straxen.plugins.merged_s2s_he package

Submodules

straxen.plugins.merged_s2s_he.merged_s2s_he module

class straxen.plugins.merged_s2s_he.merged_s2s_he.MergedS2sHighEnergy[source]

Bases: MergedS2s

High energy channels: attenuated signals of the top PMT-array Merge together peaklets if peak finding favours that they would form a single peak instead.

Technically, the S2 merging algorithm merges S2 peaklets into S2 peaks. By introducing more information about the waveform and (x, y) distribution of potential groups of peaklets, the algorithm removes PI and DE population from S2 peaks.

Note: Types FAR_XYPOS_S2_TYPE (20) and WIDE_XYPOS_S2_TYPE (22) are still S2s, but they do not participate in the event building.

The algorithm merges S2 peaklets when they are close in (t, x, y). But if a group of peaklets is dense in time but sparse in (x, y), the following steps are conducted:

  1. Merge these peaklets that are dense in (x, y).

  2. Assign the peaklets that are dense in time but not dense in (x, y) by type 20,

    they are usually PI or DE.

  3. If the sum of nearby type 20 is large compared to the merged peak,

    assign the merged peak as type 22, because it is usually PI.

Reference: xenon:xenonnt:analysis:s2_merging_time_position xenon:xenonnt:analysis:sr2_peak_types

child_plugin = True
compute(peaklets_he, start, end)[source]
data_kind: Dict[str, str] | str = 'merged_s2s_he'
depends_on: Tuple[str, ...] = ('peaklets_he', 'peaklet_classification_he')
infer_dtype()[source]

Return dtype of computed data; used only if no dtype attribute defined.

provides: Tuple[str, ...] | str = ('merged_s2s_he',)
property use_bayesian_merging

Module contents