Linearized gate set tomography scales error characterization to many qubits via sparse models, linear fitting, and shallow circuits, with simulations showing accuracy on 10-qubit systems including crosstalk.
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Bench- marking quantum processor performance at scale
13 Pith papers cite this work. Polarity classification is still indexing.
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A protocol for approximate error correction in quantum simulations of SU(2) lattice gauge theories that extracts gauge-violation syndromes via group QFT and applies iterative recovery sweeps called gauge cooling.
Thermodynamic recycling of algorithmic failure branches enables information erasure with heat dissipation below the Landauer limit on a quantum processor.
SCALA is a signaling cellular automaton with local attraction that achieves ~7.5% threshold and p_L proportional to p^{d/4} scaling for toric codes while keeping computation strictly local and robust to measurement and decoder noise.
A 50-qubit quantum processor produces dynamical structure factors for KCuF3 that quantitatively match neutron-scattering measurements of its spinon spectrum.
QESEM is a characterization-based error mitigation technique that achieves unbiased estimates with substantially reduced runtime cost compared to probabilistic error cancellation while outperforming zero-noise extrapolation on utility-scale circuits.
Gaussian randomized rounding on two-qubit marginals of depth-D circuits with local depolarizing noise p yields samples whose expected Max-Cut cost matches the noisy quantum device up to an approximation ratio of 1-O[(1-p)^D].
VarQEC uses a distinguishability loss as a machine-learning objective to variationally discover resource-efficient encoding circuits optimized for given noise models.
Genetic algorithm-optimized dynamical decoupling sequences empirically outperform canonical DD sequences on IBM quantum processors for circuits up to 100 qubits, with gains increasing with size and complexity.
Exascale classical simulation validates noise-tolerant performance of a 98-qubit QPU up to 48 qubits for LR-QAOA, with statistical analysis showing coherent regime up to 93 qubits before outputs become indistinguishable from random.
In the large-N limit, spin squeezing torsion yields a nonlinear qubit governed by the two-state Gross-Pitaevskii equation that solves single-input state discrimination on the Bloch sphere.
Offset-charge-tunable transmon qubit achieves 99.37% fidelity in charge-parity mapping and over 93.4% in continuous monitoring at 4 μs intervals via randomized benchmarking.
QPDE applied to 2- and 3-spin Heisenberg models on IBM processors yields 85-93% accuracy versus classical values after noise mitigation.
citing papers explorer
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Scalable linearized gate set tomography
Linearized gate set tomography scales error characterization to many qubits via sparse models, linear fitting, and shallow circuits, with simulations showing accuracy on 10-qubit systems including crosstalk.
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Approximate Error Correction for Quantum Simulations of SU(2) Lattice Gauge Theories
A protocol for approximate error correction in quantum simulations of SU(2) lattice gauge theories that extracts gauge-violation syndromes via group QFT and applies iterative recovery sweeps called gauge cooling.
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Thermodynamic Recycling of Algorithmic Failure Branches: Quantum-Computer Demonstration with Quantum Error Correction
Thermodynamic recycling of algorithmic failure branches enables information erasure with heat dissipation below the Landauer limit on a quantum processor.
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High-performance cellular automaton decoders for quantum repetition and toric code
SCALA is a signaling cellular automaton with local attraction that achieves ~7.5% threshold and p_L proportional to p^{d/4} scaling for toric codes while keeping computation strictly local and robust to measurement and decoder noise.
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Benchmarking quantum simulation with neutron-scattering experiments
A 50-qubit quantum processor produces dynamical structure factors for KCuF3 that quantitatively match neutron-scattering measurements of its spinon spectrum.
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Reliable high-accuracy error mitigation for utility-scale quantum circuits
QESEM is a characterization-based error mitigation technique that achieves unbiased estimates with substantially reduced runtime cost compared to probabilistic error cancellation while outperforming zero-noise extrapolation on utility-scale circuits.
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Sampling (noisy) quantum circuits through randomized rounding
Gaussian randomized rounding on two-qubit marginals of depth-D circuits with local depolarizing noise p yields samples whose expected Max-Cut cost matches the noisy quantum device up to an approximation ratio of 1-O[(1-p)^D].
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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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Empirical learning of dynamical decoupling on quantum processors
Genetic algorithm-optimized dynamical decoupling sequences empirically outperform canonical DD sequences on IBM quantum processors for circuits up to 100 qubits, with gains increasing with size and complexity.
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Large-Scale Quantum Circuit Simulation on an Exascale System for QPU Benchmarking
Exascale classical simulation validates noise-tolerant performance of a 98-qubit QPU up to 48 qubits for LR-QAOA, with statistical analysis showing coherent regime up to 93 qubits before outputs become indistinguishable from random.
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From spin squeezing to fast state discrimination
In the large-N limit, spin squeezing torsion yields a nonlinear qubit governed by the two-state Gross-Pitaevskii equation that solves single-input state discrimination on the Bloch sphere.
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Characterizing charge-parity detection based on an offset-charge-tunable transmon qubit via randomized benchmarking
Offset-charge-tunable transmon qubit achieves 99.37% fidelity in charge-parity mapping and over 93.4% in continuous monitoring at 4 μs intervals via randomized benchmarking.
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Applications of the Quantum Phase Difference Estimation Algorithm to the Excitation Energies in Spin Systems on a NISQ Device
QPDE applied to 2- and 3-spin Heisenberg models on IBM processors yields 85-93% accuracy versus classical values after noise mitigation.