Milestones of research activity in quantum computing: EPS grand challenges

TL;DR

Since 2017, quantum computing has experienced a significant shift due to increased funding and integration with machine learning, with future milestones expected as practical quantum applications emerge by 2050.

Contribution

The paper highlights key milestones leading to the 2017 inflection point and discusses future prospects of quantum computing becoming mainstream by 2050.

Findings

Increased funding and interest since 2017.

Integration of machine learning techniques into quantum computing.

Expected widespread practical quantum applications by 2050.

Abstract

We argue that quantum computing underwent an inflection point circa 2017. Long promised funding materialised which prompted public and private investments around the world. Techniques from machine learning suddenly influenced central aspects of the field. On one hand, machine learning was used to emulate quantum systems. On the other hand, quantum algorithms became viewed as a new type of machine learning model (creating the new model of {\it variational} quantum computation). Here we sketch some milestones which have lead to this inflection point. We argue that the next inflection point would occur around when practical problems will be first solved by quantum computers. We anticipate that by 2050 this would have become commonplace, were the world would still be adjusting to the possibilities brought by quantum computers.