A crowd pours out of a narrow passage. Some run in a tight group in one direction, like jetty events in nuclear collisions. Others scatter evenly in all directions, like isotropic events. The shape of particle debris, which physicists call transverse sphericity, turned out to be a handy tool for hunting a rare phenomenon.
In collisions of lead nuclei at enormous energies, the chiral magnetic effect can arise: an ultrastrong magnetic field momentarily separates positive and negative charges along its axis. This effect is predicted by theory, but it's hard to pick out from background processes — the usual collective flow of particles and decays of short-lived resonances (particles that quickly decay into others). Previously, events were classified by the flow vector, but that method suffers from circularity: the classifier itself is contaminated by the same background it's supposed to suppress.
The authors simulated lead-nucleus collisions at an energy of 5.02 TeV using the AMPT transport model, including a realistic implementation of the chiral magnetic effect. They split events into jetty and isotropic based on transverse sphericity and compared the signal in the two classes. It turned out that in isotropic events the background contribution from elliptic flow and resonance decays is significantly weaker, and the signal-to-background ratio is higher. This means that selecting isotropic events is a cleaner way to search for the chiral magnetic effect.
This approach complements existing methods and could help confirm or refute the existence of the chiral magnetic effect in experiments. If the effect is reliably isolated, it would be an important step toward understanding the properties of the super-hot matter born in relativistic nuclear collisions.
as written by the authors arXiv:2604.05654
We present the first study of the Chiral Magnetic Effect (CME) using transverse spherocity as an event-shape classifier in Pb+Pb collisions at $$\sqrt{s_{NN}} = 5.02$$ TeV, simulated with the A Multi-Phase Transport (AMPT) model with a realistic CME implementation. Transverse spherocity separates events into jetty and isotropic topologies based on the geometric distribution of transverse momentum. Unlike traditional event shape engineering methods, which use the flow vector as an event classifier that is itself contaminated by the very backgrounds it is intended to suppress, spherocity provides a cleaner, geometry-driven classification that avoids this circular limitation. CME inclusion shifts the spherocity distribution toward more isotropic events, confirming its sensitivity to CME-induced charge separation. The charge-dependent azimuthal correlator $$\Delta\gamma$$ and correlated background coupled with elliptic flow are consistently higher in jetty events. The scaled ratio $$\Delta\gamma/v_2$$ shows enhanced values for isotropic events, confirming effective background suppression after elliptic flow scaling. Our results demonstrate that isotropic event selection via transverse spherocity provides a cleaner and more reliable environment for CME searches by simultaneously suppressing flow-driven and resonance-decay backgrounds, making it a powerful complementary method to existing flow-vector-based methods.
The magnetic field in lead-nucleus collisions at the Large Hadron Collider can reach $10^{18}$ gauss, a billion times stronger than the most powerful magnets on Earth, but it lasts only a tiny fraction of a second.