[Paper Review] Prospects of fast timing detectors for particle identification at future Higgs factories

Bohdan Dudar, Jenny List+2 more|arXiv (Cornell University)|Jan 1, 2021

Particle Detector Development and Performance1 references4 citations

TL;DR

This paper investigates the use of fast timing silicon sensors in the electromagnetic calorimeter of a future Higgs factory detector to enable precise particle identification (PID) of charged hadrons (π±, K±, p) via time-of-flight (TOF) measurements. With sub-100 ps time resolution, TOF-based PID achieves mass reconstruction precision sufficient to resolve kaon mass discrepancies and extend PID into the 3–5 GeV momentum range where dE/dx fails, using track parameters at the calorimeter surface and a multi-hit TOF fit estimator to minimize mass bias.

ABSTRACT

We present an overview of a study on precise mass reconstruction and identification of charged hadrons ($\pi^{\pm}$, $K^{\pm}$, $p$) using time-of-flight measurements in the electromagnetic calorimeter of a typical Higgs factory detector. Time-of-flight measurements can take advantage of fast timing Si sensors with a time resolution in the order of 10 ps. A precise time-of-flight measurement might contribute to the kaon mass determination and can improve particle identification in the momentum regions inaccessible for the $dE/dx$ method. In this contribution, we discuss the current status and the challenges of the time-of-flight approach for a precise reconstruction of charged hadron masses.

Motivation & Objective

• To assess the feasibility of using fast timing silicon sensors (10–100 ps resolution) in the electromagnetic calorimeter for precise charged hadron identification at future Higgs factories.
• To address the challenge of particle identification in the 3–5 GeV momentum range, where dE/dx measurements fail due to overlapping Bethe-Bloch bands.
• To improve the precision of kaon mass measurement, which currently suffers from a 13 keV discrepancy between two spectroscopic measurements.
• To evaluate and optimize TOF estimators based on single- and multi-hit timing information from ECal clusters.
• To calibrate TOF estimators using photon clusters to reduce systematic biases in hadron mass reconstruction.

Proposed method

• Uses the ILD detector concept and full simulation with e+e−→Z→q¯q events at √s = 500 GeV.
• Applies the Pandora particle flow algorithm to reconstruct particle flow objects (PFOs) with one track and one ECal cluster in the barrel.
• Calculates momentum from track curvature (Ω) and dip angle (λ) at the IP or calorimeter surface using the relativistic momentum formula p = eBz/|Ω|√(1 + tan²λ).
• Estimates time-of-flight (τ) via β = ℓtrack/(cτ), where ℓtrack is derived from track parameters and extrapolated entry point to ECal.
• Tests four TOF estimators: τclosest (closest hit), τearliest (earliest hit), τcorr (corrected for hit-to-entry distance), and τavg/τfit (multi-hit averaging or linear fit of first 10 ECal layers).
• Calibrates TOF estimators using photon clusters with known true time-of-arrival to correct for systematic biases.

Experimental results

Research questions

• RQ1 Can TOF measurements with 10–100 ps time resolution enable particle identification of charged hadrons in the 3–5 GeV momentum range where dE/dx fails?
• RQ2 Which combination of track parameters (at IP vs. calorimeter surface) and TOF estimator minimizes mass reconstruction bias for π±, K±, and p?
• RQ3 How significant is the systematic bias in TOF estimation, and can it be reduced through calibration using photon clusters?
• RQ4 What is the impact of finite time resolution and shower development fluctuations on TOF estimator performance?
• RQ5 Can TOF-based mass reconstruction achieve the 10 keV precision required to resolve the current kaon mass discrepancy?

Key findings

• Using track parameters at the calorimeter surface (Ωcalo, λcalo) and a multi-hit TOF fit estimator (τfit) yields the smallest mass bias, with consistent performance across π±, K±, and p.
• The τfit estimator with calorimeter-surface track parameters shows the least deviation in mass bias between particle types, achieving a bias of approximately 3–4 MeV for typical kaons.
• After calibration using photon clusters, the timing bias in τfit is reduced by a factor of 3, though a residual bias of ~1 ps remains, corresponding to a 3–4 MeV mass bias.
• The study identifies that the residual bias is two orders of magnitude larger than the 10 keV precision needed to resolve the kaon mass discrepancy.
• The choice of track parameters and TOF estimator significantly affects mass reconstruction accuracy, with the combination of Ωcalo, λcalo and τfit being optimal.
• Future work is required to model finite time resolution, digitization effects, and to extend the method to endcap regions and non-barrel PFOs.