A new sparse Pauli-frame method shows coherent noise thresholds are overestimated by a factor of ~4 under Pauli-twirling and revises the T-to-S gate error rate factor to as high as 7 at distance d=5.
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Ensemble Feature Selection trains a ridge-regression linear estimator on an ensemble of noisy channels to estimate process infidelity of non-Clifford gates, validated against IRB on IBM hardware with 0.01 precision over 0.02-0.2 infidelity range.
A 120-qubit digital simulation of 1D Fermi-Hubbard dynamics on IBM hardware matches TDVP tensor-network results to ~1% RMSE up to t≈5.2, with a large wall-clock speedup at the point of divergence.
Quantum DMFT framework combining Gaussian subspace state representation with compressed circuits for Green's functions, shown to converge in simulation and run on 8-qubit IBM hardware.
Simplified error models such as Pauli twirling lead to severe discrepancies, including under/over-estimation, measurement dependencies, and fidelity oscillations, in iterative quantum network protocols.
citing papers explorer
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Computing logical error thresholds with the Pauli Frame Sparse Representation
A new sparse Pauli-frame method shows coherent noise thresholds are overestimated by a factor of ~4 under Pauli-twirling and revises the T-to-S gate error rate factor to as high as 7 at distance d=5.
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Non-Clifford Benchmarking via Ensemble Feature Selection
Ensemble Feature Selection trains a ridge-regression linear estimator on an ensemble of noisy channels to estimate process infidelity of non-Clifford gates, validated against IRB on IBM hardware with 0.01 precision over 0.02-0.2 infidelity range.
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Fast, accurate, high-resolution simulation of large-scale Fermi-Hubbard models on a digital quantum processor
A 120-qubit digital simulation of 1D Fermi-Hubbard dynamics on IBM hardware matches TDVP tensor-network results to ~1% RMSE up to t≈5.2, with a large wall-clock speedup at the point of divergence.
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Efficient Quantum Implementation of Dynamical Mean Field Theory for Correlated Materials
Quantum DMFT framework combining Gaussian subspace state representation with compressed circuits for Green's functions, shown to converge in simulation and run on 8-qubit IBM hardware.
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Limitations of Error Model Approximations in Quantum Network Simulation
Simplified error models such as Pauli twirling lead to severe discrepancies, including under/over-estimation, measurement dependencies, and fidelity oscillations, in iterative quantum network protocols.