Probing the chiral magnetic effect via transverse spherocity event classification in relativistic heavy-ion collisions

TL;DR

This study introduces transverse spherocity as a novel event-shape classifier in heavy-ion collisions, effectively enhancing the detection of the Chiral Magnetic Effect by reducing background interference.

Contribution

It demonstrates that transverse spherocity provides a cleaner, geometry-driven classification method that improves CME signal extraction compared to traditional flow vector techniques.

Findings

CME shifts spherocity distribution toward more isotropic events.

Charge-dependent correlators are higher in jetty events, but scaled ratios favor isotropic events.

Isotropic event selection suppresses flow-driven and resonance backgrounds.

Abstract

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.