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Fabrication and Characterization of Superconducting Resonators
Published on: May 21, 2016
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An alternate protocol to achieve stochastic and deterministic resonances.
Ishant Tiwari1, Darshil Dave1, Richa Phogat1
1Department of Physics, Indian Institute of Technology, Bombay, Powai, Mumbai-400 076, India.
Chaos (Woodbury, N.Y.)
|November 3, 2017
Summary
This study explores Stochastic Resonance (SR) and Deterministic Resonance (DR) in two systems by tuning parameters, not just noise. Optimal parameter settings maximize information transfer, demonstrating a resonance phenomenon useful for understanding biological signal detection.
Area of Science:
- Nonlinear dynamics
- Complex systems
- Signal processing
Background:
- Stochastic Resonance (SR) and Deterministic Resonance (DR) are phenomena where a non-zero level of noise or chaos enhances signal detection.
- Conventional studies vary noise/chaos amplitude, but this work explores parameter tuning for resonance effects.
Purpose of the Study:
- To investigate the ubiquitousness of SR and DR in unrelated systems (FitzHugh-Nagumo and bistable potential).
- To explore resonance phenomena by regulating tunable system parameters (setpoints) instead of noise/chaos amplitude.
- To quantify information transfer and identify resonance regions.
Main Methods:
- Studied FitzHugh-Nagumo and bistable potential models.
- Regulated tunable system parameters ('setpoint') as the primary variable.
- Quantified input-output signal information transfer using the normalized cross-correlation coefficient (|CCC|).
- Analyzed |CCC| variation with setpoint and noise/chaos amplitude using heat maps.
Main Results:
- An optimal setpoint value was found to maximize information transfer (|CCC|) in both systems.
- |CCC| exhibited unimodal variation with the setpoint, characteristic of SR/DR.
- Heat maps revealed resonance regions in the noise-setpoint plane, indicating enhanced signal detection.
- Regulating setpoint alone did not induce Coherence Resonance (CR).
Conclusions:
- Resonance phenomena (SR/DR) can be induced and optimized by tuning system parameters, not just external noise/chaos.
- The identified resonance regions offer insights into biological signal detection mechanisms in noisy environments.
- Parameter-based resonance differs from noise-driven resonance and Coherence Resonance.
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