SLIQ: Quantum Image Similarity Networks on Noisy Quantum Computers

Daniel Silver, Tirthak Patel, Aditya Ranjan, Harshitta Gandhi, William Cutler +1 more
9/26/2023
quant-phcs.CVeess.IV

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Abstract

Exploration into quantum machine learning has grown tremendously in recent years due to the ability of quantum computers to speed up classical programs. However, these efforts have yet to solve unsupervised similarity detection tasks due to the challenge of porting them to run on quantum computers. To overcome this challenge, we propose SLIQ, the first open-sourced work for resource-efficient quantum similarity detection networks, built with practical and effective quantum learning and variance-reducing algorithms.

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Cite this paper

@article{silver2023sliq,
  title  = {SLIQ: Quantum Image Similarity Networks on Noisy Quantum Computers},
  author = {Daniel Silver and Tirthak Patel and Aditya Ranjan and Harshitta Gandhi and William Cutler and Devesh Tiwari},
  year   = {2023},
  eprint = {2309.15259},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2309.15259v1}
}

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