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Bulletin of the American Physical Society

Automatic Calibration and Characterization of Quantum Devices - Experimental Results on NISQ QPUs and Quantum Memory devices

Shai Machnes, Nicolas Wittler, Federico Roy, Anurag Saha Roy, Kevin Pack, Frank K. Wilhelm

Published Mar 5, 2020• 0 citations
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Achieving high-fidelity execution on noisy intermediate-scale quantum (NISQ) hardware requires careful selection of physical qubit layouts, as gate errors, readout errors, and coherence times vary across the device and drift over time. Currently, qubit mapping is performed either through manual inspection of device calibration data or through automated layout pipelines, neither of which provides integrated, interactive layout visualization combined with calibration analytics. In this work, we present the Interactive Quantum Mapper (I-QMapper), a Jupyter-based, open-source tool for noise-aware layout selection, visualization, and analysis on superconducting quantum hardware. I-QMapper offers two operating modes: a general-purpose mode for arbitrary circuits, and a dedicated mode for quantum-chemistry applications, specifically tailored to the Local Unitary Cluster Jastrow (LUCJ) ansatz. Within each mode, a Design panel supports interactive layout construction, while an Error panel provides calibration analytics through four temporal viewing modes (Live, Snapshot, Intraday, and Multi-day range) together with threshold filtering and delta-mode comparison for drift identification. Each layout receives a Layout-Quality Score (LQS) that aggregates the readout and two-qubit gate errors of the layout into a single quality value. Starting from the automatic LUCJ circuit-generation provided by IBM Quantum, we extend it to a multi-programming setting in which multiple circuits are mapped onto a single quantum processing unit (QPU). I-QMapper further supports side-by-side visualization of two quantum backends and layout comparison, and session export for experimental reproducibility. By combining interactive exploration with calibration analytics, I-QMapper aims to support both rapid layout prototyping and informed noise-aware experimental design on NISQ devices.

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As noisy intermediate-scale quantum (NISQ) devices grow in number of qubits, determining good or even adequate parameter configurations for a given application, or for device calibration, becomes a cumbersome task. An evolutionary algorithm is presented here which allows for the automatic tuning of the parameters of any arrangement of coupled qubits, to perform a given task with high fidelity. The algorithm's use is exemplified with the generation of schemes for the distribution of quantum states and the design of multi-qubit gates. The algorithm is demonstrated to converge very rapidly, yielding unforeseeable designs of quantum devices that perform their required tasks with excellent fidelities. Given these promising results, practical scalability, and application versatility, the approach has the potential to become a powerful technique to aid the design and calibration of NISQ devices.

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Abstract As noisy intermediate‐scale quantum (NISQ) devices grow in number of qubits, determining good or even adequate parameter configurations for a given application, or for device calibration, becomes a cumbersome task. An evolutionary algorithm is presented here which allows for the automatic tuning of the parameters of any arrangement of coupled qubits, to perform a given task with high fidelity. The algorithm's use is exemplified with the generation of schemes for the distribution of quantum states and the design of multi‐qubit gates. The algorithm is demonstrated to converge very rapidly, yielding unforeseeable designs of quantum devices that perform their required tasks with excellent fidelities. Given these promising results, practical scalability, and application versatility, the approach has the potential to become a powerful technique to aid the design and calibration of NISQ devices.

arXiv:2009.01706•Advanced Quantum Technologies•Jun 15, 2021•17 citations
Achieving high-fidelity execution on noisy intermediate-scale quantum (NISQ) hardware requires careful selection of physical qubit layouts, as gate errors, readout errors, and coherence times vary across the device and drift over time. Currently, qubit mapping is performed either through manual inspection of device calibration data or through automated layout pipelines, neither of which provides integrated, interactive layout visualization combined with calibration analytics. In this work, we present the Interactive Quantum Mapper (I-QMapper), a Jupyter-based, open-source tool for noise-aware layout selection, visualization, and analysis on superconducting quantum hardware. I-QMapper offers two operating modes: a general-purpose mode for arbitrary circuits, and a dedicated mode for quantum-chemistry applications, specifically tailored to the Local Unitary Cluster Jastrow (LUCJ) ansatz. Within each mode, a Design panel supports interactive layout construction, while an Error panel provides calibration analytics through four temporal viewing modes (Live, Snapshot, Intraday, and Multi-day range) together with threshold filtering and delta-mode comparison for drift identification. Each layout receives a Layout-Quality Score (LQS) that aggregates the readout and two-qubit gate errors of the layout into a single quality value. Starting from the automatic LUCJ circuit-generation provided by IBM Quantum, we extend it to a multi-programming setting in which multiple circuits are mapped onto a single quantum processing unit (QPU). I-QMapper further supports side-by-side visualization of two quantum backends and layout comparison, and session export for experimental reproducibility. By combining interactive exploration with calibration analytics, I-QMapper aims to support both rapid layout prototyping and informed noise-aware experimental design on NISQ devices.
As noisy intermediate-scale quantum (NISQ) devices grow in number of qubits, determining good or even adequate parameter configurations for a given application, or for device calibration, becomes a cumbersome task. An evolutionary algorithm is presented here which allows for the automatic tuning of the parameters of any arrangement of coupled qubits, to perform a given task with high fidelity. The algorithm's use is exemplified with the generation of schemes for the distribution of quantum states and the design of multi-qubit gates. The algorithm is demonstrated to converge very rapidly, yielding unforeseeable designs of quantum devices that perform their required tasks with excellent fidelities. Given these promising results, practical scalability, and application versatility, the approach has the potential to become a powerful technique to aid the design and calibration of NISQ devices.
Abstract As noisy intermediate‐scale quantum (NISQ) devices grow in number of qubits, determining good or even adequate parameter configurations for a given application, or for device calibration, becomes a cumbersome task. An evolutionary algorithm is presented here which allows for the automatic tuning of the parameters of any arrangement of coupled qubits, to perform a given task with high fidelity. The algorithm's use is exemplified with the generation of schemes for the distribution of quantum states and the design of multi‐qubit gates. The algorithm is demonstrated to converge very rapidly, yielding unforeseeable designs of quantum devices that perform their required tasks with excellent fidelities. Given these promising results, practical scalability, and application versatility, the approach has the potential to become a powerful technique to aid the design and calibration of NISQ devices.