[Paper Review] A Case for Variability-Aware Policies for NISQ-Era Quantum Computers

Swamit Tannu, Moinuddin K. Qureshi|arXiv (Cornell University)|May 25, 2018

Quantum Computing Algorithms and ArchitectureComputer Science26 references49 citations

TL;DR

The paper studies variability in qubit and link error rates on NISQ devices and proposes variation-aware qubit movement and allocation policies that improve reliability by avoiding weaker qubits/links.

ABSTRACT

Recently, IBM, Google, and Intel showcased quantum computers ranging from 49 to 72 qubits. While these systems represent a significant milestone in the advancement of quantum computing, existing and near-term quantum computers are not yet large enough to fully support quantum error-correction. 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 to perform entanglement). We observe that there exists variation in the error rates of different qubits and links, which can have an impact on the decisions for qubit movement and qubit allocation. We analyze characterization data for the IBM-Q20 quantum computer gathered over 52 days to understand and quantify the variation in the error-rates and find that there is indeed significant variability in the error rates of the qubits and the links connecting them. We define reliability metrics for NISQ computers and show that the device variability has the substantial 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. We show that our Variation-Aware policies improve the reliability of the NISQ system up to 2.5x.

Motivation & Objective

• Motivate the need to consider variability in qubit error rates for NISQ-era quantum computing.
• Characterize error-rate variation across qubits and links using IBM-Q20 data collected over 52 days.
• Define reliability metrics for NISQ devices and quantify how variability impacts system reliability.
• Propose and evaluate variation-aware policies for qubit movement and qubit allocation to improve reliability.

Proposed method

• Analyze 52 days of IBM-Q20 characterization data to quantify variation in qubit and link error rates.
• Define reliability metrics to assess impact of device variability on NISQ systems.
• Develop Variation-Aware Qubit Movement (VQM) policy to avoid weaker qubits/links during entanglement operations.
• Develop Variation-Aware Qubit Allocation (VQA) policy to map program qubits to stronger qubits/links.
• Evaluate policies by comparing reliability improvements, reporting up to 2.5x gains.

Experimental results

Research questions

• RQ1 How variable are error rates across qubits and links in a real IBM-Q20 device over time?
• RQ2 Can movement and allocation policies that account for this variability improve NISQ reliability?
• RQ3 What is the potential reliability gain from applying variation-aware strategies compared to baseline policies?

Key findings

• There is significant variability in error rates among qubits and links on IBM-Q20 over 52 days.
• Device variability has a substantial impact on overall system reliability.
• Variation-aware qubit movement (VQM) and variation-aware qubit allocation (VQA) improve reliability, achieving up to 2.5x improvements.