A Non-Parametric Density Estimation Approach to Measuring Beam Cooling in MICE

TL;DR

This paper explores the use of kernel density estimation, a non-parametric method, to accurately measure muon beam cooling in the MICE experiment, addressing the need for precise analysis tools in particle physics.

Contribution

It introduces the application of kernel density estimation to measure muon beam phase-space density reduction in MICE, enhancing measurement accuracy.

Findings

KDE provides precise phase-space density calculations.

KDE effectively measures beam cooling effects.

The method improves analysis accuracy for MICE data.

Abstract

The goal of the international Muon Ionization Cooling Experiment (MICE) is to demonstrate muon beam ionization cooling for the first time. It constitutes a key part of the R&D towards a future neutrino factory or muon collider. The intended MICE precision requires the development of analysis tools that can account for any effects (e.g., optical aberrations) which may lead to inaccurate cooling measurements. Non-parametric density estimation techniques, in particular, kernel density estimation (KDE), allow very precise calculations of the muon beam phase-space density and its increase as a result of cooling. In this study, kernel density estimation technique and its application to measuring the reduction in MICE muon beam phase-space volume is investigated.