Exploring Chaotic Quantum Wave Correlations in Proton–Proton Collisions

This work introduces the F_QW fingerprint, a novel metric for quantifying synchronized wave behavior in complex systems. The method integrates three core measures—coherence (C), velocity (v), and potential (P)—into a normalized, reproducible indicator of dynamical complexity. The approach is applied to proton–proton collision data from the CERN Open Data Portal, using a Python-based analysis pipeline built with uproot, NumPy, and Matplotlib. Each dataset produces a characteristic F_QW value and corresponding Lyapunov exponent, allowing direct assessment of chaotic dynamics in high-energy collision events. Results show consistently positive Lyapunov exponents, indicating non-trivial chaotic fluctuations and sensitive dependence on initial conditions. The findings suggest that proton–proton collisions exhibit measurable chaotic signatures, offering new perspectives for exploring complexity in quantum and high-energy systems. The F_QW fingerprint bridges methods from chaos theory, computational neuroscience, and quantum physics, providing a transparent and reproducible framework for future studies. All results, scripts, and datasets are aligned with the principles of open science and data reproducibility.