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This research introduces the first 12-CNOT decomposition of the double qubit excitation operator, achieving significant reductions in circuit depth and gate count compared to previous state-of-the-art methods. Since this primitive is a fundamental building block for practical quantum algorithms, optimizing its resource efficiency directly translates to substantial overall savings in complex computations.
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A 12-CNOT Double Qubit Excitation Gate

arXiv2 min read

arXiv:2608.11733v2 Announce Type: replace Abstract: In this work, we presented, to the best of our knowledge, the first reported 12-CNOT decomposition of the double qubit excitation operator. We compared our new circuit with the previous SOTA 13-CNOT circuits in 4 different metrics. Our new circuit has the lowest CNOT count (12), lowest CNOT depth (8, roughly 27% reduction), and lowest total circuit depth (15, 25% reduction) among all the previous SOTA circuits. Further, we only added 2 extra one-qubit gates compared to the lowest one-qubit gate count (11) among the previous SOTA circuits. As the double qubit excitation operator can be used as a building block hundreds or thousands of times in practical quantum algorithms, any reduction in such primitives compounds over the full circuit, resulting in significant overall resource savings.

Abstract:In this work, we presented, to the best of our knowledge, the first reported 12-CNOT decomposition of the double qubit excitation operator. We compared our new circuit with the previous SOTA 13-CNOT circuits in 4 different metrics. Our new circuit has the lowest CNOT count (12), lowest CNOT depth (8, roughly 27% reduction), and lowest total circuit depth (15, 25% reduction) among all the previous SOTA circuits. Further, we only added 2 extra one-qubit gates compared to the lowest one-qubit gate count (11) among the previous SOTA circuits. As the double qubit excitation operator can be used as a building block hundreds or thousands of times in practical quantum algorithms, any reduction in such primitives compounds over the full circuit, resulting in significant overall resource savings.

Quantum Physics (quant-ph); Artificial Intelligence (cs.AI)

arXiv:2608.11733 [quant-ph]

(or arXiv:2608.11733v2 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2608.11733 Focus to learn more arXiv-issued DOI via DataCite

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Full text under the publisher's open licence · 221 words

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