The team observed two merging galaxies and discovered that the energy from a quasar is actively transforming the gas within its companion galaxy, thereby dictating whether new stars can form.

Exotic antimatter spotted in heavy-ion collisions at the LHC

Bengaluru
13 May 2025
Graphical representation of collisions at LHC

The Large Hadron Collider (LHC) at CERN, near Geneva, is one of the largest and most expensive experiments undertaken by humanity. It's a 27-kilometer ring of superconducting magnets that accelerates particles, like protons or lead ions, to near the speed of light and collides them. The collisions are designed to recreate the extreme conditions kike those that existed just moments after the Big Bang, creating a fleeting state of matter called quark-gluon plasma. This super-hot, dense soup of fundamental particles quickly cools and decomposes into the ordinary matter we know.

Occasionally, however, the quark-gluon plasma can produce something much more exotic: hypernuclei and their antimatter counterparts, antihypernuclei. These are like regular atomic nuclei but with an added ingredient – a strange particle called a hyperon. Finding and studying these rare objects gives physicists unique insights into the fundamental forces that hold matter together and can even help us understand the mysterious interiors of neutron stars or the state of the early universe.

In a significant new result from the A Large Ion Collider Experiment (ALICE) collaboration at the LHC, which includes scientists from all over the world, including India, has announced the first evidence for the antihyperhelium-4 nucleus, the antimatter version of a hypernucleus of helium. It consists of an antiproton, two antineutrons, and an anti-Lambda hyperon, all bound together. Antimatter nuclei are much harder to produce and detect than their matter counterparts. 

Additionally, the ALICE team also made the very first measurements at the LHC of the production rates and masses for both the matter and antimatter versions of the hypernuclei with a total of four particles (A=4), specifically hyperhydrogen-4 and hyperhelium-4 and their antiparticles.

The ALICE is one of nine detectors at the LHC. It is like a giant, multi-layered camera designed to detect and track every particle flying out from the collision point. Hypernuclei and antihypernuclei are unstable particles, meaning they don't last long. They decay into other, more common particles after a tiny fraction of a second. Crucially, they travel a short distance from the collision point before they decay. This means their decay happens at a displaced vertex, slightly away from where the lead nuclei initially crashed. The ALICE detector is excellent at spotting these displaced decay points and tracing the paths of the decay products. This allows it to detect these incredibly rare particles amidst the thousands of other particles produced in a heavy-ion collision.

By measuring the energy and momentum of these decay products, scientists can calculate a value called the invariant mass, which is like a unique fingerprint for a specific particle. When the invariant mass for all the potential candidates are plotted on a graph, the presence of hypernucleus or antihypernucleus shows as specific peaks. To help sort through the massive amount of data and pick out the real signals from the background noise, the ALICE team used sophisticated machine learning techniques, specifically a gradient-boosted decision tree. They trained this program to recognise the tell-tale signs of a hypernucleus decay based on properties like the distance of the decay from the collision point and the characteristics of the decay particles.

The measurements were made using data from central lead-lead collisions collected in 2018. The team measured the production rates (or yields) of the A=4 hypernuclei and antihypernuclei. They found that the average yields of the matter and antimatter versions were minimal, on the order of a few parts per million of the total particles produced.

They also measured the ratio of antihypernuclei to hypernuclei. This ratio is sensitive to the baryochemical potential, which tells you about the balance between matter and antimatter in the hot, dense matter created in the collision. At the LHC, this potential is expected to be very close to zero, meaning equal amounts of matter and antimatter are produced. The measured ratios for both A=4 hypernuclei were consistent with unity (around 1), which fits this expectation perfectly.

The team also measured the masses of the hyperhydrogen-4 and hyperhelium-4 and their antiparticles. These measurements were compatible with previous world-average values, though the statistical uncertainties were still quite significant compared to the systematic uncertainties. Precise mass measurements help constrain theoretical models that describe the forces between hyperons and nucleons inside these strange nuclei. These forces are not as well understood as those between protons and neutrons. Differences in mass and excitation energies between hypernuclei and antihypernuclei can also explain charge-symmetry breaking in these interactions. The experimental observations and calculations help us ring-fence our theoretical models with stricter constraints and verify them.

While the precision of these first measurements is limited by the number of A=4 hypernuclei and antihypernuclei found in the 2018 data sample, the ALICE detector's ability to make such measurements is evident. Future runs of the LHC will collect much larger datasets, allowing for even more precise measurements of the production rates, masses, and other properties of these exotic particles.

These future results will be crucial for refining our theoretical understanding of the strong force in the presence of strange quarks, improving models of neutron stars (which might contain hyperons), and shedding more light on the conditions of the early universe. Finding and studying these rare, strange forms of matter and antimatter pushes the boundaries of our knowledge about the fundamental building blocks of the cosmos.


This research article was written with the help of generative AI and edited by an editor at Research Matters.


 

English