Noisy intermediate-scale quantum algorithms

TLDR

Noisy quantum computers can, in principle, perform reliable computations, but current noise levels limit scalability, though moderate‑complexity tasks remain feasible. This review surveys the capabilities of the noisy intermediate‑scale quantum era. Topics covered include simulations of many‑body physics and chemistry, combinatorial optimization, and machine learning. The NISQ era has introduced new programming paradigms that will underpin future, more powerful quantum computers.

Abstract

Noisy quantum computers can in principle perform reliable quantum computations, but truly scalable systems require noise levels lower than are presently achieved. Still, moderate-complexity computations can be performed. This review discusses what is possible in this ``noisy intermediate scale'' quantum (NISQ) era. Topic areas include the simulation of many-body physics and chemistry, combinatorial optimization, and machine learning. It is evident that the NISQ era has produced new paradigms for programming that will be built upon as quantum computers are further perfected.