Simulating and mitigating crosstalk

Abstract

We describe an efficient and scalable framework for modeling crosstalk effects on quantum information processors. By applying optimal control techniques, we show how to tuneup arbitrary high-fidelity parallel operations on systems with substantial local and nonlocal crosstalk. Simulations show drastically lower error rates for a 2D square array of 100 superconducting transmon qubits. These results suggest that rather than striving to engineer away undesirable interactions during fabrication, we can largely mitigate their effects through careful characterization and control optimization.

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Cited by in corpus (19)

• Suppression of crosstalk in superconducting qubits using dynamical decoupling
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• Scalable High-Performance Fluxonium Quantum Processor
• Natural quantum reservoir computing for temporal information processing
• Calibration of flux crosstalk in large-scale flux-tunable superconducting quantum circuits
• Pulse variational quantum eigensolver on cross-resonance based hardware
• Optimal control of families of quantum gates
• Classification of four-qubit entangled states via Machine Learning
• Control and mitigation of microwave crosstalk effect with superconducting qubits
• Filtering crosstalk from bath non-Markovianity via spacetime classical shadows
• Control of the $ZZ$ coupling between Kerr-cat qubits via transmon couplers
• A Review of Design Concerns in Superconducting Quantum Circuits
• Classical-Quantum Noise Mitigation for NISQ Hardware
• Estimation of correlations and non-separability in quantum channels via unitarity benchmarking
• Quantum optimal control in quantum technologies. Strategic report on current status, visions and goals for research in Europe
• Optimized Noise Suppression for Quantum Circuits
• Estimating Coherent Contributions to the Error Profile Using Cycle Error Reconstruction
• Implementing High-fidelity Two-Qubit Gates in Superconducting Coupler Architecture with Novel Parameter Regions
• Tomography-assisted noisy quantum circuit simulator using matrix product density operators