In this episode, we discuss the details of the CMS experiment's innovative advancement in particle detection, specifically focusing on its enhanced ability to identify highly collimated electron-positron pairs. Previously, the CMS detector struggled to differentiate these pairs when they travelled too closely, often registering them as a single particle. To overcome this, the CMS Collaboration developed a new machine learning-based technique that significantly improves the detector's resolution, enabling it to distinguish pairs with extremely small angular separations. The text explains how this new method has been rigorously tested and validated using both simulations and real-world data, confirming its efficacy in energy measurement and consistency. This improved capability will allow CMS to conduct more precise searches for new phenomena beyond the Standard Model, particularly theories predicting the existence of lightweight bosons that decay into such electron-positron pairs.

Read more about it in: https://cms-results.web.cern.ch/cms-results/public-results/preliminary-results/EGM-24-002/index.html