Modeling the Timing Characteristics of the PICOSEC Micromegas Detector

TL;DR

This paper presents a detailed phenomenological model for the timing characteristics of the PICOSEC Micromegas detector, validated by simulations and experiments, explaining microscopic variables influencing timing resolution.

Contribution

It introduces a new statistical and phenomenological model based on 'time-gain per interaction' to predict PICOSEC timing behavior accurately.

Findings

Simulation results match experimental timing data

Model explains counter-intuitive microscopic variable behavior

Provides formulae for fast predictive calculations

Abstract

The PICOSEC Micromegas detector can time the arrival of Minimum Ionizing Particles with a sub-25 ps precision. A very good timing resolution in detecting single photons is also demonstrated in laser beams. The PICOSEC timing resolution is determined mainly by the drift field. The arrival time of the signal and the timing resolution vary with the size of the pulse amplitude. Detailed simulations based on GARFIELD++ reproduce the experimental PICOSEC timing characteristics. This agreement is exploited to identify the microscopic physical variables, which determine the observed timing properties. In these studies, several counter-intuitive observations are made for the behavior of such microscopic variables. In order to gain insight on the main physical mechanisms causing the observed behavior, a phenomenological model is constructed and presented. The model is based on a simple mechanism of "time-gain per interaction" and it employs a statistical description of the avalanche evolution. It describes quantitatively the dynamical and statistical properties of the microscopic quantities, which determine the PICOSEC timing characteristics, in excellent agreement with the simulations. In parallel, it offers phenomenological explanations for the behavior of these microscopic variables. The formulae expressing this model can be used as a tool for fast and reliable predictions, provided that the input parameter values (e.g. drift velocities) are known for the considered operating conditions.