Not All Qubits Are Created Equal: A Case for Variability-Aware Policies for NISQ-Era Quantum Computers

By Swamit S. Tannu, Moinuddin K. Qureshi. International Conference on Architectural Support for Programming Languages and Operating Systems, 2018

446 citations recorded by the source corpus.

Existing and near-term quantum computers are not yet large enough to support fault-tolerance. Such systems with few tens to few hundreds of qubits are termed as Noisy Intermediate Scale Quantum computers (NISQ), and these systems can provide benefits for a class of quantum algorithms. In this paper, we study the problems of Qubit-Allocation (mapping of program qubits to machine qubits) and Qubit-Movement (routing qubits from one location to another for entanglement). We observe that there can be variation in the error rates of different qubits and links, which can impact the decisions for qubit movement and qubit allocation. We analyze publicly available characterization data for the IBM-Q20 to quantify the variation and show that there is indeed significant variability in the error rates of the qubits and the links connecting them. We show that the device variability has a significant impact on the overall system reliability. To exploit the variability in error rate, we propose Variation-Aware Qubit Movement (VQM) and Variation-Aware Qubit Allocation (VQA), policies that optimize the movement and allocation of qubits to avoid the weaker qubits and links, and guide more operations towards the stronger qubits and links. Our evaluations, with a simulation-based model of IBM-Q20, show that Variation-Aware policies can improve the system reliability by up to 1.7x. We also evaluate our policies on the IBM-Q5 machine and demonstrate that our proposal significantly improves the reliability of real systems (up to 1.9X).

Subfields: Artificial Intelligence, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/d5a0b04e42b3f8aafe3fcbfeaccb2350d096969f

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Citations in the corpus

Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers (2019, methodology): “[66, 68] observed the usefulness of calibration data.”
t|ket⟩: a retargetable compiler for NISQ devices (2020, background): “Some solutions consider device noise [36, 81] when routing, using gate fidelity information to produce a routed circuit with best execution fidelity.”
QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits (2021, background): “Noise-adaptive qubit mapping [34], [48], [58] aims to find the best mapping from logical qubits to physical qubits, which minimizes the gate error and SWAP insertion overhead.”
Software Mitigation of Crosstalk on Noisy Intermediate-Scale Quantum Computers (2020, methodology): “ponential rate as time passes. However, in this work, we show that program duration can be traded off to avoid crosstalk, and thus improve the overall reliability of application executions. Recently, [43, 44, 47, 58] used hardware characterization data to improve the quality of compilation. They imp”