The Grand Challenge of Quantum Applications

TL;DR

This paper discusses the pathways, challenges, and framework for developing practical quantum computing applications, emphasizing the importance of identifying real-world problems and the role of AI in advancing the field.

Contribution

It introduces a five-stage framework for quantum application development and highlights key under-resourced challenges like problem identification and real-world connection.

Findings

Critical obstacles in quantum application development identified

A five-stage framework proposed for progressing from theory to practice

Emphasis on problem selection and real-world relevance as key challenges

Abstract

This perspective outlines promising pathways and critical obstacles on the road to developing useful quantum computing applications, drawing on insights from the Google Quantum AI team. We propose a five-stage framework for this process, spanning from theoretical explorations of quantum advantage to the practicalities of compilation and resource estimation. For each stage, we discuss key trends, milestones, and inherent scientific and sociological impediments. We argue that two central stages -- identifying concrete problem instances expected to exhibit quantum advantage, and connecting such problems to real-world use cases -- represent essential and currently under-resourced challenges. Throughout, we touch upon related topics, including the promise of generative artificial intelligence for aspects of this research, criteria for compelling demonstrations of quantum advantage, and the future of compilation as we enter the era of early fault-tolerant quantum computing.