Adiabatic Quantum Computing for Binary Clustering
classification
📊 stat.ML
quant-ph
keywords
computingquantumadiabaticbinaryclusteringadiabaticallyadoptapproach
pith:CVY3OHEV Add to your LaTeX paper
What is a Pith Number?\usepackage{pith}
\pithnumber{CVY3OHEV}
Prints a linked pith:CVY3OHEV badge after your title and writes the identifier into PDF metadata. Compiles on arXiv with no extra files. Learn more
read the original abstract
Quantum computing for machine learning attracts increasing attention and recent technological developments suggest that especially adiabatic quantum computing may soon be of practical interest. In this paper, we therefore consider this paradigm and discuss how to adopt it to the problem of binary clustering. Numerical simulations demonstrate the feasibility of our approach and illustrate how systems of qubits adiabatically evolve towards a solution.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.