Develops practical scalable protocols to upper-bound total variation distance for quantum circuits with non-Clifford two-qubit gates and generalizes Pauli twirling to non-Pauli bases.
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Preskill, Quantum computing in the NISQ era and beyond, Quantum2, 79 (2018)
19 Pith papers cite this work. Polarity classification is still indexing.
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A GNN predicts Gaussians over QAOA parameters to create graph-conditioned trust regions that reduce circuit evaluations for MaxCut from 85-343 down to 45 while keeping approximation ratios within 3 points of heuristics.
A nonequilibrium Kramers turnover is isolated in a Kerr parametric oscillator via analytical rescaling of effective friction and temperature, confirmed by temperature-dependent phase-slip measurements in a MEMS device.
Merged amplitude encoding reduces circuit executions in CCQKAN by a factor of n with 1-2 extra qubits and preserves trainability in numerical tests on networks and MNIST classification.
σ-VQE uses low-depth circuits and an energy-selective cost function to preferentially prepare quantum many-body scar states on NISQ devices.
Trapped-ion experiment generates all four Bell states of GKP qubits via beamsplitter interference of qunaught states and applies error correction to extend their lifetime.
Forward–reverse evolution, Richardson extrapolation, and runtime randomization cancel the leading O(T^{-1}) adiabatic phase error in Berry phase estimation, yielding O(ε^{-3/2}) total cost (QPE) or Θ(ε^{-1/3}) coherent runtime (Hadamard test).
A trapped-ion architecture based on LDPC codes and cat-state factories achieves 110 logical qubits and one million T gates per day using 2514 physical qubits, with estimates for Heisenberg model simulation on 100 sites in one month using 10000 qubits.
Localized correlation-converged virtual orbitals yield molecular dissociation energies comparable to or better than cc-pVXZ basis sets while using substantially fewer orbitals.
Graph neural networks that incorporate local hardware noise parameters as graph features enable quantum error mitigation with better scalability and lower error than traditional global regression methods on 10-16 qubit circuits.
The authors construct a variational quantum regression algorithm with parameters mapped to regression coefficients, but the cost function has a scaling degeneracy that breaks the claimed equivalence to mean squared error.
Directly training soft-unitary matrices with a unitarity regularization term and converting them to circuits via alignment enables faster training and lower loss than gate-based optimization on small quantum classification and reinforcement learning tasks.
Doubly geometric control achieves simultaneous fourth-order suppression of control errors via level-n identity constructions, with extension to sixth order.
Krylov shadow tomography produces exponentially converging bounds on quantum Fisher information that exactly match the QFI for low-rank states and outperform existing polynomial lower bounds.
A new optimization-based protocol estimates quantum coherence from scarce data with system-size-independent cost and is experimentally demonstrated.
Exploiting sign freedom in Cirac-Zoller red-sideband pulses enables pulse cancellation that cuts multi-controlled gate times and reduces LCU select-operator pulse cost from O(L log L) to O(L).
Physics-informed quantum neural networks trained on noisy measurements can construct nontrivial decision boundaries to classify quantum states via order parameters and are suited for NISQ hardware due to links with Markovian open many-body systems.
Bayesian optimization with Gaussian process surrogate accelerates numerical calibration of Mølmer-Sørensen gate parameters, with performance tied to quantum projection noise.
The paper identifies four key hurdles in the transition from NISQ to FASQ quantum computers and argues that targeting them will accelerate progress toward useful quantum advantage.
citing papers explorer
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Quantum Accreditation with Non-Clifford Two-qubit Gates
Develops practical scalable protocols to upper-bound total variation distance for quantum circuits with non-Clifford two-qubit gates and generalizes Pauli twirling to non-Pauli bases.
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Query-Efficient Quantum Approximate Optimization via Graph-Conditioned Trust Regions
A GNN predicts Gaussians over QAOA parameters to create graph-conditioned trust regions that reduce circuit evaluations for MaxCut from 85-343 down to 45 while keeping approximation ratios within 3 points of heuristics.
