A Case for Variability-Aware Policies for NISQ-Era Quantum Computers
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.
Swamit S. Tannu Moinuddin K. Qureshi