The Quantum Tortoise and the Classical Hare: A simple framework for understanding which problems quantum computing will accelerate (and which it will not)
Sukwoong Choi, William S. Moses, Neil Thompson

TL;DR
This paper introduces a simple framework to predict which problems will benefit from quantum computing by comparing quantum and classical strengths, revealing that many small to medium problems may not see advantages, while larger or highly algorithmic problems will.
Contribution
The paper presents a novel race-based framework for understanding quantum advantage, combining intuition and quantitative analysis to identify problem types that benefit from quantum computing.
Findings
Many small to medium problems will not benefit from quantum computing.
Larger problems or those with significant algorithmic gains will benefit.
Quantum advantage is determined by the dominance of speed or algorithmic efficiency.
Abstract
Quantum computing promises transformational gains for solving some problems, but little to none for others. For anyone hoping to use quantum computers now or in the future, it is important to know which problems will benefit. In this paper, we introduce a framework for answering this question both intuitively and quantitatively. The underlying structure of the framework is a race between quantum and classical computers, where their relative strengths determine when each wins. While classical computers operate faster, quantum computers can sometimes run more efficient algorithms. Whether the speed advantage or the algorithmic advantage dominates determines whether a problem will benefit from quantum computing or not. Our analysis reveals that many problems, particularly those of small to moderate size that can be important for typical businesses, will not benefit from quantum computing.…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Blockchain Technology Applications and Security · Cloud Computing and Resource Management
