Electronics Testing, LArSoft Analysis, and Data Acquisition for - - PowerPoint PPT Presentation
Electronics Testing, LArSoft Analysis, and Data Acquisition for MicroBooNE Victor Genty Nevis Labs August 1, 2013 Genty (Nevis) REU Presentations August 1, 2013 1 / 31 Outline 1 Mini & Micro - BooNE 2 Low Energy Excess 3 LArSoft
Victor Genty
Nevis Labs
August 1, 2013
Genty (Nevis) REU Presentations August 1, 2013 1 / 31
1 Mini & Micro - BooNE 2 Low Energy Excess 3 LArSoft Analysis 4 PMT Gain Study 5 Splitter Reflection 6 PMT Data Acquisition Genty (Nevis) REU Presentations August 1, 2013 2 / 31
Studied: νµ → νe oscillations, both modes With: Cerenkov detector, 950,000 liters of mineral oil, 1520 phototubes in 12-meter diameter sphere Found: Observed data above 475 MeV are consistent with expected background A low energy excess below this energy
Genty (Nevis) REU Presentations August 1, 2013 3 / 31
Excess events in 200 - 475 MeV neutrino energy region found by MiniBooNE. Variety of interpretations by many beyond the Standard Model physics including... 3+N Sterile Neutrinos ...but could be misidentified νµ → can not distinguish e− and γ signal MicroBooNE detector proposed to study even lower ν energy
Events/MeV 0.2 0.4 0.6 Events/MeV 0.2 0.4 0.6
+/-
µ from
e
ν &
e
ν
+/-
from K
e
ν &
e
ν from K
e
ν &
e
ν misid π γ N → ∆ dirt
Best Fit (E>475MeV)
Fit Region (GeV)
QE ν
E 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Events/MeV
0.0 0.1 0.2 0.3 3.0 1.5
Data - expected background Best Fit
2
=1.0eV
2
m ∆ =0.004, θ 2
2
sin
2
=0.3eV
2
m ∆ =0.03, θ 2
2
sin
the MiniBooNE Search for ¯ νµ → ¯ νe Oscillations”, Phys. Rev. Lett. 105, 181801 (2010)
Genty (Nevis) REU Presentations August 1, 2013 4 / 31
Specifications 170 ton liquid argon cryostat Time Projection Chamber (TPC) with 3 wireplanes 32-40, 8-inch photomultiplier tubes Will study νe/¯ νe appearance
LAr
Genty (Nevis) REU Presentations August 1, 2013 5 / 31
LArSoft is a complete set of simulation, reconstruction, and analysis tools for liquid argon detectors Whole detector simulated by GEANT4 (LArG4) Neutrino beams simulated by GENIE, all other particles possible Reconstruction chain developed Event display for three wireplane, can investigate reconstructed parameters against truth...
Genty (Nevis) REU Presentations August 1, 2013 6 / 31
Reconstructing neutrino interactions inside MicroBooNE
Clustering
Hits are signal vs time information from a calibrated Wire object and looks for peaks that indicate real energy deposition occurred Clustering algorithms identify reconstructed wire hits which are correlated both spatially and temporally DBSCAN and Fuzzy Clustering are two such algorithms
Energy
Total visible energy deposited on TPC from e− showers
Raw Data Hits Clusters Wires
Calibrated Data
2D/3D Tracks
Genty (Nevis) REU Presentations August 1, 2013 7 / 31
1
Generate νe events filter for 1e− + 1p final states, simple event topology
2
I wrote a LArSoft module, MCHitter, to calculate purity and efficiency of reconstructed clusters
3
Compare DBSCAN, FuzzyCluster
Purity Measures How much of a cluster is composed
If less than 1: clustering algorithm could not distinguish true particle hits from one another Efficiency Measures How many of all hits the particle generated are in a specific cluster If less than 1: algorithm failed to group the hits created by the particle into a single cluster
Genty (Nevis) REU Presentations August 1, 2013 8 / 31
PuritiesComb_fuzzy_cut
Entries 2897
Purity 0.2 0.4 0.6 0.8 1 Frequency 0.05 0.1 0.15 0.2 0.25 0.3
PuritiesComb_fuzzy_cut
Entries 2897
PuritiesComb_fuzzy_cut
PuritiesComb_fuzzy_cut
Entries 2897
EfficienciesComb_fuzzy_cutEntries 2897
Efficiency 0.2 0.4 0.6 0.8 1 Frequency 0.05 0.1 0.15 0.2 0.25 0.3
EfficienciesComb_fuzzy_cutEntries 2897
EfficienciesComb_fuzzy_cut
EfficienciesComb_fuzzy_cutEntries 2897
PuritiesComb_db_cut
Entries 2747
Purity 0.2 0.4 0.6 0.8 1 Frequency 0.05 0.1 0.15 0.2 0.25 0.3
PuritiesComb_db_cut
Entries 2747
PuritiesComb_db_cut
PuritiesComb_db_cut
Entries 2747
EfficienciesComb_db_cut
Entries 2747
Efficiency 0.2 0.4 0.6 0.8 1 Frequency 0.05 0.1 0.15 0.2 0.25 0.3
EfficienciesComb_db_cut
Entries 2747
EfficienciesComb_db_cut
EfficienciesComb_db_cut
Entries 2747
Genty (Nevis) REU Presentations August 1, 2013 9 / 31
1 2 3 4 5 1 2 3 4 5 ADC Counts ×106 True e− Energy (GeV) Counts vs. Energy
Visible energy fraction ∼ 45% Reconstructed ADC counts from hits scaled linearly with true e− energy Important for detector calibration
Entries 1000 Mean 0.431 RMS 0.01129
0.2 0.4 0.6 0.8 1 Events 50 100 150 200 250 300 350 400 450
Entries 1000 Mean 0.431 RMS 0.01129
Energy Fraction
1 GeV Electron
Entries 1000 Mean 0.411 RMS 0.03992
Ionization/True Energy 0.2 0.4 0.6 0.8 1 Events 20 40 60 80 100 120 140
Entries 1000 Mean 0.411 RMS 0.03992
0.5 - 5.0 GeV Electron
Genty (Nevis) REU Presentations August 1, 2013 10 / 31
Phototube array 32-40, 8-inch photomultiplier array located behind TPC wireplanes will collect Argon scintillation The primary importance of the optical systems is for triggering on events Optical information can also contribute to event reconstruction I tested a R5912 8-inch PMT, similar to the ones used in MicroBooNE minus the wavelength shifting coating and single coaxial input. Will be used to study read out electronics
Genty (Nevis) REU Presentations August 1, 2013 11 / 31
Definition Phototube gain is the ratio of secondary electrons collected on the anode to primary electrons ejected from cathode → amplification factor Procedure
1
Pulse PMT with blue LED @ 100 Hz
2
Record mean (µv) peak height and standard deviation (σv) of output voltages, and
triggers
3
Repeat for different input voltages G: Gain Ns: Number of secondary electrons Np: Number of primary electrons G ≡ Ns Np µv = CGNp σv = CG
⇒ Np = (µv/σv)2 and Ns =
eR ⇒ G =
eR σv µv 2
Genty (Nevis) REU Presentations August 1, 2013 12 / 31
1 2 3 4 5 6 7 1100 1200 1300 1400 1500 1600 1700 1800 Gain ×107 Voltage (V) Gain vs. Voltage
(100 mV, 20 ns)/DIV (200 mV, 20 ns)/DIV (300 mV, 20 ns)/DIV
Took data at different oscilloscope precisions (window size)
Optimal operating voltage is 1500 V Interesting gain response at high voltages
20 40 60 80 100 1100 1200 1300 1400 1500 1600 1700 1800 Np Voltage (V) Primary Electrons vs. Voltage
(100 mV, 20 ns)/DIV (200 mV, 20 ns)/DIV (300 mV, 20 ns)/DIV
Number of primary electrons deviates as function of input voltage Should remain constant Photocathode electrons non-poissonian?
Genty (Nevis) REU Presentations August 1, 2013 13 / 31
1 2 3 4 5 6 7 5 10 15 20 25 30 35 40 45 Gain ×107 Time (min) Gain vs. Time
Variation in gain at constant 1500 V over 40 minutes Spread is about ± one unit around 4 × 107
1 2 3 4 5 6 7 1100 1200 1300 1400 1500 1600 1700 1800 Gain ×107 Voltage (V) Gain vs. Voltage
Measurement Average
Every measurement over 1.5 week period plotted in red, blue square is the average as estimate of systematic uncertainty Largest source of systematic uncertainty is the oscilloscope precision
Genty (Nevis) REU Presentations August 1, 2013 14 / 31
A current test of MicroBooNE’s optical system is called Bo. Bo is a liquid argon test chamber for MicroBooNE photomultipliers, cold electronics, high voltage system and much more. An issue arose during electronics testing with the splitter used to split the HV input from the PMT signal, signal reflection observed in shaper
R C1 C2 L Vin Vout
A simple circuit was used to study the PMT signal reflection between the splitting capacitor C2 and the PMT base
Genty (Nevis) REU Presentations August 1, 2013 15 / 31
Why is there reflection? Impedance differentials along the length of the circuit reflect EM signals Splitting circuit, and 50 Ω cable are at different impendances. Toy Circuit Varying L controls the timescale of reflection Varying C2 controls amplitude No ringing is observed when: τcircuit = RcableC2 ≫ τtravel = L vsignal
**Much greater ∼ 3-5 times
vsignal = 1 foot/1.5 ns L = 4 → 20 meters C2 = 1 nF → 10 nF
Genty (Nevis) REU Presentations August 1, 2013 16 / 31
5 10 15 20 25 30
0.5 1 1.5 Voltage (mV) Time (µs) Short Cable - Shaper
5 10 15 20 25 30
0.5 1 1.5 Voltage (mV) Time (µs) Long Cable - Shaper
τcircuit = 50 Ω · 1 nF = 50 ns Short cable L = 4 m τcircuit > τtravel = 4 m · 1.5 ns/foot ∼ 20 ns → no ringing Long cable L = 20 m τcircuit ≯ τtravel = 10 m · 1.5 ns/foot ∼ 100 ns → yes ringing
Genty (Nevis) REU Presentations August 1, 2013 17 / 31
Increase τcircuit by C2 → 10 nF
10 20 30 40
0.5 1 1.5 Voltage (mV) Time (×100ns) Short Cable - Scope
5 10 15 20 25 30
0.5 1 1.5 2 2.5 Voltage (mV) Time (×100ns) Long Cable - Scope 10 20 30 40
0.5 1 1.5 Voltage (mV) Time (µs) Short Cable - Shaper 10 20 30 40
0.5 1 1.5 Voltage (mV) Time (µs) Long Cable - Shaper
Genty (Nevis) REU Presentations August 1, 2013 18 / 31
Results Bo circuit sees ringing in the shaper output when it shouldn’t, with same parameters are test circuit Bo circuit has another capacitor in series with the splitting capacitance reducing effective capacitance Bo circuit has high voltage across the splitting capacitance further reducing capacitance
PMT + HV in Anode x1 Anode x0.1
10nF (2kV) 10k 500
room temperature
10nF 16k (2kV)
GND
10M 10k
GND
450 10nF | |
Capacitance in MicroBooNE splitter circuit used with Bo is being increased!
Genty (Nevis) REU Presentations August 1, 2013 19 / 31
Procedure Use the controller module to trigger a pulse generator Feed the pulse to the RC circuit built for the ringing tests. This generates a narrow (few nanosecond) PMT-like pulse of variable charge depending on the pulse amplitude. Feed into the shaper and read out through the FEM Decoder & Analysis Module pmtbaseline
Pedestal calculation and subtraction per shaper channel Calculate signal peak and area for pulse recon.
Trigger Module Pulse Generator RC
Circuit Shaper PC
Beam Gate
FEM
Genty (Nevis) REU Presentations August 1, 2013 20 / 31
Pedestal mean and standard deviation calculated from the first 5 points of the beam gate sample. Mean, RMS plotted versus FEM channel number
Channel 5 10 15 20 25 30 35 40 ADC 2040 2045 2050 2055 2060
Entries 400000 Mean x 20 Mean y 2049 RMS x 11.54 RMS y 3.248 1000 2000 3000 4000 5000 6000 7000 8000 Entries 400000 Mean x 20 Mean y 2049 RMS x 11.54 RMS y 3.248
Pedestal Mean
Channel 5 10 15 20 25 30 35 40 ADC 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
Entries 400000 Mean x 20 Mean y 0.3674 RMS x 11.54 RMS y 0.1782 1000 2000 3000 4000 5000 6000 7000 8000 Entries 400000 Mean x 20 Mean y 0.3674 RMS x 11.54 RMS y 0.1782
