Grover search revisited; application to image pattern matching
Hiroyuki Tezuka, Kouhei Nakaji, Takahiko Satoh, Naoki Yamamoto

TL;DR
This paper proposes a practical quantum algorithm for database search and image pattern matching using approximate amplitude encoding and shallow circuits, enabling more feasible implementation of Grover's algorithm.
Contribution
It introduces a new quantum algorithm that approximately implements Grover's search with shallow circuits and demonstrates its application to image pattern matching.
Findings
Algorithm effectively performs pattern matching on images.
Uses approximate amplitude encoding with shallow quantum circuits.
Demonstrates practical feasibility of Grover-based search in image processing.
Abstract
The landmark Grover algorithm for amplitude amplification serves as an essential subroutine in various type of quantum algorithms, with guaranteed quantum speedup in query complexity. However, there have been no proposal to realize the original motivating application of the algorithm, i.e., the database search or more broadly the pattern matching in a practical setting, mainly due to the technical difficulty in efficiently implementing the data loading and amplitude amplification processes. In this paper, we propose a quantum algorithm that approximately executes the entire Grover database search or pattern matching algorithm. The key idea is to use the recently proposed approximate amplitude encoding method on a shallow quantum circuit, together with the easily implementable inversion-test operation for realizing the projected quantum state having similarity to the query data, followed…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
