Limitations of Fault-Tolerant Quantum Linear System Solvers for Quantum Power Flow
Parikshit Pareek, Abhijith Jayakumar, Carleton Coffrin, and Sidhant Misra

TL;DR
This paper critically evaluates the potential for quantum algorithms to outperform classical methods in power flow problems, revealing fundamental complexity limitations that challenge claims of exponential speedup.
Contribution
It provides a rigorous complexity analysis of quantum power flow algorithms, demonstrating their limitations compared to classical algorithms and clarifying conditions for potential quantum advantage.
Findings
HHL-based quantum methods have higher runtime complexity than classical algorithms for DCPF and FDLF.
Quantum advantage requires narrow condition number ranges and specific readout conditions.
The analysis applies to any quantum linear system solver with known performance bounds.
Abstract
Quantum computers hold promise for solving problems intractable for classical computers, especially those with high time or space complexity. Practical quantum advantage can be said to exist for such problems when the end-to-end time for solving such a problem using a classical algorithm exceeds that required by a quantum algorithm. Reducing the power flow (PF) problem into a linear system of equations allows for the formulation of quantum PF (QPF) algorithms, which are based on solving methods for quantum linear systems such as the Harrow-Hassidim-Lloyd (HHL) algorithm. Speedup from using QPF algorithms is often claimed to be exponential when compared to classical PF solved by state-of-the-art algorithms. We investigate the potential for practical quantum advantage in solving QPF compared to classical methods on gate-based quantum computers. Notably, this paper does not present a new…
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Taxonomy
TopicsElectrochemical Analysis and Applications
