Speaker
Description
Accurate modeling of the underlying event (UE) in heavy-ion collisions poses a significant challenge, particularly for analyses involving hard probes. No existing Monte Carlo (MC) simulation can reproduce the complex underlying physics. To address this, the ATLAS Collaboration developed an innovative technique that overlays simulated signal events onto real minimum-bias data recorded by the detector (Data Overlay). This approach ensures that both the UE and detector response are represented with high fidelity in the reconstructed events. This strategy reduces the computational cost of MC production by limiting full detector simulations to relatively simple signals.
For the Data Overlay method, a dedicated dataset is collected at a rate exceeding 1,000 events per period during which detector conditions remain stable. The data are preprocessed such that detector readouts and reconstructed vertex positions are available on an event-by-event basis. In the Data Overlay procedure, the simulated signal vertex is aligned with the corresponding vertex in data, and the combined event is processed through the standard ATLAS reconstruction chain.
This technique has been successfully applied in Run 2 ATLAS heavy-ion analyses but has now been modernized for use with the heavy-ion Run 3 dataset. An extensive validation program has been carried out, and the results of this study will be presented together with the technical details of this approach.
The first application on light-ions data taken in the summer of 2025 is envisaged.