Experimental Demonstration on Quantum Sensitivity to Available Information in Decision Making

TL;DR

This paper experimentally demonstrates that quantum decision-making machinery is more sensitive to available hints than classical methods, due to quantum superposition effects, and this sensitivity persists even when superposition diminishes.

Contribution

It introduces a quantum decision-making model showing enhanced sensitivity to information compared to classical models, highlighting the role of superposition.

Findings

Quantum machinery is more sensitive to hints than classical.

Quantum sensitivity persists despite superposition decay.

Quantum superposition enhances decision-making sensitivity.

Abstract

We present an experimental illustration on the quantum sensitivity of decision making machinery. In the decision making process, we consider the role of available information, say hint, whether it influences the optimal choices. To the end, we consider a machinery method of decision making in a probabilistic way. Our main result shows that in decision making process our quantum machine is more highly sensitive than its classical counterpart to the hints we categorize into "good" and "poor." This quantum feature originates from the quantum superposition involved in the decision making process. We also show that the quantum sensitivity persists before the quantum superposition is completely destroyed.