Abstract
Abstract
The PandaX-4T experiment is designed for multiple purposes,
including searches for solar neutrinos, weakly interacting massive
particles, and rare double beta decays of xenon isotopes. The
experiment produces a huge amount of raw data that needs to be
stored for related physical analyses in a wide energy range. With
the upgrading of the PandaX-4T experiment, the doubled sampling rate
resulted in a larger data size, which challenges both the cost and
the data processing speed. To address this issue, we propose a data
reduction strategy by removing the noise tail of large signals and
downsampling the remaining parts of them. This strategy reduces the
requirement for storage by 65% while increasing data processing
speed. The influences on physical analyses on different topics at
different energy regions are negligible.