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Bulletin of the American Physical Society

Charting the design landscape of circuit QED for optimal gates

Felix Motzoi, Michael H. Goerz, Christiane P. Koch, K. Birgitta Whaley

Published Mar 15, 2017• 0 citations
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With recent improvements in coherence times, superconducting transmon qubits have become a promising platform for quantum computing. They can be flexibly engineered over a wide range of parameters, but also require us to identify an efficient operating regime. Using state-of-the-art quantum optimal control techniques, we exhaustively explore the landscape for creation and removal of entanglement over a wide range of design parameters. We identify an optimal operating region outside of the usually considered strongly dispersive regime, where multiple sources of entanglement interfere simultaneously, which we name the quasi-dispersive straddling qutrits regime. At a chosen point in this region, a universal gate set is realized by applying microwave fields for gate durations of 50 ns, with errors approaching the limit of intrinsic transmon coherence. Our systematic quantum optimal control approach is easily adapted to explore the parameter landscape of other quantum technology platforms.

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Abstract With recent improvements in coherence times, superconducting transmon qubits have become a promising platform for quantum computing. They can be flexibly engineered over a wide range of parameters, but also require us to identify an efficient operating regime. Using state-of-the-art quantum optimal control techniques, we exhaustively explore the landscape for creation and removal of entanglement over a wide range of design parameters. We identify an optimal operating region outside of the usually considered strongly dispersive regime, where multiple sources of entanglement interfere simultaneously, which we name the quasi-dispersive straddling qutrits regime. At a chosen point in this region, a universal gate set is realized by applying microwave fields for gate durations of 50 ns, with errors approaching the limit of intrinsic transmon coherence. Our systematic quantum optimal control approach is easily adapted to explore the parameter landscape of other quantum technology platforms.

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Quantum landscape tomography for efficient single-gate optimization on quantum computers

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Abstract Circuit optimization is a fundamental task for practical applications of near-term quantum computers. In this work we address this challenge through the powerful lenses of tensor network theory. Our approach involves the full characterization of the influence of individual gates on the entire circuit, a process we call quantum landscape tomography. We derive the necessary and sufficient requirements of this process and propose two implementations, respectively based on 2-unitary design and Clifford tableaux. The latter implementation strikes a convenient balance between the number of shots and the number of circuits needed for the tomography. Numerical simulations based on a realistic noise model demonstrate the advantage of our approach with respect to both gradient-free and gradient-based methods. Overall, our findings highlight the potential of quantum landscape tomography to enhance circuit optimization in near-term quantum computing applications.

arXiv:2407.18305•Quantum Science and Technology•Jun 5, 2026•0 citations
With recent improvements in coherence times, superconducting transmon qubits have become a promising platform for quantum computing. They can be flexibly engineered over a wide range of parameters, but also require us to identify an efficient operating regime. Using state-of-the-art quantum optimal control techniques, we exhaustively explore the landscape for creation and removal of entanglement over a wide range of design parameters. We identify an optimal operating region outside of the usually considered strongly dispersive regime, where multiple sources of entanglement interfere simultaneously, which we name the quasi-dispersive straddling qutrits regime. At a chosen point in this region, a universal gate set is realized by applying microwave fields for gate durations of 50 ns, with errors approaching the limit of intrinsic transmon coherence. Our systematic quantum optimal control approach is easily adapted to explore the parameter landscape of other quantum technology platforms.
Abstract With recent improvements in coherence times, superconducting transmon qubits have become a promising platform for quantum computing. They can be flexibly engineered over a wide range of parameters, but also require us to identify an efficient operating regime. Using state-of-the-art quantum optimal control techniques, we exhaustively explore the landscape for creation and removal of entanglement over a wide range of design parameters. We identify an optimal operating region outside of the usually considered strongly dispersive regime, where multiple sources of entanglement interfere simultaneously, which we name the quasi-dispersive straddling qutrits regime. At a chosen point in this region, a universal gate set is realized by applying microwave fields for gate durations of 50 ns, with errors approaching the limit of intrinsic transmon coherence. Our systematic quantum optimal control approach is easily adapted to explore the parameter landscape of other quantum technology platforms.
Abstract Circuit optimization is a fundamental task for practical applications of near-term quantum computers. In this work we address this challenge through the powerful lenses of tensor network theory. Our approach involves the full characterization of the influence of individual gates on the entire circuit, a process we call quantum landscape tomography. We derive the necessary and sufficient requirements of this process and propose two implementations, respectively based on 2-unitary design and Clifford tableaux. The latter implementation strikes a convenient balance between the number of shots and the number of circuits needed for the tomography. Numerical simulations based on a realistic noise model demonstrate the advantage of our approach with respect to both gradient-free and gradient-based methods. Overall, our findings highlight the potential of quantum landscape tomography to enhance circuit optimization in near-term quantum computing applications.