Zero-noise extrapolation has a finite-shot help-harm boundary below which it increases local mean-squared error due to variance penalties outweighing bias reduction.
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10 Pith papers cite this work, alongside 283 external citations. Polarity classification is still indexing.
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quant-ph 10representative citing papers
VQE-PDFT hybrid framework computes electron transfer in ErCRY4 cryptochrome protein with rates aligning to experiments using quantum circuits and QM/MM modeling.
Proves finite-shot mean-squared-error laws for virtual distillation and symmetry verification that define certified operating windows and a selection trichotomy for their comparison.
A tailored quantum multi-programming workflow for the LUCJ ansatz enables parallel circuit execution with SQD/ext-SQD post-processing that mitigates cross-talk, yielding ethanol energies within 0.001 kcal/mol of classical HCI references.
GSC-QEMit adaptively mitigates quantum errors using hierarchical context clustering, Gaussian-process forecasting, and contextual bandits, delivering 9% higher average logical fidelity than unmitigated runs in Qiskit Aer simulations.
SNT merges SV and PEC for subspace-tailored error mitigation in Trotterized FHM simulations, mapping out optimal combinations by hardware quality and shot budget while quantifying when noisy devices could surpass classical methods.
I-QMapper is a Jupyter-based interactive tool that combines qubit layout construction with real-time and historical calibration analytics for error-aware mapping on superconducting NISQ devices.
Empirical study of real NISQ order-finding data identifies dominant verified mass fraction as the strongest predictor of whether standard post-processing recovers the true order.
Compact binary-register encoding and divide-and-conquer execution enable high-success variational quantum solutions to small TSP instances with reduced qubit overhead.
citing papers explorer
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The finite-shot help-harm boundary of zero-noise extrapolation
Zero-noise extrapolation has a finite-shot help-harm boundary below which it increases local mean-squared error due to variance penalties outweighing bias reduction.
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Quantum-Classical Hybrid Computation of Electron Transfer in a Cryptochrome Protein via VQE-PDFT and Multiscale Modeling
VQE-PDFT hybrid framework computes electron transfer in ErCRY4 cryptochrome protein with rates aligning to experiments using quantum circuits and QM/MM modeling.
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Certified Finite-Shot Operating Windows for Virtual Distillation and Symmetry Verification
Proves finite-shot mean-squared-error laws for virtual distillation and symmetry verification that define certified operating windows and a selection trichotomy for their comparison.
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A Quantum Multi-Programming Framework to Maximize Quantum Resources for the LUCJ Ansatz
A tailored quantum multi-programming workflow for the LUCJ ansatz enables parallel circuit execution with SQD/ext-SQD post-processing that mitigates cross-talk, yielding ethanol energies within 0.001 kcal/mol of classical HCI references.
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GSC-QEMit: A Telemetry-Driven Hierarchical Forecast-and-Bandit Framework for Adaptive Quantum Error Mitigation
GSC-QEMit adaptively mitigates quantum errors using hierarchical context clustering, Gaussian-process forecasting, and contextual bandits, delivering 9% higher average logical fidelity than unmitigated runs in Qiskit Aer simulations.
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Near-Term Fermionic Simulation with Subspace Noise Tailored Quantum Error Mitigation
SNT merges SV and PEC for subspace-tailored error mitigation in Trotterized FHM simulations, mapping out optimal combinations by hardware quality and shot budget while quantifying when noisy devices could surpass classical methods.
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I-QMapper: Error-Aware Layout Optimization and Device Diagnostics for NISQ Hardware
I-QMapper is a Jupyter-based interactive tool that combines qubit layout construction with real-time and historical calibration analytics for error-aware mapping on superconducting NISQ devices.
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When Noisy Quantum Order Finding Remains Recoverable for Shor's Algorithm
Empirical study of real NISQ order-finding data identifies dominant verified mass fraction as the strongest predictor of whether standard post-processing recovers the true order.
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A Resource-Efficient Variational Quantum Framework for the Traveling Salesman Problem
Compact binary-register encoding and divide-and-conquer execution enable high-success variational quantum solutions to small TSP instances with reduced qubit overhead.
- MCMit: Mid-Circuit Measurement Error Mitigation