Optimization driven quantum circuit reduction

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autorschaft

Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Aufsatznummer104509
FachzeitschriftNew journal of physics
Jahrgang27
Ausgabenummer10
PublikationsstatusVeröffentlicht - 22 Okt. 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.

ASJC Scopus Sachgebiete

Zitieren

Optimization driven quantum circuit reduction. / Rosenhahn, Bodo; Osborne, Tobias J.; Hirche, Christoph.
in: New journal of physics, Jahrgang 27, Nr. 10, 104509, 22.10.2025.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Rosenhahn B, Osborne TJ, Hirche C. Optimization driven quantum circuit reduction. New journal of physics. 2025 Okt 22;27(10):104509. doi: 10.1088/1367-2630/ae0e40
Rosenhahn, Bodo ; Osborne, Tobias J. ; Hirche, Christoph. / Optimization driven quantum circuit reduction. in: New journal of physics. 2025 ; Jahrgang 27, Nr. 10.
Download
@article{1e6de627862b4d5cb9d99eb02ed7f6e7,
title = "Optimization driven quantum circuit reduction",
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",
author = "Bodo Rosenhahn and Osborne, {Tobias J.} and Christoph Hirche",
note = "Publisher Copyright: {\textcopyright} 2025 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft.",
year = "2025",
month = oct,
day = "22",
doi = "10.1088/1367-2630/ae0e40",
language = "English",
volume = "27",
journal = "New journal of physics",
issn = "1367-2630",
publisher = "Institute of Physics",
number = "10",

}

Download

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 -

Von denselben Autoren