Daniel Miner <dminer@brandeis.edu> 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 <dminer@brandeis.edu> 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 <dminer@brandeis.edu> 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 <dminer@brandeis.edu> 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 <dminer@brandeis.edu> 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 <dminer@brandeis.edu> 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 <dminer@brandeis.edu> 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 <dminer@brandeis.edu> 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 <dminer@brandeis.edu> 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 <dminer@brandeis.edu> 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 <dminer@brandeis.edu> 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 <dminer@brandeis.edu> 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 <dminer@brandeis.edu> 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 <dminer@brandeis.edu> Brandeis University, University of Rochester Summer 2

Acknowledgements

• Wojtek Skulski• Frank Wolfs• Jan Toke• Erik Bjorn Johnson