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Characterizing Grover search algorithm on large-scale superconducting quantum computers
Published 2025-01-01Subjects: “…State-of-the-art superconducting quantum computers…”
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Modeling Short-Range Microwave Networks to Scale Superconducting Quantum Computation
Published 2025-01-01“…A core challenge for superconducting quantum computers is to scale up the number of qubits in each processor without increasing noise or cross-talk. …”
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Superconducting quantum computing optimization based on multi-objective deep reinforcement learning
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Noise-Aware Quantum Amplitude Estimation
Published 2024-01-01“…We provide results from quantum amplitude estimation run on various IBM superconducting quantum computers and on Quantinuum's H1 trapped-ion quantum computer to show that the proposed model is a good fit for real-world experimental data. …”
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Sparse Blossom: correcting a million errors per core second with minimum-weight matching
Published 2025-01-01“…For 0.1% circuit-level depolarising noise, sparse blossom processes syndrome data in both $X$ and $Z$ bases of distance-17 surface code circuits in less than one microsecond per round of syndrome extraction on a single core, which matches the rate at which syndrome data is generated by superconducting quantum computers. Our implementation is open-source, and has been released in version 2 of the PyMatching library.…”
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Comparative study of quantum error correction strategies for the heavy-hexagonal lattice
Published 2025-02-01“…In this work, we make a comparative study of possible strategies to overcome this limitation for the heavy-hexagonal lattice, the architecture of current IBM superconducting quantum computers. We explore two complementary strategies: the search for an efficient embedding of the surface code into the heavy-hexagonal lattice, as well as the use of codes whose connectivity requirements are naturally tailored to this architecture, such as subsystem-type and Floquet codes. …”
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