Self-Improving Quantum Search: Using Grover's Algorithm to Discover Superior Algorithms

We propose a framework for algorithmic self-improvement based on quantum search. The core idea is to use Grover’s algorithm to search the space of quantum algorithms for one that outperforms Grover itself. The discovered algorithm then searches for an even better algorithm, and so on. We formalize this recursive improvement process and analyze the conditions under which it converges to optimal query complexity.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-22
DOI
https://doi.org/10.5281/zenodo.18333327
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
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article

Self-Improving Quantum Search: Using Grover's Algorithm to Discover Superior Algorithms

Kaoru Aguilera Katayama
Zenodo (CERN European Organization for Nuclear Research)
Quantum Computing Algorithms and Architecture
article

Self-Improving Quantum Search: Using Grover's Algorithm to Discover Superior Algorithms

Kaoru Aguilera Katayama
article en

Abstract

We propose a framework for algorithmic self-improvement based on quantum search. The core idea is to use Grover’s algorithm to search the space of quantum algorithms for one that outperforms Grover itself. The discovered algorithm then searches for an even better algorithm, and so on. We formalize this recursive improvement process and analyze the conditions under which it converges to optimal query complexity.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 81%
Quantum Computing Algorithms and Architecture
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Self-Improving Quantum Search: Using Grover's Algorithm to Discover Superior Algorithms — Kaoru Aguilera Katayama · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS