Microboone Supernova Stream Data Quality and Readout Studies

MicroBooNE Supernova Stream Data Quality and Readout Studies Clara Berger Nevis Laboratories, Columbia University, New York Abstract Abstract: The MicroBooNE detector at Fermilab has the capa- bility to detect neutrino interactions from galactic core-collapse supernova events. To allow for potential data collection if a supernova occurs, the recently instated MicroBooNE supernova stream continuously collects data from the detector that is significantly compressed to cut down on the rates at which the data is read out. An FPGA suppresses the data by applying a dynamic zero-suppression algorithm that discriminates passing charge signals from the baseline, which is determined on the fly. This note details a study of reconstructing baseline in each channel readout. It also presents data quality studies on wire occupancy and flipping bits in the supernova stream. These studies will help determine how best to implement lossy data reduction and reconstruction at the Deep Underground Neutrino Experiment, where if detected and studied, supernova neutrino interactions could reveal some of the conditions within and processes that drive these stellar core-collapses. Contents 1 Introduction 2 1.1 MicroBooNE Detector . .2 1.1.1 Supernova Neutrinos . .3 1.1.2 Supernova Stream . .3 1.1.3 Suppression Scheme . .4 1.2 DUNE . .4 1 2 Data Quality Studies 5 2.1 Wire Occupancy . .5 2.2 Flipped Bits . .7 3 Baseline Studies 9 3.1 Methods . .9 3.2 Results . .9 3.3 Waveform Abnormalities . 12 3.3.1 Identical ADC Values in the ROI . 12 3.3.2 Double Peaks in V Plane . 16 4 Conclusions and Further Research 17 5 Acknowledgements 18 1 Introduction 1.1 MicroBooNE Detector The Micro Booster Neutrino Experiment (MicroBooNE) detector is a 170 ton liquid argon time projection chamber (LArTPC) located at Fermilab. MicroBooNE's primary physics goals include resolving predecessor Mini- BooNE's low energy event excess, measuring precision cross-sections, and searching for astronomical and exotic particles, such, as presented in this paper, as neutrinos from a nearby core-collapse supernova [1]. The detector is along the Booster neutrino beam (BNB), which produces mainly muon neutrinos from pion decays, as well as neutrinos from pion and kaon decays in the NuMI beam. When a charged particle traverses the detector, it leaves a stream of free electrons in the dense liquid argon. The electron trails then drift in the electric field in the detector (generated by a voltage applied on to a cathode plane) toward an anode plane. As depicted in figure 1, at the anode, 3 wire planes are arranged at 60◦; −60◦; and 0◦ from the vertical and the charges will either induce signal on the wires as the trails drift (in the first two sets of wires or induction planes) or be collected as signal (in the final set of wires or the collection plane). While the signals on the wire planes spatially track hits in the detector, the third dimension of reconstruction is the time between when the event took place and when the charge drifted to the anode. The light collection system detects the 2 Figure 1: Rendering of MicroBooNE LArTPC neutrino detection process. scintillation photons from each event that supply this initial time of event information [1]. 1.1.1 Supernova Neutrinos The majority of the binding energy released during a core-collapse supernova is in the form of neutrinos with energies on the order of tens of MeV. The neutrinos carried away in the supernova are mixed all three flavors but liquid argon is especially sensitive to detecting electron neutrinos (νe) through the process 40 − 40 ∗ νe + Ar ! e + K : The cores of supernovae house extreme conditions such as temperatures and densities. Learning about the properties of these supernova neutrinos can reveal interesting physics about the dynamics of and processes driving a collapsing stellar core in a supernova event [4]. 1.1.2 Supernova Stream The signals from the wire channels as well as from the photo-multiplier tubes in the light collection system are read out and digitized in two streams. The first avenue for read out and stored data, or the "NU" stream, is for beam neutrino events where all information is losslessly compressed and recorded according to triggers from the BNB, NuMI and external events [1]. 