In a lab in Illinois, physicists captured and tamed a tiny particle of antimatter in a trap with invisible walls. By studying how the positron behaved, the researchers may soon have a chance to break our best mathematical model of physical reality.

The positron is the antimatter counterpart of the electron, which means the two particles have the same mass but the opposite electric charge. Unlike electrons, however, positrons are rare and typically exist for a tiny fraction of a second because the moment one meets one of the super-abundant electrons in our universe, the pair annihilate. This makes positrons difficult to study.

at Northwestern University in Illinois and his colleagues have now found a way to trap a positron and keep it around for months on end. By analysing data collected while the positron was trapped, they plan to precisely measure the antiparticle’s properties and consequently investigate one of the biggest problems with the standard model of particle physics.

The researchers obtained the positron from a radioactive isotope of sodium that emits one whenever it decays. Such positrons are very fast and hard to control, so they placed the sodium into a special refrigerator to lower its temperature and energy, and slow down the antiparticles.

They slowed them further by directing the positrons through a tungsten crystal. While some positrons were annihilated as they travelled through the crystal, some came through unscathed. They were then directed into a refrigerated chamber that was empty of all other particles. Here, electronic components generated electromagnetic fields that confined a single incoming positron, serving as invisible walls that trapped the particle.

The researchers then pushed the positron into its lowest possible energy state, which Gabrielse says allowed them to keep the otherwise elusive antiparticle trapped for months. They could also push it into the next lowest energy state with controlled bursts of microwaves.

Subscriber-only newsletter

Sign up to Editor’s Highlights

Sign up to newsletter

“It’s a real kick to stand in my lab and watch a positron making transitions – ‘quantum jumps’ we call them – between its lowest energy states. How much more fundamental, how much neater can it get?” he says.

“Trapping an antiparticle is extremely difficult,” says at Japanese scientific institute RIKEN, particularly since any stray particle, burst of light or tiny vibration could disturb it and the trap had to be kept just tenths of a degree above the coldest temperature possible.

The payoff for trapping and controlling the positron despite these experimental challenges could be remarkable. “This has the potential to become one of the most precise measurements of a fundamental constant in physics,” says Ulmer.

Six ways we could finally find new physics beyond the standard model

Leading physicists explain how they think we will discover the new particles or forces that would complete one of science’s greatest unfinished masterpieces

Specifically, Gabrielse and his colleagues want to measure the positron’s magnetic moment, which is a number that quantifies its response to magnetic fields. The researchers have previously made the most precise ever measurement of the electron’s magnetic moment, and comparing this figure with the one for the antiparticle would enable them to compare the properties of matter and antimatter with unprecedented precision.

The standard model predicts they should have identical magnetic moments, but this prediction underscores a notable shortcoming of this theory. The problem is that if matter and antimatter are so alike, then they should have been created in equal amounts and fully annihilated as the universe began, leaving nothing. “The standard model seems to be inconsistent, or at least significantly incomplete, with basic features of the universe, like why we have a universe at all,” says Gabrielse.

Uncovering a difference between the electron and positron could hint at some currently unknown mechanism that resulted in our matter-filled universe. If all goes according to plan, the researchers aim to have data that will shed light on this within the year.

Making quantum computers error-proof is one of the biggest challenges currently facing the technology. Researchers at Google Quantum AI have now demonstrated one way to do so more efficiently. Their work suggests the smaller quantum computers that will be available in the next few years could be more impactful than expected.

Quantum computers can run mathematical operations, analogous to addition or multiplication, that conventional computers cannot. This makes them suitable for solving some problems that had previously been considered unsolvable, such as those that underpin cryptography.

Most important among the quantum operations the computers run are “non-Clifford gates”, which are the key ingredients for algorithms that transcend conventional computation.

But there is a problem. Quantum computers are very error-prone, and their building blocks, called qubits, must be encoded into special groups, or “logical qubits”, before they can execute operations reliably. Executing non-Clifford gates in an error-corrected way requires large numbers of qubits, which means having to build very large quantum computers – a formidable engineering challenge.

Now, at Google Quantum AI and her colleagues have used the firm’s Willow quantum computer to show that the error-correction process can be made more efficient. Their new technique ultimately reduced Willow’s errors 40 times.

At the centre of their advance is the idea of a “magic state”, which is a special quantum state that qubits must assume before the quantum computer can run error-corrected non-Clifford operations. Creating these states had, so far, been a real bottleneck for quantum computing, says Rosenfeld. “It eats up a lot of qubits and a lot of time,” she says.

Free newsletter

Sign up to Professor Hannah Fry’s column

Sign up to newsletter

In 2024, her colleagues at Google Quantum AI proposed a more efficient method for creating magic states called “magic state cultivation”. Here, instead of many imperfect qubits being repeatedly combined and manipulated into a magic state that is then put towards running an error-corrected operation, the magic state is “grown” within a smaller patch of qubits.

The Google researchers showed that magic state cultivation could, in theory, enable quantum computers to run consequential programs with just one-tenth the number of qubits we had expected they would need. The new experiment by Rosenfeld and her colleagues proves that magic state cultivation works in practice.

This is not the first time that new methods for making magic states have lowered a quantum computer’s error rates. Advances in creating magic states and error-correcting non-Clifford gates have also been achieved in . Willow’s qubits, which are based on tiny superconducting circuits, achieved error rates similar to those past experiments, but Rosenfeld says that they work more quickly, potentially reducing the quantum computer’s overall runtime.

Atom-based quantum computers are catching up in the race to usefulness

A quantum computer made from extremely cold atoms can correct its own errors during long computations, an important prerequisite for becoming truly useful

“This is an impressive demonstration of a promising recent idea pioneered by Google,” says at the University of California, Davis. “It’s an approach that can make fault-tolerant quantum computing substantially cheaper.” The new work demonstrates one of the building blocks necessary for universal quantum computing and could be a “gamechanger” in terms of building intermediately sized quantum computers with hundreds of logical qubits, says at ETH Zurich in Switzerland.

at Imperial College London says that while this experiment is a significant step forward, Willow’s errors will need to be reduced further before it can tackle truly useful problems. Additionally, Kim says that in the experiment, Willow generated good magic states only for a fraction of its computational runs: only 8 per cent of Willow’s computations produced high-quality magic states that could then be put into further use.

Rosenfeld says that this percentage ought to increase as she and her colleagues refine the technique and improve Willow’s hardware. It is, in this case, also affected by a very careful benchmarking technique that the team used, which may not be used in future applications, she says. “This is the first demonstration that the concepts work. We’re not done.”