KM3NeT data analysis conventions

KM3NeT DATA 2014 001-dataAnalysisConvention ACreusot v1 December 15, 2014 KM3NeT data analysis conventions Robert Bormuth 1, Alexandre Creusot 2 1 Nikhef, 2 Laboratoire AstroParticules et Cosmologie, corresponding author:creusot@apc.univ-paris7.fr Abstract This note is dedicated to the definition and description of the different parameters used for the first level analysis of the KM3NeT data. Terms such as baseline, burst fraction, or trigger are detailed for the final KM3NeT data format, as well as for the data format of the two prototypes, the PPM-DOM and the PPM-DU. Status version date author reviewer validation creation 1 02/12/2014 Bormuth/Creusot - - modification 1 12/12/2014 Bormuth/Creusot Graf/Chiarusi -

Introduction The PPM-DOM [1] has been the first multi-pmt detector deployed in the deep sea. As a consequence, during the data analysis, several parameters were defined for the first time while the others were inherited from the Antares data analysis. All these parameters were then adapted for the data analysis of the second prototype, the PPM-DU, and most of them will also be used in the KM3NeT framework. For each parameter, one after the other, we will present its definition, how to derive its value based on the data and some examples if needed. The KM3NeT parameters will be presented in the first section. The second section will be dedicated to the explanation of the few parameters used differently in the prototype framework. 1 General data conventions for KM3NeT 1.1 Data structure Data are organized according to the identities of the digital optical modules, i.e. DOMs, and to the absolute timing of the time slices. One DOM is composed of 31 photomultiplier tubes, i.e. PMTs. One time slice has a duration of about 134 ms (2 27 ns). One time slice of one DOM is organized according to the start time of the hits and to the PMT identities. The most elementary cell of the data is the hit. A hit is a digitized signal seen by one PMT. It is defined by a start time and a length, the time over threshold (ToT). More information about the data structure can be found in [2]. 1.2 PMT position The 31 PMTs of each DOM have well defined positions. For this purpose, a reference frame has been defined with respect to the vertical plane and to the ropes holding the DOM (see [3]). The details of the PMT positioning can be found in [3] and [4]. 1.3 Multiplicity The multiplicity corresponds to the number of PMTs of a single DOM that have detected a hit in a predefined time window. This time window, called L1 time window, has been fixed at 25 ns. If only one PMT has detected a hit in the time window, we then speak of single rate. For x PMTs having detected a hit in the same L1 time window, we use the terminology x-fold. 1.4 baselines Depending on the analysis performed, several baselines can be defined. The generic term baseline is applied when speaking about single PMT rates. It also corresponds to the background rate of hits and is therefore also called single rate baseline. The official way to estimate the rate of hits on a specific PMT is based on the observed number of hits within a time slice. The histogram of the rate of hits per time slice is shown in the plot of figure 1 for the PMT#11 of the DOM#0 of the PPMDU and for run#425. The rising edge of the distribution is fit to a Gaussian function (µ, σ). The mean value µ of the fit corresponds 2

to the baseline value for the run. Only complete slices, i.e. not saturating, are considered for this calculation. It is worth mentioning that single hit information are not accessible for triggered data. It is therefore not possible to estimate the baseline (or to draw the histogram of figure 1) after data processing. On the other hand, its value is estimated during the data processing and saved in the summary slice (see section 1.8). Figure 1: Histogram of the rate of hits for the PMT#11 of the DOM#0 of the PPMDU and for the run#425. Each entry of the histogram corresponds to one time slice. When looking at 2-fold events, the 2-fold baseline is defined as the rate of random coincidences between the 2 PMTs. The official method consists in fitting the distribution of the time difference between the hits of each PMT to Gaussian and constant functions (left plot of the figure 2). The 2-fold baseline is given by the constant divided by the run duration. For larger multiplicities, another method is used to estimate the x-fold baselines: for each individual time slice, the hit start times are scrambled 1. The x-fold baseline is also called combinatorial background. The x-fold baseline is shown as a function of x in red in the right plot of figure 2. The same histogram for non scrambled data is also shown in blue for comparison. 1.5 Burst fraction The background induced by the bioluminescence may affect the signal on different time scales. If the seasonable effects appear as a long term increase of the baseline all over the array, the bursts affect the PMT counting rates locally and on a time scale comparable to the time slice duration. In order to monitor the bioluminescent activity in the environment the burst fraction is estimated for each run. The burst fraction is defined as the ratio between the number of slices above a threshold of 1.2 baseline and the total number of slices. If 2 consecutive time slices are above the threshold, they are considered as the same burst. 1.6 High rate cut As previously mentioned, the bursts of bioluminescence may affect the signal to noise ratio. The high rate cut (HRC) has been introduced in order to minimize the noise induced by the 1 scrambling is done by adding 100 ns PMT identity to the hit start time 3

