Afterpulse prediction for SUBMET experiment

TL;DR

The SUBMET experiment at J-PARC searches for millicharged particles with $m_ chi<1.6\,\mathrm{GeV}/c^2$ and $Q_\nchi<10^{-3}e$. PMTs exhibit afterpulses following large pulses, which contaminate the signal region; the authors develop a data-driven method to predict afterpulse rates using the large-pulse area and the exponential time structure, with module-specific time constants. Two parametric forms for the area dependence are considered: linear and exponential in $A$, with fitted parameters $p_0$, $p_1$, and $\tau$. The method achieves about 20% precision in predicting afterpulses across 160 modules and can be used to robustly include events with large pulses in background estimates. This improves the reliability of background predictions for the millicharged particle search.

Abstract

The SUB-Millicharge ExperimenT (SUBMET) investigates an unexplored parameter space of millicharged particles with mass $m_χ< $ 1.6 GeV/c$^2$ and charge $Q_χ< 10^{-3}e$. The detector consists of an Eljen-200 plastic scintillator coupled to a Hamamatsu Photonics R7725 photomultiplier tube (PMT). PMT afterpulses, delayed pulses produced after an energetic pulse, have been observed in the SUBMET readout system, especially following primary pulses with a large area. We present a prediction method for afterpulse rates based on measurable parameters, which reproduces the observed rate with approximately 20\% precision. This approach enables a better understanding of afterpulse contributions and, consequently, improves the reliability of background predictions.

Figures (9)

• Figure 1: The SUBMET detector installed at the J-PARC neutrino monitor building.
• Figure 2: Time distribution of pulses with heights exceeding 140 mV. (a) shows the full beam structure consisting of 8 bunches as recorded in the standard data-taking mode. (b) shows a delayed time window in the run dedicated to afterpulse studies.
• Figure 3: Waveform of an afterpulse event. Green arrows indicate the detected pulses by the SUBMET pulse finding algorithm. A significant baseline fluctuation is observed immediately after the large pulse (Region1).
• Figure 4: Distribution of number of afterpulses $n$ vs pulase area $A$. The black dots represent the average number of afterpulses in each area bin. The orange solid and green dashed lines correspond to the linear and the exponential fits, respectively.
• Figure 5: Distribution of $\Delta t = t_\textrm{afterpulse}-t_\textrm{large pulse}$ normalized to unit area.