Details
| Original language | English |
|---|---|
| Article number | 104509 |
| Journal | New journal of physics |
| Volume | 27 |
| Issue number | 10 |
| Publication status | Published - 22 Oct 2025 |
Abstract
Implementing a quantum circuit on specific hardware with a reduced available gate set is often associated with a substantial increase in the length of the equivalent circuit. This process is also known as transpilation and due to decoherence, it is mandatory to keep quantum circuits as short as possible, without affecting functionality. In this work we propose three different transpilation approaches, based on a localized term-replacement scheme, to substantially reduce circuit lengths while preserving the unitary operation implemented by the circuit. The first variant is based on a stochastic search scheme, and the other variants are driven by a database retrieval scheme and a machine learning based decision support. We show that our proposed methods generate short quantum circuits for restricted gate sets, superior to the typical results obtained by using various qiskit and Berkley quantum synthesis toolkit optimization levels. Our method can be applied to different gate sets and scales well with an arbitrary number of qubits.
Keywords
- machine learning, quantum circuits, transpilation
ASJC Scopus subject areas
- Physics and Astronomy(all)
- General Physics and Astronomy
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In: New journal of physics, Vol. 27, No. 10, 104509, 22.10.2025.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Optimization driven quantum circuit reduction
AU - Rosenhahn, Bodo
AU - Osborne, Tobias J.
AU - Hirche, Christoph
N1 - Publisher Copyright: © 2025 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft.
PY - 2025/10/22
Y1 - 2025/10/22
N2 - Implementing a quantum circuit on specific hardware with a reduced available gate set is often associated with a substantial increase in the length of the equivalent circuit. This process is also known as transpilation and due to decoherence, it is mandatory to keep quantum circuits as short as possible, without affecting functionality. In this work we propose three different transpilation approaches, based on a localized term-replacement scheme, to substantially reduce circuit lengths while preserving the unitary operation implemented by the circuit. The first variant is based on a stochastic search scheme, and the other variants are driven by a database retrieval scheme and a machine learning based decision support. We show that our proposed methods generate short quantum circuits for restricted gate sets, superior to the typical results obtained by using various qiskit and Berkley quantum synthesis toolkit optimization levels. Our method can be applied to different gate sets and scales well with an arbitrary number of qubits.
AB - Implementing a quantum circuit on specific hardware with a reduced available gate set is often associated with a substantial increase in the length of the equivalent circuit. This process is also known as transpilation and due to decoherence, it is mandatory to keep quantum circuits as short as possible, without affecting functionality. In this work we propose three different transpilation approaches, based on a localized term-replacement scheme, to substantially reduce circuit lengths while preserving the unitary operation implemented by the circuit. The first variant is based on a stochastic search scheme, and the other variants are driven by a database retrieval scheme and a machine learning based decision support. We show that our proposed methods generate short quantum circuits for restricted gate sets, superior to the typical results obtained by using various qiskit and Berkley quantum synthesis toolkit optimization levels. Our method can be applied to different gate sets and scales well with an arbitrary number of qubits.
KW - machine learning
KW - quantum circuits
KW - transpilation
UR - http://www.scopus.com/inward/record.url?scp=105019689858&partnerID=8YFLogxK
U2 - 10.1088/1367-2630/ae0e40
DO - 10.1088/1367-2630/ae0e40
M3 - Article
AN - SCOPUS:105019689858
VL - 27
JO - New journal of physics
JF - New journal of physics
SN - 1367-2630
IS - 10
M1 - 104509
ER -