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Tunable Coupling Scheme for Implementing High-Fidelity Two-Qubit Gates

5 Pith papers cite this work. Polarity classification is still indexing.

5 Pith papers citing it

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quant-ph 5

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Barbell Codes: qLDPC Codes for Superconducting Quantum Hardware

quant-ph · 2026-06-04 · unverdicted · novelty 6.0

Barbell codes are a family of qLDPC codes with a matching superconducting chip layout enabling constant hardware complexity, simulated to preserve logical information over trillions of QEC cycles at 10^{-4} physical noise with under 30 data qubits per logical qubit.

Data-Driven Hamiltonian Reduction for Superconducting Qubits via Meta-Learning

quant-ph · 2026-04-27 · unverdicted · novelty 6.0

HAML meta-learns a mapping from control inputs and device parameters to effective two-qubit Hamiltonian coefficients via simulation training, then adapts online with few measurements, recovering coefficients where Schrieffer-Wolff perturbation theory fails.

Driven-dissipative entanglement of distant giant atoms

quant-ph · 2026-06-11 · unverdicted · novelty 5.0

Reports experimental generation of remote Bell entanglement between two giant atoms with fidelity 0.89 using driven-dissipative stabilization and in-situ frequency tuning.

Fabless Quantum Chip Design and Commercial Production

quant-ph · 2026-06-16 · unverdicted · novelty 4.0

Proposes a fabless-foundry ecosystem for superconducting quantum chips built on certified PDKs, SPICE-Q multiphysics modeling, parameterized cells, Q-EDA automation, and a quantum-IP market.

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Showing 4 of 4 citing papers after filters.

  • Barbell Codes: qLDPC Codes for Superconducting Quantum Hardware quant-ph · 2026-06-04 · unverdicted · none · ref 33

    Barbell codes are a family of qLDPC codes with a matching superconducting chip layout enabling constant hardware complexity, simulated to preserve logical information over trillions of QEC cycles at 10^{-4} physical noise with under 30 data qubits per logical qubit.

  • Data-Driven Hamiltonian Reduction for Superconducting Qubits via Meta-Learning quant-ph · 2026-04-27 · unverdicted · none · ref 1

    HAML meta-learns a mapping from control inputs and device parameters to effective two-qubit Hamiltonian coefficients via simulation training, then adapts online with few measurements, recovering coefficients where Schrieffer-Wolff perturbation theory fails.

  • Driven-dissipative entanglement of distant giant atoms quant-ph · 2026-06-11 · unverdicted · none · ref 11

    Reports experimental generation of remote Bell entanglement between two giant atoms with fidelity 0.89 using driven-dissipative stabilization and in-situ frequency tuning.

  • Fabless Quantum Chip Design and Commercial Production quant-ph · 2026-06-16 · unverdicted · none · ref 55

    Proposes a fabless-foundry ecosystem for superconducting quantum chips built on certified PDKs, SPICE-Q multiphysics modeling, parameterized cells, Q-EDA automation, and a quantum-IP market.