Application of a pulse shape selection method to a true coaxial Ge(Li) detector for measurements of nanoseconds half-lives

Efficient machine learning approach for optimizing the timing resolution of a high purity germanium detector

“…Most of the methods-analog or digital-that aim to improve the timing resolution of the HPGe detector optimize the time pick-off algorithm by determining one set of time pick-off parameters for all the HPGe detector waveshapes. A single set of parameters, however, lead to large spread in time pick-off and often ~ 1 to 5 ns timing resolutions are attained only by rejecting a large fraction of waveshapes that are responsible for the time broadening [13][14][15]. The rejection of signals adversely affects the experimental count rate and can lead to loss of valuable information-especially for events involving low energy γ photons [5].…”

“…Pioneering works that utilized analog processing methods to select specific pulse shapes had achieved a few ns (~ 1 ns) timing resolutions with small volume or planar Ge (Li) detectors 3 [14,15], and thus demonstrated the critical dependence of the timing resolution on waveform shape. Complex and time-consuming optimization of the timing filter amplifier (TFA)-constant fraction discriminator (CFD) combination was shown to obtain ~ 4 ns coincidence timing resolution with large volume HPGe detectors (~ 60 cm 3 ) that have ~ 10% efficiency [2] and that utilize γ photons only within 511±50 keV.…”