Quantum Superposition and Measurement Effects in Social Interaction Experiments

Abstract

Quantum computing introduces a transformative approach to social science research by integrating quantum probability models into social interaction experiments. This study examines the effects of quantum superposition, measurement-induced state collapse, and interference on decision-making processes. Compared to classical probability models, quantum approaches offer a more accurate representation of cognitive uncertainty, preference reversals, and contextual dependencies. The research highlights the advantages of quantum measurement in survey design, behavioral analysis, and policy simulations. However, challenges remain, including the limitations of current quantum hardware, the interdisciplinary gap between quantum mechanics and social sciences, and ethical concerns regarding data security and experimental manipulation. Future research should focus on refining quantum experimental methodologies, enhancing computational capabilities, and developing ethical guidelines for quantum-driven social science applications. By addressing these challenges, quantum computing can provide new theoretical insights and practical advancements in understanding human behavior and collective decision-making.