A 256-atom neutral ytterbium processor demonstrates fault-tolerant entanglement of 24 logical qubits and runs Bernstein-Vazirani on 28 logical qubits with better-than-physical error rates using erasure conversion.
Fault-tolerant quantum computation
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Mid-circuit stabilizer verification in six-qubit GSE-encoded Clifford Trotter steps reduces logical error rates by up to 54% on Barium ion hardware, with the gain vanishing if checks are deferred to circuit end.
VarQEC uses a distinguishability loss as a machine-learning objective to variationally discover resource-efficient encoding circuits optimized for given noise models.
New combinatorial proofs and circuit designs for quantum error correction reduce physical qubit overhead by up to 10x and time overhead by 2-6x for codes including Steane, Golay, and surface codes.
citing papers explorer
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Fault-tolerant quantum computation with a neutral atom processor
A 256-atom neutral ytterbium processor demonstrates fault-tolerant entanglement of 24 logical qubits and runs Bernstein-Vazirani on 28 logical qubits with better-than-physical error rates using erasure conversion.
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Mid-Circuit Measurements for Clifford Noise Reduction in Hamiltonian Simulations
Mid-circuit stabilizer verification in six-qubit GSE-encoded Clifford Trotter steps reduces logical error rates by up to 54% on Barium ion hardware, with the gain vanishing if checks are deferred to circuit end.
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Learning Encodings by Maximizing State Distinguishability: Variational Quantum Error Correction
VarQEC uses a distinguishability loss as a machine-learning objective to variationally discover resource-efficient encoding circuits optimized for given noise models.
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Lower overhead fault-tolerant building blocks for noisy quantum computers
New combinatorial proofs and circuit designs for quantum error correction reduce physical qubit overhead by up to 10x and time overhead by 2-6x for codes including Steane, Golay, and surface codes.