Quantum Set Intersection and Its Application to Associative Memory
Abstract
We describe a quantum algorithm for computing the intersection of two sets and its application to associative memory. The algorithm is based on a modification of Grover's quantum search algorithm (Grover, 1996). We present algorithms for pattern retrieval, pattern completion, and pattern correction. We show that the quantum associative memory can store an exponential number of memories and retrieve them in sub-exponential time. We prove that this model has advantages over known classical associative memories as well as previously proposed quantum models.
Cite
Text
Salman and Baram. "Quantum Set Intersection and Its Application to Associative Memory." Journal of Machine Learning Research, 2012.Markdown
[Salman and Baram. "Quantum Set Intersection and Its Application to Associative Memory." Journal of Machine Learning Research, 2012.](https://mlanthology.org/jmlr/2012/salman2012jmlr-quantum/)BibTeX
@article{salman2012jmlr-quantum,
title = {{Quantum Set Intersection and Its Application to Associative Memory}},
author = {Salman, Tamer and Baram, Yoram},
journal = {Journal of Machine Learning Research},
year = {2012},
pages = {3177-3206},
volume = {13},
url = {https://mlanthology.org/jmlr/2012/salman2012jmlr-quantum/}
}