Towards the ultimate PMT waveform analysis for neutrino and dark matter experiments

Xu, Dacheng; Xu, Benda; Bao, Erjin; Wu, Yiyang; Zhang, Aiqiang; Wang, Yuyi; Zhang, Geliang; Xu, Yu; Guo, Ziyi; Pei, Jihui; Mao, Hanyang; Liu, Jiashuo; Wang, Zhe; Chen, Shaomin

doi:10.48550/arxiv.2112.06913

Cited by 1 publication

(1 citation statement)

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“…The timing parameter estimation requires an algorithm to extract the starting time and charge for each pulse found in a waveform. This type of algorithm can be called a "charge fitting" or "wave-unfolding" algorithm [28,29]. Currently, the time-dependent parameters commonly used in estimation use the time difference between the first independent pulse and the second pulse [15,23].…”

Section: Discussionmentioning

confidence: 99%

Batch VUV4 characterization for the SBC-LAr10 scintillating bubble chamber

Hawley-Herrera,

Alfonso-Pita,

Behnke

et al. 2024

J. Inst.

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The Scintillating Bubble Chamber (SBC) collaboration purchased 32 Hamamatsu VUV4 silicon photomultipliers (SiPMs) for use in SBC-LAr10, a bubble chamber containing 10 kg of liquid argon. A dark-count characterization technique, which avoids the use of a single-photon source, was used at two temperatures to measure the VUV4 SiPMs breakdown voltage (VBD), the SiPM gain (g SiPM), the rate of change of g SiPM with respect to voltage (m), the dark count rate (DCR), and the probability of a correlated avalanche (PCA) as well as the temperature coefficients of these parameters. A Peltier-based chilled vacuum chamber was developed at Queen's University to cool down the Quads to 233.15 ± 0.2 K and 255.15 ± 0.2 K with average stability of ±20 mK. An analysis framework was developed to estimate VBD to tens of mV precision and DCR close to Poissonian error. The temperature dependence of VBD was found to be 56 ± 2 mV K-1, and m on average across all Quads was found to be (459 ± 3(stat.)±23(sys.))× 103 e- PE-1 V-1. The average DCR temperature coefficient was estimated to be 0.099 ± 0.008 K-1 corresponding to a reduction factor of 7 for every 20 K drop in temperature. The average temperature dependence of PCA was estimated to be 4000 ± 1000 ppm K-1. PCA estimated from the average across all SiPMs is a better estimator than the PCA calculated from individual SiPMs, for all of the other parameters, the opposite is true. All the estimated parameters were measured to the precision required for SBC-LAr10, and the Quads will be used in conditions to optimize the signal-to-noise ratio.

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