A D-Wave hybrid solver is applied to post-disaster road restoration on a 24-zone Sioux Falls network, with claimed speed and equity advantages that the paper's own equations do not support.
Reconsider HHL algorithm and its related quantum machine learning algorithms
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abstract
HHL quantum algorithm to solve linear systems is one of the most important subroutines in many quantum machine learning algorithms. In this work, we present and analyze several other caveats in HHL algorithm, which have been ignored in the past. Their influences on the efficiency, accuracy and practicability of HHL algorithm and several related quantum machine learning algorithms will be discussed. We also found that these caveats affect HHL algorithm much deeper than the already noticed caveats. In order to obtain more practical quantum machine learning algorithms with less assumptions based on HHL algorithm, we should pay more attention to these caveats.
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Q-RESTORE: Quantum-Driven Framework for Resilient and Equitable Transportation Network Restoration
A D-Wave hybrid solver is applied to post-disaster road restoration on a 24-zone Sioux Falls network, with claimed speed and equity advantages that the paper's own equations do not support.