Strange Bedfellows: Quantum Mechanics and Data Mining

TL;DR

This paper explores how quantum mechanics principles can be applied to data mining, specifically for clustering, by mapping data problems into quantum frameworks and leveraging quantum evolution to identify clusters.

Contribution

It introduces a novel approach of using quantum mechanics to perform data clustering, bridging physics and data analysis in an innovative way.

Findings

Quantum mapping of clustering problems

Quantum evolution facilitates cluster formation

Potential for quantum-enhanced data analysis

Abstract

Last year, in 2008, I gave a talk titled {\it Quantum Calisthenics}. This year I am going to tell you about how the work I described then has spun off into a most unlikely direction. What I am going to talk about is how one maps the problem of finding clusters in a given data set into a problem in quantum mechanics. I will then use the tricks I described to let quantum evolution lets the clusters come together on their own.