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Daniel Miner <[email protected]> Brandeis University, University of Rochester Summer 2
Detection and Analysis of StoppingMuons Using a Compact Digital PulseProcessor
Daniel MinerSummer 2003 REU at
University of Rochester
Daniel Miner <[email protected]> Brandeis University, University of Rochester Summer 2
What Does Waveform Digitizing Do?• Turns an analog signal into a set of discrete-valued samples taken at
regular time intervals• Must be digitized frequently enough to capture waveform features• Discrete-valued samples are mathematically easy to work with
Why Digital Pulse Processing?• Easily interfaced with a computer for analysis• Can store data and process later• One can extract more features of the signal using less bulky
equipment than with analog methods
The blue line represents theanalog signal, and the reddots represent the digitalsamples.
Transient 18Y
X60.0 80.0 100.0 120.0 140.0 160.0 180.0 200.0
1950.0
2.0E+3
2050.0
2100.0
2150.0 Transient 18
Daniel Miner <[email protected]> Brandeis University, University of Rochester Summer 2
The DDC-1 Digital Pulse Processor
• 12 bit ADC (Analog to Digital Converter) – converts an analog
voltage to a discrete value between 0 and 4095
• Run at 48 MHz
• Uses a looping buffer of 1024 samples
Designed and built by Wojtek Skulski
USBprocessor
FPGA
Signal IN
ADC 48MHz 12 bits
Variablegain amp
USBconnector
Daniel Miner <[email protected]> Brandeis University, University of Rochester Summer 2
How Can We Demonstrate the Advantagesof Digital Signal processing?
•A great deal ofinformation can beextracted from theobservation of muons•With analog techniques, acomparable experimentwould require severalequipment crates•All the information can beobtained with the simpledigital setup shown
Detector assemblyHV PS
Experiment controland data display
PC
DDC-1 digitizer board
Daniel Miner <[email protected]> Brandeis University, University of Rochester Summer 2
What are Muons?
• Similar to electrons, except with much higher mass (about 200x
electron mass)
• Created in the upper atmosphere by cosmic rays interactions
• Mean lifetime at rest of 2.2 microseconds
• Decay into an electron and two neutrinos
• Can be stopped by solid objects or dense liquids
Daniel Miner <[email protected]> Brandeis University, University of Rochester Summer 2
Stopping Muons in a Scintillator
Muon excites scintillatormolecules, causing photonemission along path
Non-stopping muonsMuon excites for somedistance in scintillator,stops, then decays,emitting electron whichexcites scintillator
Stopping muons
Transient 3183Y
X0.0 100.0 200.0 300.0 400.0 500.0 600.0 700.0 800.0 900.0 1.0E+3
1750.0
1800.0
1850.0
1900.0
1950.0
2.0E+3
2050.0
2100.0
2150.0 Transient 3183
MuonMuon
Electron
Transient 6Y
X0.0 100.0 200.0 300.0 400.0 500.0 600.0 700.0 800.0 900.0 1.0E+3
0.0
500.0
1.0E+3
1500.0
2.0E+3
Transient 6
Daniel Miner <[email protected]> Brandeis University, University of Rochester Summer 2
The Experimental Setup
ScintillatorLight-proofenclosure
Photomultipliertube
HV PowerSupply DDC-1
Computer
USBCable
•Scintillator: Bicron BC-400 plastic,
6” X 5” cylinder
•Photomultiplier tube: Hamamatsu
R1847-13, 2 inch
•HV: Tennelec TC 952, -1000 V
•Run for approximately 5 and a
half days
Daniel Miner <[email protected]> Brandeis University, University of Rochester Summer 2
MuonDAQ by Daniel Minerand Wojtek Skulski
DAQ and Offline Processing• Recorded Data:
-Double pulse transients-Single pulse energy-Primary double pulse energy-Secondary double pulse energy-Delay between primary and secondarypulse for double pulses
• Re-processes double pulses with morestringent criteria
• Smooths plots with moving average filter• Plots normalized difference between two
signals or histograms• Integrates area under pulse with
variable scaling factor
MuonProcess by Daniel Miner
Daniel Miner <[email protected]> Brandeis University, University of Rochester Summer 2
Binned Single Energy, bin 10Y
X0.0 50.0 100.0 150.0 200.0 250.0 300.0
0.0
5.0E+3
1.0E+4
1.5E+4
Binned Single Energy, bin 10
Single Pulse Energy DistributionRaw single pulse energy distribution
Shape is result of :•MIP peak (to be explained later)•Geometry of scintillator•Background noise distribution•Energy resolution of scintillator
MuonMIP peak
Daniel Miner <[email protected]> Brandeis University, University of Rochester Summer 2
Calibrated Single Pulse Energy Disrtibution
-20
0
20
40
60
80
100
120
140
160
0 10 20 30 40 50 60 70
Energy (MeV)
Norm
aliz
ed C
ount
s
Calibrated normalized experimental energydistribution
Energy Calibration• Cosmic muons that don’t stop can be approximated as MIP’s –
Minimum Ionizing Particles• MIP energy loss through the plastic scintillator is 2.3 MeV / cm• MIP energy distribution is path length distribution multiplied by MIP
energy loss• MIP peak is a good calibration point
31 MeV MIPpeak
Monte Carlo simulationsoftware was written (by DanielMiner and Wojtek Skulski) andused to determine the energyloss distribution and the energyof the MIP peak.
Daniel Miner <[email protected]> Brandeis University, University of Rochester Summer 2
Calibrated Stopping Muon Energy DistributionStopping Muon Pulse Energy Distributions
-20
0
20
40
60
80
100
120
140
160
180
0 10 20 30 40 50 60 70 80 90 100
Energy (MeV)
Cou
nts
Calibrated primary (stopping) pulseenergy distribution
Calibrated secondary (decay) pulseenergy distribution
The primary distribution is the result of the energy loss distribution forparticles at the endpoint of the Bethe-Bloch equation range. Thesecondary distribution is the electron energy spectrum of beta decayfrom muons.
31 Mev MIPPeak
53 MeV MaximumDecay Energy
Muon
Electron
The electron decayendpoint at 53 MeV maybe clearly observed.
Daniel Miner <[email protected]> Brandeis University, University of Rochester Summer 2
Normalized Decay Time Distribution
-0.5
0
0.5
1
1.5
2
0 1 2 3 4 5 6 7 8 9 10
Delta T (microseconds)
Nor
mal
ized
Cou
nt
Normalized Fit Delta T
Normalized Experimental Delta T
~2.2 MicrosecondsMean Lifetime
ArtifactSpike
Decay Time Distribution
Mean Delta T obtained: 2.12 + 0.04 microsecondsAccepted Delta T: 2.19703 + 0.00004 microseconds
Daniel Miner <[email protected]> Brandeis University, University of Rochester Summer 2
Conclusions• Cosmic muons were observed and positively identified by their
decay time• Energy distributions were obtained for both MIP muons, stopping
muons, and decay electrons• The experiment, assembled essentially from scratch, performed
beyond expectations• The digital technology used has proved its capability and versatility
Developments by Daniel Miner• Co-developed data acquisition (DAQ) software• Developed pulse detection and sorting algorithms• Co-developed data object management system• Developed offline data processing software• Co-developed Monte Carlo simulation system• Constructed experimental setup• Oversaw and performed data collection and calibration
Daniel Miner <[email protected]> Brandeis University, University of Rochester Summer 2
Acknowledgements
• Wojtek Skulski• Frank Wolfs• Jan Toke• Erik Bjorn Johnson