September 27, 2026 Dataset Open Access

Over, Paul; Bengoechea, Sergio; Borello Busilacchi, Leonardo; Kiffner, Martin; Rung, Thomas; Michailidis, Alexios A.

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{"DOI":"10.25592/uhhfdm.21872","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>","author":[{"family":"Over, Paul"},{"family":"Bengoechea, Sergio"},{"family":"Borello Busilacchi, Leonardo"},{"family":"Kiffner, Martin"},{"family":"Rung, Thomas"},{"family":"Michailidis,  Alexios A."}],"id":"21872","issued":{"date-parts":[[2026,9,27]]},"note":"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.","title":"Operator Learning for efficient Quantum Computation","type":"dataset","version":"v2"}