Can the observer know the state of Schrodinger's cat without opening the box?

TL;DR

This paper introduces a quantum expected value theory and decision-making framework that allows observers to infer the state of Schrödinger's cat without opening the box, using quantum decision trees optimized by genetic programming.

Contribution

It proposes a novel quantum decision theory with value operators and quantum decision trees, integrating genetic programming for optimization under uncertainty.

Findings

Quantum decision trees can effectively guide state inference.

Genetic programming optimizes quantum decision strategies.

The framework enables decision-making without direct observation.

Abstract

In order to know if the Schrodinger's cat is alive or dead without opening the box, observers have to play a game with nature. The observers have to "guess" (with degrees of belief) the state of the cat due to incomplete information; in other words, the observers' decision has to be made under uncertainty. We propose a quantum expected value theory for decision-making under uncertainty. Value operator is proposed to guide observers to choose corresponding actions based on their subjective beliefs through objective quantum world by maximizing the value from the measured historical results. The value operator, as a quantum decision tree, can be constructed from both quantum gates and logic operations. Genetic programming is applied to optimize quantum decision trees.