3 The alternate stream allows for the detection of these unpredictable neutrino events from supernovae, appropriately the supernova or "SN" stream, and thus must be continuously reading data from non-beam events. Super- nova neutrinos would reach Earth before electromagnetic signals so not only must the stream be continuously reading data, it must also store several hours of data in case of an alert from another observatory, neutrino or electromagnetic. In order to limit the amount of continuously read out data to near 30 GB/s, a Field Programmable Gate Array (FPGA) applies a Zero- Suppression algorithm that can discriminate between signal waveforms and the baseline, and subsequently suppress that baseline. This greatly reduces the amount of data to be processed by the DAQ, while retaining information on the regions of interest (ROIs), or packets of signal that have been selected from the baseline [2, 3]. For a supernova within the galaxy, on the order of 10 neutrino interactions producing ∼10 MeV electrons are expected in MicroBooNE [1]. 1.1.3 Suppression Scheme While the FPGA is running throughout the entire readout, only the waveforms that surpass a certain amplitude threshold are stored. These thresholds are in respect to the baseline and vary by plane [1]. The readout stream is divided into 64 tick (1 tick = 0.5 µs) sections in which the FPGA computes the baseline mean and variance. If the values are deemed consistent (∆(mean) < 2ADC; ∆(variance) < 3ADC2) over a set of 3 of these sections, the mean of the middle block is taken as the baseline [2]. After establishing the baseline, the FPGA will subtract this baseline from all values read out and will trigger to record an ROI if a sample passes a -25 ADC threshold in the first induction plane, ±15 ADC threshold in the second induction plane, or a +30 ADC threshold in the collection plane [3]. Within the ROI, 7 presamples are taken before the first sample that passes the threshold, as well as 8 postsamples after the last sample passing the threshold to capture the baseline before and after the pulse. 1.2 DUNE The Deep Underground Neutrino Experiment (DUNE) is an international collaboration experiment that will utilize the high intensity neutrino beam at 4 Figure 2: The Deep Underground Neutrino Experiment running between Fermilab and SURF. the Long Baseline Neutrino Facility (LBNF) at Fermilab. By 2035 DUNE is proposed to be comprised of a 1.2 MW beam and a near detector at Fermilab as well as four 10 kt LArTPCs at the Sanford Underground Research Facility (SURF) 1,300 km away in Lead, SD as depicted in in figure 2. The main sci- ence goals of DUNE include measuring CP violations, investigating neutrino mass hierarchy, and detecting neutrinos from core-collapse supernovae [5]. In the proposed DUNE detector, 3000 of such events are expected in 40 kt LAr from a supernova 10 kpc away [5, 4]. Our current work with the supernova stream in MicroBooNE will help inform how to best implement FPGA analysis in upcoming and more sensitive DUNE. 2 Data Quality Studies All data presented uses supernova stream run 14662, the assembled frames for the Online Monitor, taken on January 17th, 2018. The binary data was then converted into LArSoft format using uboonecode version 6 47 01. 2.1 Wire Occupancy MicroBooNE is known to have a variety of dead wires that do not return any signal in that channel. We see that beyond the dead wires, the probability of a hit occurring in a particular channel is not uniform. Figure 3 shows the gaps in a wire occupancy plot that expose dead wires but also a few particularly active channels with many more hits occurring in one channel 5 Figure 3: The number of hits recorded in each wire after 200 events. Both dead channels and noisy channels can be identified from the distribution. Figure 4: 100 events in Run 14662 displayed on top of each other revealing the dead and noisy channels. The red lines depict the approximate shape of the occupancy distribution we would expect based on the than the surrounding channels. These are most likely noisy channels. The distribution of hits per wire in the collection plane is relatively flat because all of the wires are the same length in the detector. The induction channels vary in length so we expect a pattern resembling that of the first 4800 channels in figure 3. We observe similar patterns in figure 4 where the tracks of 100 events were stacked also giving an indication of how hits build up in each wire. However, we have found that the gap between about wire 2000 and 3000 is due to an inefficiency at high thresholds and these wires output signals when the thresholds in the channels were lowered based on the distribution of ADCs in the NU stream. More hits in a channel in the SN stream consequently requires that more data is read and saved. 6 Figure 5: Waveform in channel 3401 showing a flipped bit at tick 4804. 2.2 Flipped Bits After the electronics write the binary data, once the data is read out, some binary words show a flipped bit where one (or more) bit(s) in the word flips. These flipped bits are almost always from 0 to 1, which adds a 2n ADC, depending on which bit is effected, to the original value.

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