Nobel Prize in Physics 2022

The Nobel Prize in Physics 2022 has been awarded to Alain Aspect, John F. Clauser and Anton Zeilinger “for experiments with entangled photons, establishing the violation of Bell inequalities and pioneering quantum information science”. In recognition of this award, Nature Portfolio presents a collection of research, review and opinion articles that celebrates the direct contributions by the awardees and the advances they have inspired.

Nobel Prize in Physics 2022


Nature Portfolio is pleased to acknowledge financial support from IBM Quantum in producing this collection. The sponsor retains sole responsibility for the following message.

IBM Quantum LogoSome of today’s most important problems are too challenging for powerful supercomputers. But a new computing paradigm, quantum computing, is widely expected to tackle some of these problems. IBM is a pioneer in the quantum field. Forty years ago, IBM co-sponsored the Physics of Computation Conference at MIT’s Endicott House, where physicists and computer scientists laid the foundations of modern quantum information science. These thinkers realized the power that quantum mechanics could have for cryptography, simulation, and computing. Since then, much of the field’s development has occurred at IBM’s Yorktown and Almaden labs. Among quantum’s weirdest ideas is quantum entanglement—but it’s also among the most important. Charlie Bennett, recent co-recipient of The Breakthrough Prize in Fundamental Physics, used entanglement to develop the concept quantum teleportation for transmitting quantum information over long distances. Quantum teleportation would neither be possible nor scalable without the recipients of this year’s Nobel Prize in Physics. IBM is grateful to the Nobel Committee for recognizing this important field. We’re eager to make this research open to the broader public for the betterment of society as a whole.

Sponsor selected articles:

Error mitigation extends the computational reach of a noisy quantum processor

Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets

Supervised learning with quantum-enhanced feature spaces

Demonstration of a quantum error detection code using a square lattice of four superconducting qubits

A rigorous and robust quantum speed-up in supervised machine learning