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Trapped Ion Quantum Computing

Bi-Quadratic Improvement in Conditional Quantum Search

arXiv
Authors: Akankshya Dash, Biswaranjan Panda, Arun K Pati

Year

2023

Paper ID

52648

Status

Preprint

Abstract Read

~2 min

Abstract Words

107

Citations

N/A

Abstract

The Grover search algorithm performs an unstructured search of a marked item in a database quadratically faster than classical algorithms and is shown to be optimal. Here, we show that if the search space is divided into two blocks with the local query operators and the global operators satisfy certain condition, then it is possible to achieve an improvement of bi-quadratic speed-up. Furthermore, we investigate the bi-quadratic speed-up in the presence of noise and show that it can tolerate noisy scenario. This may have potential applications for diverse fields, including database searching, and optimization, where efficient search algorithms play a pivotal role in solving complex computational problems.

Why This Paper Matters

  • This paper contributes to the Trapped-Ion Quantum Computing research area in the Quantum Articles archive.
  • It adds a 2023 reference point for readers tracking recent quantum research.
  • The Grover search algorithm performs an unstructured search of a marked item in a database quadratically faster than classical algorithms and is shown to be optimal.

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References & Citation Signals

[1] DOI https://doi.org/arXiv:2312.05680 [2] arXiv https://arxiv.org/abs/2312.05680 [3] Publisher https://arxiv.org/abs/2312.05680

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