Figure 2: In the left, histogram of the time difference between hits of PMT#11 and PMT#12 of the DOM#0 of the PPMDU and for the run#425. In the right, histogram of the x-fold coincidences for the combinatorial background in red and for the data of dom#0 and run#425 in blue. Number of PMTs is also called multiplicity. bursts. The HRC is extracted from the Gaussian fit of the single rate baseline calculation (left plot of figure 1). It is defined as HRC = µ + 3 σ (1) Time slices with a rate of hits above the HRC are considered as too noisy and are therefore cut during the analysis (offline). 1.7 High rate veto The high rate veto (HRV) is the limit above which the data transfer between the PMT and the shore is stopped. It is adjustable. If the HRV is reached, then for the rest of the time slice, no hits are transmitted for the PMT. The next time slice contains a status word including the HRV channels from the last time slice. 1.8 Trigger 1.8.1 Trigger logic The trigger for the PPM-DU is a offline software trigger. The software used is provided by JPP, mainly the L1 hit selector and the 3DShower trigger. It functions in two steps. The PMT time calibration and dom time calibration is applied during the trigger process but the uncalibrated information is written to file. First the L1 hit selection is applied per DOM. A L1 hit is defined as two hits on a DOM, with a time difference smaller than TMaxLocal = 25 ns. T L1 TMaxLocal = 25 ns (2) In the applied L1 selector a raw hit can be part of up to two L1 hits. It can be the later of the two hits of one L1 and the earlier hit of a second L1. The time of a L1 hit is defined as the time of the earlier of the two hits it is composed of. After the L1 hits are selected, the L1 hits of all three DOMs are merged in one L1 time 4

stream. On this time stream the 3DShower trigger is applied. The 3DShower trigger selects triggered events from the L1 time stream by grouping all L1 hits with a time difference smaller than T event =330.345 ns forward in time. T event = DOM maxdst /c water + T MaxExtra 330.345 ns (3) where DOM maxdst is the maximal distance between the DOMs which is 71.76 m and T MaxExtra = 20 ns. Every L1 can only be part of one event. If an event contains more L1 hits than numberofhits= 1 it is written to file. 1.8.2 Trigger output The trigger can output different file formats. In the PPM-DU case we use the ROOT file format. A ROOT file consists of three main ROOT trees and a header. The ROOT trees are: Triggered Event Header Information on trigger parameters Triggered hits Uncalibrated hit information of all hits that compose a L1 hit in a triggered event Snapshot hits Raw hit information of all hits in a time window around a triggered event [ TTrigger T MaxExtra, T Trigger + T MaxExtra ] Timeslices containing L1 hits Summaryslices Information on PMT rates, duration of analyzed data and other useful information Any hit information written to file is raw information as read by the data acquisition. 2 Specific conventions for prototypes For historical reasons, most of the PPM-DOM parameters were derived from the Antares environment. Nevertheless, it happened that some of them were adapted to the specific studies driven in [1]. This is the case for the burst fraction estimation. In this section, the main differences between the prototype and production conventions will be presented. 2.1 Data structure For the prototypes, the terminology frame may sometimes be used. It refers to the former format of the data and corresponds to a size fraction (one sixth) of the time slice. 5

2.2 Baselines The method defined in section 1.4 is officially used for the baseline estimation of both prototypes. An alternative method for estimating the baseline is based on the time difference between 2 consecutive hits. The tail of the distribution is fit to an exponential function. The results with such a method are shown in the right plot of figure 3. Both methods give similar results for pmt#11 of dom#0 of run#425: 5.4 khz and 5.3 khz for the official and alternative methods, respectively. Figure 3: Histogram of the time difference between 2 consecutive hits for the PMT#11 of the DOM#0 of the PPMDU and for the run#425. 2.3 Burst, cut and veto The vetoing and cutting were defined differently for the PPM-DOM. First, no HRC was defined. The HRV was defined as the limit for which a time slice was considered as a burst. HRV = µ + 3 σ (4) So to say that the PPM-DOM HRV was the KM3NeT HRC. Furthermore, the burst fraction was the ratio between the number of slices with a rate above the HRV and the the total number of slices. Finally, the data transfer limit was called Xo f f instead of HRV. This limit has been set to the same value for the PPM-DOM than for the PPM-DU. The table 1 presents the vetoing and cutting parameters for the prototypes and the production DOMs. PPM-DOM PPM-DU production 1.2 baseline no yes yes µ + 3 σ HRV HRC HRC data transfer limit Xo f f HRV HRV burst fraction n HRV /n total n 1.2 baseline /n total n 1.2 baseline /n total Table 1: Vetos and cuts for the prototypes and the production DOMs. n HRV and n 1.2 baseline are the number of slices above the HRV and 1.2 baseline, respectively. n total is the total number of slices. 6

3 Terminology reminder hit: PMT signal defined by a start time and a duration (ToT) slice (or time slice): 2 27 ns of data for a single DOM frame: 2 27 ns of data of several PMTs (one sixth of a slice) L1 time window: coincidence window for the PMTs of a single DOM (25 ns) multiplicity: number of PMTs having a hit in a L1 time window baseline (or single rate baseline): rate of hits on a single PMT high rate veto: data acquisition saturation high rate cut: limit above which a time slice is considered as too noisy burst fraction: ratio between the number of burst slices and the total number of slice. The limit above which a time slice is considered as a burst is 1.2 baseline coincidence time window: coincidence window for the DOMs (330.345 ns) L1 hit: group of hits satisfying the L1 hit selector L1 time slice: 2 27 ns of L1 hits for a single DOM L1 hit selector: algorithm selecting the PMT hits in coincidence within the L1 time window on a single DOM event (or coincidence or triggered event): group of L1 hits satisfying the 3DShower trigger 3DShower trigger: algorithm selecting among the DOMs the L1 hits in coincidence within the coincidence time window slice header: information on the trigger parameters snapshot hit: complementary information on raw hits that are neighbors in time of the triggered event summary slice: general information on the slice References [1] KM3NeT collaboration, The European Physical Journal C, September 2014, 74:3056 [2] km3net SOFT WG 2014 006 JPPconverter ACreusot v1.pdf [3] KM3NeT DET 2014 002 - PMT map - rev 3.pdf [4] KM3NeT PPM 2014 008-PMTpositioning ACreusot v3.pdf 7