Pedestal RMS
Pedestal mean ∼ 2049, pedestal varies over 10 ADC counts Pedestal RMS ∼ 0.37
Genty (Nevis) REU Presentations August 1, 2013 21 / 31
Charge 100 150 200 250 300 350 400 450 500 550 600 Pulse Count 200 400 600 800 1000
Integrated Charge Ch. 4
Peak Amplitude 70 72 74 76 78 80 82 Events 200 400 600 800 1000 1200 1400 1600 1800 2000 2200
Peak Heights Ch. 4
Distribution of integrated charge. Increasing in amplitude to the right by 500 mV input. High energy tail
2/9 distribution of peak heights, another estimator of pulse energy. Would expect peak heights to be gaussian as well but because of a digitization effect there are 3 distributions
Genty (Nevis) REU Presentations August 1, 2013 22 / 31
Pulse Amplitude 24 25 26 27 28 29 30 Pulse Count 500 1000 1500 2000 2500 3000 3500
Pulse Height Division
Make 3 cuts on pulse amplitude distribution Find max bin, look ±0.5 as estimate
Charge 140 145 150 155 160 165 170 175 180 185 Pulse Count 100 200 300 400 500 600 700 800 900
Charge: Amp=4.0
Charge distribution split by peak cuts
Genty (Nevis) REU Presentations August 1, 2013 23 / 31
Amplitude 4 5 6 7 8 9 10 11 12 Middle Mean Fitted Charge 150 200 250 300 350 400 450 500 / ndf
2
χ 255.1 / 7 p0 0.2447 ±
p1 0.02926 ± 43.64 / ndf
2
χ 255.1 / 7 p0 0.2447 ±
p1 0.02926 ± 43.64
Middle Charge Sum Ch. 4
For each input A, plot mean Linear as function of input A
Amplitude 4 5 6 7 8 9 10 11 12
2
χ
1 2 3 4 5 6
2
χ All Middle
Magenta: middle peak fits Blue: fits without cuts For each input A, plot χ2 goodness
Cuts are indication better selection
Genty (Nevis) REU Presentations August 1, 2013 24 / 31
Repeat over all shaper channels
40 42 44 46 48 50 2 4 6 8 10 12 14 Slope of Fitted Mean Charge Shaper Channel Number Mean Fitted Charge vs. Channel
Slope of fitted mean plotted over channel number
2 4 6 8 10 12 14 Fitted Y-intercept Charge Shaper Channel Number Y-intercept Fitted vs. Channel
Y-intercept of fitted mean plotted
Shows non linearity at low energy (A< 4)
Genty (Nevis) REU Presentations August 1, 2013 25 / 31
Genty (Nevis) REU Presentations August 1, 2013 26 / 31
Genty (Nevis) REU Presentations August 1, 2013 27 / 31
Fermilab Booster Decay Pipe 50 m Target and Horn Absorber Dirt Detector
1
8 GeV protons produced in booster
2
Impinge on Beryllium target, magnetic horn focusses π± & K ± depending on neutrino mode
3
Mesons decay via → µ± + ¯ νµ/νµ channel, some µ± → e± + ¯ νµ/νµ + νe/¯ νe
4
Absorber filters charged leptons
Genty (Nevis) REU Presentations August 1, 2013 28 / 31
Liquid argon TPCs have a low energy resolution at a few MeV, far below the hundreds of MeV threshold on MiniBooNE, and will be able to resolve the size of the signal at lower energies. MiniBooNE could not differentiate between electrons and photons, a TPC can “see” the difference → e− connected to a primary vertex which is singly ionizing, γ are doubly ionizing and have a gap between vertex Detector R&D for larger TPC experiments to search for CP violation in neutrino sector
TPC wireplanes: red and green “induction” planes ±60◦ to vertical, Blue parallel “collection” plane
Genty (Nevis) REU Presentations August 1, 2013 29 / 31
1
Generate single electron, muon and uniform flux CC νe events with singles.fcl and GENIE. Filter for 1e− + 1p final states
2
Reconstruct clusters with modified uboone offline .fcl script
3
Feed to a module I wrote, MCHitter, to calculate purity and efficiency of reconstructed clusters
4
Compare DBSCAN, FuzzyCluster
Genty (Nevis) REU Presentations August 1, 2013 30 / 31
Purity = # of hits from trackID in cluster total # of hits in cluster
e− π−
Measures How much of a cluster is composed
If less than 1: clustering algorithm could not distinguish true particle hits from one another Efficiency = # of hits from trackID in cluster total # of hits for that trackID
e− π−
Measures How many of all hits the particle generated are in a specific cluster If less than 1: algorithm failed to group the hits created by the particle into a single cluster
Genty (Nevis) REU Presentations August 1, 2013 31 / 31