback.

Irrational Decimations and Path Integrals for External Noise

1982 ◽  
Vol 49 (9) ◽  
pp. 605-609 ◽  
Author(s):  
Mitchell J. Feigenbaum ◽  
Brosl Hasslacher
Keyword(s):  
Path Integrals ◽  
External Noise

Phase transition induced by external noise

1977 ◽  
Vol 64 (1) ◽  
pp. 19-21 ◽  
Author(s):  
W. Horsthemke ◽  
R. Lefever
Keyword(s):  
Phase Transition ◽  
External Noise
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