Sophronia

From ancient Greek: sensible, prudent.

This city processes each S2 signal previously selected as pmaps in irene assuming a unique S1 within an event to produce a set of reconstructed energy depositions (Hits). Hits consist of three dimensional coordinates with an associated energy (PMT signal) and charge (SiPM signal). The city contains a peak/event filter, which can be configured to find events with a certain number of S1/S2 signals that satisfy certain properties. Currently, the city is designed to accept only 1 S1 signal. If the configuration allows for more than one S1, the first one will be used to estimate z. Furthermore, hits can be optionally corrected for geometrical and lifetime effects. Besides hits, the city also stores the global (x, y) position of each S2 signal. The tasks performed are:

• Classify peaks according to the filter.

• Filter out events that do not satisfy the selector conditions.

• Resample S2 signals.

• Compute a set of hits for each slice in the resampled S2 signal.

• If there are more than one hit per slice, share the energy according to the charge recorded in the tracking plane.

• If correction maps are provided, apply corrections to hits.

Input

• /Run/events: Table containing the event number and timestamps

• /Run/runInfo: Table containing the run number for each event

• /PMAPS/S1: Table containing S1 pmt-summed peak information

• /PMAPS/S2: Table containing the S2 pmt-summed peak information

• /PMAPS/S2Si: Table containing the S2 sipm peak information

Output

• /DST/Events: summary of the S1 and S2 information of the reconstructed events. See Dorothea for more details

• /RECO/Events: list of hit data for each event

• /Filters/s12_selector: flag for whether an event passed the S1 and S2 selections

• /Filters/valid_hit: flag for whether an event passed the empty pmap filter

Config

Besides the Common arguments to every city, Sophronia has the following arguments:

Parameter	Type	Description
drift_v	float	Drift velocity. Used to calculate the z position from the drift time
s1_params	dict	Selection criteria for S1 signals (see Peak filtering)
s2_params	dict	Selection criteria for S2 signals (see Peak filtering)
global_reco_algo	XYReco	Reconstruction algorithm applied to entire peaks (kDST)
global_reco_params	dict	Configuration parameters for the global recontruction algorithm
rebin	int	Level of resampling or grouping of consecutive samples for reconstruction. Must be \(\geq\) 1
rebin_method	RebinMethod	Resampling method (usually stride)
q_thr	float	Charge threshold to be applied to the SiPMs
sipm_charge_type	SiPMCharge	Type of SiPM charge to use (usually raw)
same_peak	bool	Controls whether invalid hits can only be merged with other hits from the same peak
corrections_file	str	Path to the file holding the correction maps
apply_temp	bool	Whether to apply temporal corrections (in general, False in MC, True in data)

Workflow

Sophronia performs the following data transformations:

• Peak filtering

• Build event summary

• Resampling and hit creation

• Hit merging

• Hit correction

Peak filtering

Irene finds peaks in the waveform with general characteristics, but does not impose strong requirements on them. Sophronia, however, can be more specific and selects S1 and S2 signals based on the following peak properties: width, height, and integral. These quantities are calculated based on a (low) threshold applied to the PMT waveform of the peak. For S2 signals, the number of SiPMs with some signal is also taken into account [1]. The variables that control this filtering are provided in the parameters {s1,s2}_params and are defined as follows:

• {s1,s2}_w{min,max}: minimum/maximum width of S1/S2 peaks

• {s1,s2}_h{min,max}: minimum/maximum height of S1/S2 peaks in a 1-\(\mu\)s sample

• {s1,s2}_e{min,max}: minimum/maximum integral of S1/S2 peaks

• {s1,s2}_ethr: threshold applied to the PMT-summed waveform to compute the quantities above

• s2_nsipm{min,max}: minimum/maximum number of SiPMs with signal in an S2 peak

• {s1,s2}_n{min,max}: minimum/maximum number of S1/S2 peaks that satisfy all of the criteria above for given event

[1]

Bear in mind that Irene requires a minimum amount of charge per peak and per slice for the SiPM to be considered.

Build event summary

This part of the processing is equivalent to Dorothea using global_reco_algo and global_reco_params. See that city’s documentation for more details.

Resampling and hit creation

In numerous occasions, the energy deposition in a 1-\(\mu\)s sample is not enough to produce a significant signal in the SiPMs, which results in poor reconstruction. It is therefore useful to be able to resample the waveforms and increase the sampling period (lower sampling rate). The variable that controls this resampling is rebin and it specifies how many consecutive 1-\(\mu\)s slices are added up together. A value of rebin = 1 means no resampling is performed. Only integer values greater than or equal to 1 are accepted.

Unlike Penthesilea, Sophronia considers the response of a SiPM in a single (resampled) slice a Hit. Hits are defined as the aggregation of the absolute position of the SiPM, the time difference between the slice and the S1 peak time [2], the amplitude of the SiPM waveform (charge) and the energy corresponding to said charge. The corresponding energy is defined as

\[E_i = \frac{Q_i}{\sum_{k=0}^{N} Q_{k}} E_{slice}\]

where \(Q_i\) and \(E_i\) are the charge and corresponding energy of SiPM \(i\), respectivly; \(N\) is the number of SiPMs with signal in the slice and \(E_{slice}\) is the energy of the slice, given by the amplitude of the PMT-summed waveform in the slice.

[2]

This information is used to obtain the z position of the hit by dividing the time difference by the drift velocity (drift_v).

Hit merging

In some occasions, a time slice might have no SiPMs recorded. This means that all SiPM waveforms have been disregarded in Irene or that no SiPM has a charge above q_thr in such slice. However, because the slice is considered part of a peak, there is some energy associated to it, which should not be discarded. In these cases, Sophronia generates a fake hit (a.k.a. NN-hits) with no charge and no position associated [3].

After all hits are generated, a second step is performed, in which the fake hits are merged with existing valid hits. This operation searches for the hits that are closest (in z) to the fake one. Each fake hit’s energy is shared among its neighbours and added to the neighbouring slice energy. The energy is not share homogeneously, but proportionally to the charge of each hit. The parameter same_peak controls whether only slices from the same peak are taken into account or if other peaks might also be taken into consideration.

[3]

Actually, the algorithm associates an unphysical charge (NN = -999999) and a position \(x = y = 0\).

Hit correction

If a correction map is provided (corrections_file), the geometrical and lifetime corrections are applied. These corrections are composed of three factors:

• geometrical: accounts for different light collection efficiencies in x,y

• lifetime: accounts for the loss of electrons (and therefore signal) due to electron attachment during the drift

• temporal: changes in the previous two corrections over time. This is applied only in data, as MC has no temporal dependence.

The geometrical correction is a 2d-function: given the hit position in x,y, we obtain a factor that normalizes the response to the center of the chamber. It may also scale the response to different units (pes-to-keV, for instance).

The lifetime correction is a 3d-function: given the hit position in x,y,z we obtain the correction factor that normalizes the response to that of z=0.

The temporal correction is a 1d-function: given the time since the start of the run, we estimate variations in the geometrical and lifetime corrections that normalize the response to that of the beginning of the run. This correction is only applied if apply_temp is set to True.