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Updated: Jul 30, 2025

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents
Published on: May 16, 2025
Distorted stability pattern and chaotic features for quantized prey-predator-like dynamics.
1Departamento de Física e Astronomia, Faculdade de Ciências da Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto, Portugal.
Quantum mechanics reveals how quantum fluctuations distort prey-predator systems, affecting stability and leading to chaotic patterns in discrete models. This study quantifies these quantum effects on Lotka-Volterra dynamics.
Area of Science:
- Theoretical Physics
- Quantum Mechanics
- Mathematical Biology
Background:
- Investigates prey-predator systems using quantum mechanics.
- Focuses on topological quantum domains and quantum phase-space descriptions.
- Utilizes Weyl-Wigner quantum mechanics for analysis.
Purpose of the Study:
- To explore nonequilibrium and instability features in prey-predator-like systems.
- To map Lotka-Volterra (LV) dynamics onto a quantum framework.
- To quantify the influence of quantum fluctuations on system equilibrium and stability.
Main Methods:
- Employs the generalized Wigner flow for one-dimensional Hamiltonian systems.
- Maps LV equations to the Heisenberg-Weyl noncommutative algebra ([x,k]=i).
- Analyzes non-Liouvillian patterns using Wigner currents and Gaussian ensemble parameters.
- Considers discretized time to identify bifurcation regimes.
Main Results:
- Quantum distortions affect hyperbolic equilibrium and stability parameters of prey-predator dynamics.
- Nonstationarity and non-Liouvillianity are quantified via Wigner currents and Gaussian parameters.
- Discretized time reveals nonhyperbolic bifurcation regimes with chaotic patterns dependent on Gaussian localization.
Conclusions:
- Quantum fluctuations significantly influence the equilibrium and stability of Lotka-Volterra driven systems.
- The study extends the quantification of quantum effects from continuous (hyperbolic) to discrete (chaotic) domains.
- Demonstrates the applicability of the generalized Wigner information flow framework to complex systems.
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