n-bit anticoncentrated distributions can be generated from O(log n) qubits via a holographic protocol of interleaved random unitaries and mid-circuit measurements.
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A tunable-coupler unit cell for fluxonium qubits delivers parallel single-qubit gate fidelities near 99.99% and two-qubit CZ fidelities around 99%, validated by generating up to 10-qubit GHZ states in a 22-qubit processor.
A pre-training diagnostic map based on spectral correlation resemblance to IQP circuits and excess structural complexity identifies suitable datasets like turbulence data for quantum generative models, yielding competitive low-resource performance.
A SQUID-array Josephson parametric amplifier achieves near-quantum-limited 20 dB gain over ~50 MHz bandwidth, with its complex gain spectra analytically reproduced by adding Fabry-Pérot interference to a quantum input-output model.
citing papers explorer
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Anticoncentrated $n$-bit distribution from $\log(n)$ qubits
n-bit anticoncentrated distributions can be generated from O(log n) qubits via a holographic protocol of interleaved random unitaries and mid-circuit measurements.
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Scalable Fluxonium Quantum Processors via Tunable-Coupler Architecture
A tunable-coupler unit cell for fluxonium qubits delivers parallel single-qubit gate fidelities near 99.99% and two-qubit CZ fidelities around 99%, validated by generating up to 10-qubit GHZ states in a 22-qubit processor.
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Toward Generative Quantum Utility via Correlation-Complexity Map
A pre-training diagnostic map based on spectral correlation resemblance to IQP circuits and excess structural complexity identifies suitable datasets like turbulence data for quantum generative models, yielding competitive low-resource performance.
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High-gain and large-bandwidth Josephson parametric amplifier influenced by Fabry-P\'erot interference
A SQUID-array Josephson parametric amplifier achieves near-quantum-limited 20 dB gain over ~50 MHz bandwidth, with its complex gain spectra analytically reproduced by adding Fabry-Pérot interference to a quantum input-output model.