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Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers by Murali, Prakash; Baker, Jonathan M.; Abhari, Ali Javadi; Chong, Frederic T.; Martonosi, Margaret is a scholarly article available to read on EtoBox.

What is Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers about?

A massive gap exists between current quantum computing (QC) prototypes, and the size and scale required for many proposed QC algorithms. Current QC implementations are prone to noise and variability which affect their reliability, and yet with less than 80 quantum bits (qubits) total, they are too resource-constrained to implement error correction. The term Noisy Intermediate-Scale Quantum (NISQ) refers to these current and near-term systems of 1000 qubits or less. Given NISQ's severe resource constraints, low reliability, and high variability in physical characteristics such as coherence time or error rates, it is of pressing importance to map computations onto them in ways that use resources efficiently and maximize the likelihood of successful runs. This paper proposes and evaluates backend compiler approaches to map and optimize high-level QC programs to execute with high reliability on NISQ systems with diverse hardware characteristics. Our techniques all start from an LLVM intermediate representation of the quantum program (such as would be generated from high-level QC languages like Scaffold) and generate QC executables runnable on the IBM Q public QC machine. We then use th

Author

Murali, Prakash; Baker, Jonathan M.; Abhari, Ali Javadi; Chong, Frederic T.; Martonosi, Margaret

Published

2019

Language

EN