Q-Means: Quantum Advantage for Clustering and Classification

Abstract

This project developed a quantum algorithm for clustering, similar to k-means, but that performs the distance estimation aspect of the clustering algorithm in a much more efficient manner, thus promising a potential speedup once quantum computing hardware matures to the point of being able to implement this quantum algorithm. This milestone report benchmarked performance of the quantum circuit used in the Q-Means clustering algorithm on classical simulators and current quantum hardware.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2022
Accession Number
AD1179545

Entities

People

  • Victor Putz

Organizations

  • QC Ware

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Cyber
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Commercial Aircraft
  • Computer Programs
  • Computers
  • Data Mining
  • Flight Paths
  • Information Processing
  • Information Science
  • Ion Traps
  • Machine Learning
  • Military Aircraft
  • Quantum Algorithms
  • Quantum Circuits
  • Quantum Computing
  • Quantum Information
  • Simulators
  • Two Dimensional
  • United States
  • Unmanned Aerial Vehicles
  • Unsupervised Machine Learning

Fields of Study

  • Computer science
  • Physics

Readers

  • Computer Vision.
  • Parallel and Distributed Computing.
  • Quantum Dot Semiconductor Device Photonics and Graphene Optoelectronic Materials and THz Physics.

Technology Areas

  • Quantum Computing