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Reinforcement learning approach for finding exchange-only gate sequences for CNOT with optimized gate time
Citation Link: https://doi.org/10.15480/882.15221
Publikationstyp
Journal Article
Date Issued
2025-05-16
Sprache
English
Author(s)
Ivanova-Rohling, Violeta N.
Rohling, Niklas
TORE-DOI
Journal
Volume
12
Issue
1
Article Number
53
Citation
EPJ Quantum Technology 12 (1): 53 (2025)
Publisher DOI
Scopus ID
Exchange-only quantum computation is a version of spin-based quantum computation that entirely avoids the difficulty of controlling individual spins by a magnetic field and instead functions by sequences of exchange pulses. The challenge for exchange-only quantum computation is to find short sequences that generate the required logical quantum gates. A reduction of the total gate time of such synthesized quantum gates can help to minimize the effects of decoherence and control errors during the gate operation and thus increase the total gate fidelity. We apply reinforcement learning to the optimization of exchange-gate sequences realizing the CNOT and CZ two-qubit gates which lend themselves to the construction of universal gate sets for quantum computation. We obtain a significant improvement regarding the total gate time compared to previously published results.
Subjects
Exchange-only qubits | Optimal gate sequences | Reinforcement learning
DDC Class
530: Physics
006.3: Artificial Intelligence
621.38: Electronics, Communications Engineering
Publication version
publishedVersion
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Name
s40507-025-00363-0.pdf
Type
Main Article
Size
5.12 MB
Format
Adobe PDF