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Nonequilibrium Kramers Turnover in a Kerr Parametric Oscillator
A nonequilibrium Kramers turnover is isolated in a Kerr parametric oscillator via analytical rescaling of effective friction and temperature, confirmed by temperature-dependent phase-slip measurements in a MEMS device.
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Merged amplitude encoding for Chebyshev quantum Kolmogorov--Arnold networks: trading qubits for circuit executions
Merged amplitude encoding reduces circuit executions in CCQKAN by a factor of n with 1-2 extra qubits and preserves trainability in numerical tests on networks and MNIST classification.
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$\sigma$-VQE: Excited-state preparation of quantum many-body scars with shallow circuits
σ-VQE uses low-depth circuits and an energy-selective cost function to preferentially prepare quantum many-body scar states on NISQ devices.
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Error Correction of Beamsplitter-Generated Entangled GKP States
Trapped-ion experiment generates all four Bell states of GKP qubits via beamsplitter interference of qunaught states and applies error correction to extend their lifetime.
-
Adiabatic Error Cancellation in Berry Phase Estimation
Forward–reverse evolution, Richardson extrapolation, and runtime randomization cancel the leading O(T^{-1}) adiabatic phase error in Berry phase estimation, yielding O(ε^{-3/2}) total cost (QPE) or Θ(ε^{-1/3}) coherent runtime (Hadamard test).
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Fault-Tolerant Quantum Computing with Trapped Ions: The Walking Cat Architecture
A trapped-ion architecture based on LDPC codes and cat-state factories achieves 110 logical qubits and one million T gates per day using 2514 physical qubits, with estimates for Heisenberg model simulation on 100 sites in one month using 10000 qubits.
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Correlation-Converged Virtual Orbitals for Accurate and Efficient Quantum Molecular Simulations
Localized correlation-converged virtual orbitals yield molecular dissociation energies comparable to or better than cc-pVXZ basis sets while using substantially fewer orbitals.
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Scalable Quantum Error Mitigation with Physically Informed Graph Neural Networks
Graph neural networks that incorporate local hardware noise parameters as graph features enable quantum error mitigation with better scalability and lower error than traditional global regression methods on 10-16 qubit circuits.
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Explainable quantum regression algorithm with encoded data structure
The authors construct a variational quantum regression algorithm with parameters mapped to regression coefficients, but the cost function has a scaling degeneracy that breaks the claimed equivalence to mean squared error.
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Soft-Quantum Algorithms
Directly training soft-unitary matrices with a unitarity regularization term and converting them to circuits via alignment enables faster training and lower loss than gate-based optimization on small quantum classification and reinforcement learning tasks.
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Universal Robust Quantum Gates via Doubly Geometric Control
Doubly geometric control achieves simultaneous fourth-order suppression of control errors via level-n identity constructions, with extension to sixth order.
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Superiority of Krylov shadow tomography in estimating quantum Fisher information: From bounds to exactness
Krylov shadow tomography produces exponentially converging bounds on quantum Fisher information that exactly match the QFI for low-rank states and outperform existing polynomial lower bounds.
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Scalable protocol to coherence estimation from scarce data: Theory and experiment
A new optimization-based protocol estimates quantum coherence from scarce data with system-size-independent cost and is experimentally demonstrated.
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Efficient Multi-Controlled Gate Implementation in Trapped-Ion Systems
Exploiting sign freedom in Cirac-Zoller red-sideband pulses enables pulse cancellation that cuts multi-controlled gate times and reduces LCU select-operator pulse cost from O(L log L) to O(L).
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Getting large-scale quantum neural networks ready for quantum hardware
Physics-informed quantum neural networks trained on noisy measurements can construct nontrivial decision boundaries to classify quantum states via order parameters and are suited for NISQ hardware due to links with Markovian open many-body systems.
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Active Learning for Calibrating Entangling Gates via Surrogate-Based Optimization
Bayesian optimization with Gaussian process surrogate accelerates numerical calibration of Mølmer-Sørensen gate parameters, with performance tied to quantum projection noise.
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Mind the gaps: The fraught road to quantum advantage
The paper identifies four key hurdles in the transition from NISQ to FASQ quantum computers and argues that targeting them will accelerate progress toward useful quantum advantage.