Dataset Open Access
Over, Paul;
Bengoechea, Sergio;
Borello Busilacchi, Leonardo;
Kiffner, Martin;
Rung, Thomas;
Michailidis, Alexios A.
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<identifier identifierType="DOI">10.25592/uhhfdm.21872</identifier>
<creators>
<creator>
<creatorName>Over, Paul</creatorName>
<nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-7436-5254</nameIdentifier>
<affiliation>Institute for Fluid Dynamics and Ship Theory, Hamburg University of Technology, 21073 Hamburg, Germany</affiliation>
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<creator>
<creatorName>Bengoechea, Sergio</creatorName>
<nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0009-0001-8205-5878</nameIdentifier>
<affiliation>Institute for Fluid Dynamics and Ship Theory, Hamburg University of Technology, 21073 Hamburg, Germany</affiliation>
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<creator>
<creatorName>Borello Busilacchi, Leonardo</creatorName>
<nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0009-0009-7755-382X</nameIdentifier>
<affiliation>PlanQC GmbH, D-85748 Garching, Germany</affiliation>
</creator>
<creator>
<creatorName>Kiffner, Martin</creatorName>
<nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-8321-6768</nameIdentifier>
<affiliation>PlanQC GmbH, D-85748 Garching, Germany</affiliation>
</creator>
<creator>
<creatorName>Rung, Thomas</creatorName>
<nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-3454-1804</nameIdentifier>
<affiliation>Institute for Fluid Dynamics and Ship Theory, Hamburg University of Technology, 21073 Hamburg, Germany</affiliation>
</creator>
<creator>
<creatorName>Michailidis, Alexios A.</creatorName>
<nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-8443-1064</nameIdentifier>
<affiliation>PlanQC GmbH, D-85748 Garching, Germany</affiliation>
</creator>
</creators>
<titles>
<title>Operator Learning for efficient Quantum Computation</title>
</titles>
<publisher>Universität Hamburg</publisher>
<publicationYear>2026</publicationYear>
<subjects>
<subject>Quantum Operator Learning</subject>
<subject>Qubit Connectivity</subject>
<subject>Matrix Encoding</subject>
<subject>Quantum Circuits Synthesis</subject>
</subjects>
<dates>
<date dateType="Issued">2026-09-27</date>
</dates>
<resourceType resourceTypeGeneral="Dataset"/>
<alternateIdentifiers>
<alternateIdentifier alternateIdentifierType="url">https://www.fdr.uni-hamburg.de/record/21872</alternateIdentifier>
</alternateIdentifiers>
<relatedIdentifiers>
<relatedIdentifier relatedIdentifierType="DOI" relationType="IsDerivedFrom">10.48550/arXiv.2606.20184</relatedIdentifier>
<relatedIdentifier relatedIdentifierType="DOI" relationType="IsPartOf">10.25592/uhhfdm.18962</relatedIdentifier>
</relatedIdentifiers>
<version>v2</version>
<rightsList>
<rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
<rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
</rightsList>
<descriptions>
<description descriptionType="Abstract"><p>The data refers to an operator learning protocol that compiles discrete&nbsp;operators into compact quantum circuits, for which a pre-print is&nbsp;available via <a href="https://arxiv.org/abs/2606.20184">arXiv:2606.20184</a>.&nbsp;The approach learns a layered sequence of local multi-qubit gates by&nbsp;backpropagation combined with a unitary retraction, allows the qubit&nbsp;connectivity of the target hardware to be taken into account, and&nbsp;represents non-unitary operators by a block encoding with a single&nbsp;ancilla qubit. The examples include propagators of the transverse-field&nbsp;Ising model and of the Pariser&ndash;Parr&ndash;Pople model of butadiene, which are&nbsp;compared with Suzuki&ndash;Trotter expansions, as well as the finite-difference&nbsp;approximation of the second derivative for one- and two-dimensional&nbsp;qubit topologies and a dense operator arising from a panel method for&nbsp;the inviscid flow around an airfoil. The repository contains one archive&nbsp;per experiment (exp1.zip &ndash; exp4.zip).</p></description>
<description descriptionType="Other">The current work have received funding from the European Union's Horizon Europe research and innovation program (HORIZON-CL4-2021-DIGITAL-EMERGING-02-10) under grant agreement No. 101080085 QCFD.</description>
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