News & Comment

45 years after being coined, the quantum Zeno effect still holds surprises.

The first confirmed discovery of a planet outside our Solar System was announced 30 years ago. Since then, technical developments have enabled detection of thousands of exoplanets.

Breakfast is serious business — and involves a lot of physics. This month, we share with you our favourite breakfast-related physics papers.

Gregory White discusses process tensor tomography, a method to characterize non-Markovian dynamics, which can find applications in quantum technologies and the study of open quantum systems.

L. A. P. Ardila highlights the importance of quantum Monte Carlo methods for the study of polarons in ultracold quantum gases.

Hillel Sanhedrai explains how it can be possible to revive a failed network functionality by controlling the activity of just a single node.

A paper in Physical Review X reports on the role of spatial coherence in branched flow patterns in light.

Wigner crystals — ordered arrays of electrons — have been recently found in various 2D materials, but the first studies of these crystals in 2D electron systems (2DESs) date back from the 1980s. Mansour Shayegan gives a brief history of Wigner crystals and highlights future prospects.

A paper in Science Advances uses a laboratory setup to simulate galaxy cluster cores and explain the suppression of heat conduction from the plasma core.

Two recent studies report more stringent constraints on dark matter from experiments with atoms and ions that make use of techniques and devices developed for quantum technologies.

Do you have a good idea for a Review article? Here is a brief guide on how to pitch ideas to editors.

100 years ago, Otto Stern and Walther Gerlach demonstrated that silver atoms have a quantized magnetic moment, as predicted from the Bohr–Sommerfeld model of the atom. But the correct interpretation of the result proved to be far more subtle — and revolutionary.

A paper in Physical Review Letters reports how twisting yarn makes it stronger.

A paper in Nature shows how reinforcement learning can solve the problem of optimizing the magnetic field in a tokamak to create a variety of plasma configurations, including ones that haven’t been achieved before.

Francis Russell reflects on the history of nonlinear excitations.

Quantum machine learning may provide powerful tools for data analysis in high-energy physics. Sau Lan Wu and Shinjae Yoo describe how the potential of these tools is starting to be tested and what has been understood thus far.

Machine learning methods relying on synthetic data are starting to be used in mathematics and theoretical physics. Michael R. Douglas discusses recent advances and ponders on the impact these methods will have in science.

As a field moves from fundamental science to industrial applications, standards for reproducibility also evolve. We commit to provide a platform for this ongoing conversation.

Two recent studies look for magnetic monopoles in very different, and rather exotic, places: in heavy ion collisions at the Large Hadron Collider and the IceCube neutrino detector in Antarctica.

Established almost 100 years ago, Bell Labs made a great contribution to advancing both fundamental science and technology. Was that the result of a unique set of circumstances or is there a reproducible recipe for success?