Speaker
Description
Resonance measurements in high-energy nuclear collisions require reliable extraction of signal yields in the presence of large combinatorial backgrounds (e.g. Event Mixing, Like-Sign). Both the background estimation technique and the invariant-mass fitting strategy can significantly influence the stability of the extracted signal and contribute to systematic uncertainties across a broad transverse-momentum range.
This poster presents a comparative study of commonly used combinatorial background subtraction methods together with different invariant-mass fitting approaches, including a direct comparison of implementations in the ROOT and RooFit frameworks. The impact of these methodological choices on fit stability, convergence behavior, parameter correlations, and relative variations of the extracted resonance signal is evaluated as a function of transverse momentum.
The analysis focuses on methodological robustness rather than final physics results, providing guidance for systematic uncertainty estimation in resonance analyses performed with the ALICE detector. The presented techniques are broadly applicable to studies using modern collider detectors and are particularly relevant for high-momentum hadron and correlation measurements in environments with large combinatorial backgrounds.
| Is this an experimental talk? | Yes |
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| Is this on behalf of a collaboration? | Yes |
| Which collaboration? | ALICE |
| Are you willing to present as a poster if it is not selected for oral presentation? | Yes |