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Tianying Xiao

Publications and source records attributed to Tianying Xiao.

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Simulation Based Characterization of Deconvolution-Based PMT Waveform Reconstruction Under Large Charge Dynamic Range and Varying Scintillation Time Profiles

Photomultiplier tubes (PMTs) are widely used as photon sensors for neutrino and dark matter detection. Accurate charge and time information extracted from PMT waveforms is crucial for event reconstruction. An algorithm based on deconvolution technology was proposed and applied to the reconstruction of PMT waveforms. This study further investigated the reliability of the deconvolution algorithm when handling a large charge dynamic range (0-200 photoelectrons), varying scintillation time profiles, and muon-induced large signals. Monte Carlo data confirmed that the deconvolution algorithm exhibits relatively stable reconstruction performance: under the simulation conditions described in this paper (including a noise level of 0.1 PE, single photoelectron charge resolution of 30%, 1 GHz sampling rate, 1000 ns window, three undershoot configurations, and eight scintillation time profiles), the residual non-linearity of charge reconstruction is controlled to approximately 1% over the range of 0 to 200 photoelectrons, and the algorithm is capable of handling muon-induced large signals. The reconstruction performance depends on adequate baseline recovery; a waveform window that is too short relative to the undershoot tail leads to degraded reconstruction quality, which can be mitigated by extending the sampling window.

physics.ins-det

Investigation and optimization of the deconvolution method for PMT waveform reconstruction

Photomultiplier tubes (PMTs) are extensively employed as photosensors in neutrino and dark matter detection. The precise charge and timing information extracted from the PMT waveform plays a crucial role in energy and vertex reconstruction. In this study, we investigate the deconvolution algorithm utilized for PMT waveform reconstruction, while enhancing the timing separation ability for pile-up hits by redesigning filters based on the time-frequency uncertainty principle. This filter design sacrifices signal-to-noise ratio (SNR) to achieve narrower pulse widths. Furthermore, we optimize the selection of signal pulses in the case of low SNR based on Short-Time Fourier Transform (STFT). Monte Carlo data confirms that our optimization yields enhanced reconstruction performance: improving timing separation ability for pile-up hits from $7\sim10$~ns to $3\sim5$~ns, while controlling the residual nonlinearity of charge reconstruction to about 1\% in the range of 0 to 20 photoelectrons.

physics.ins-det