Novel method to indirectly reconstruct neutrinos in collider experiments

TL;DR

This paper introduces a novel inclusive-tagging scheme using an asymptotically recursive vector sequence to indirectly reconstruct neutrinos in collider experiments, potentially transforming decay reconstruction and improving Standard Model measurements.

Contribution

The authors propose the first solution capable of capturing the four-momentum of multiple undetected particles like neutrinos in collider events, advancing reconstruction techniques.

Findings

Potential to significantly improve precision in Standard Model parameter measurements.

First proposed method to reconstruct multiple neutrinos in collider experiments.

Introduces a recursive vector sequence with applications beyond particle physics.

Abstract

Neutrinos play a crucial role in particle physics, but cannot be tracked in collider experiments. If more than one neutrino is present in a collision event, it is impossible to extract neutrinos' information using any of the traditional methods. In this Letter, we introduce an innovative inclusive-tagging scheme that is capable of capturing the four-momentum of an undetected particle on the signal side, such as a neutrino, $K_L^0$, etc., in collider experiments. This is the first proposed solution to the longstanding challenge outlined above. Our scheme, based on an asymptotically recursive vector sequence, has the potential to catalyze a significant transformation in the reconstruction techniques for (semi-)leptonic decays of collider experiments. The application and development of this scheme will greatly improve the precision of measurements of Standard Model parameters in the (semi-)leptonic sector with the same data samples, and could play a pivotal role in the search for new physics. Additionally, the asymptotically recursive (vector) sequence introduced in our scheme might also have promising applications in other fields, such as machine learning.