A Framework for Quantum Advantage

TL;DR

The paper defines a concrete, platform-agnostic notion of quantum advantage anchored in verifiable output correctness and demonstrable quantum separation, and argues that progress will come through a sequence of robust, reproducible demonstrations evaluated against evolving classical methods. It analyzes three promising problem families—sampling, variational, and expectation-value estimation—showing how verifiability and error mitigation shape near-term gains. It then outlines the essential elements for realized advantage: reliable circuit execution, quantum-centric HPC infrastructure, and performant hardware, with detailed considerations for superconducting qubits and neutral-atom platforms. Finally, it calls for coordinated benchmarks, open data, and collaborative benchmarking ecosystems to credibly and constructively advance the field toward practical quantum advantage in chemistry, materials science, and optimization.

Abstract

As quantum computing approaches the threshold where certain tasks demonstrably outpace their classical machines, the need for a precise, clear, consensus-driven definition of quantum advantage becomes essential. Rapid progress in the field has blurred this term across companies, architectures, and application domains. Here, we aim to articulate an operational definition for quantum advantage that is both platform-agnostic and empirically verifiable. Building on this framework, we highlight the algorithmic families most likely to achieve early advantage. Finally, we outline our vision for the near future, in which quantum computers enhance existing high-performance computing platforms, enabling new frontiers in chemistry, materials discovery, optimization, and beyond.