Zukai Wang
University of Virginia
1Monopoles In NOvAZukai Wang
• Introduction to Magnetic Monopoles
• Motivation of Searching Magnetic Monopoles
• NOνA Project and NOνA Far Detector
• Simulation of Magnetic Monopole
• Data Driven Trigger
• NOνA’s Potential on monopole
• Outlook
2Monopoles In NOvAZukai Wang
3P.A.M Dirac (1902-1984) Video obtained at: http://moedal.web.cern.ch/
Monopoles In NOvAZukai Wang
4
Assume an electron is transported along a closed path enclosing the Dirac String,
the phase transition of its wave function should be:
Dirac ChargeMonopoles In NOvAZukai Wang
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6Monopoles In NOvAZukai Wang
7
To accommodate magnetic monopoles in classic electromagnetism,
let’s rewrite the Maxwell Equations in a symmetric way:
Scalar
pseudoscalar
vector
pseudovector
Monopoles In NOvAZukai Wang
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If you accept the idea of magnetic charge, you may notice
the following Duality Transforms are completely trivial:
CP violation is a necessary consequence of the
existence of a particle carrying both electric charge and
magnetic charge.
It is just our
convention to say a
particle possessing
an electric charge or
magnetic charge.
What really matters
is the fraction…
Monopoles In NOvAZukai Wang
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Rutherford Scattering
Correction by considering the electron spin (Y. Kazama, C. N. Yang, and
A. S. Goldhaber, Phys. Rev. D 15, 2287 (1977) )
Monopoles In NOvAZukai Wang
Energy loss for monopoles of
a single Dirac charge in Silicon.
experimental data open circle
for protons in Silicon are also
shown. The solid curves are
calculated from the
corresponding theoretical
work mentioned in
parentheses. The solid curve
inside the shaded region
shows the Ahlen and Kinoshita
result for monopoles. The
figure is reprinted from D. E.
Groom’s 1986 review article.
10Monopoles In NOvAZukai Wang
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Bethe-Bloch Analog (Ahlen Formula)
Generalized Lindhard Theory
Monopoles In NOvAZukai Wang
: Monopole Physics: Energy Loss
12
Geant4 simulation
of monopole
transportation in
Silicon.
And the a linear
interpolation was
implemented to
the unknown
region.
Monopoles In NOvAZukai Wang
D.E. Groom, PHYSICS REPORTS
(Review Section of Physics Letters)
140. No.6(1986) 323-373
Minimum Ionizing
Simulation: Energy Loss of Monopole:
In All Related Material
13Monopoles In NOvAZukai Wang
Neutrino Oscillation
Zukai Wang Monopoles In NOvA 14
http://arxiv.org/abs/1006.2359
15Monopoles In NOvAZukai Wang
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15.6m x 15.6m x 66.9m
14 kTon
344,064 Cells
Monopoles In NOvAZukai Wang
17Monopoles In NOvAZukai Wang
18Monopoles In NOvAZukai Wang
19Monopoles In NOvAZukai Wang
20Monopoles In NOvAZukai Wang
21Monopoles In NOvAZukai Wang
3.9 cm x 6.0cm x 15.6 cm
ΝΟνΑ Monopole Search Strategy
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2. Look for sub-luminal, penetrating particles
• Covers the low-ββββ range: ββββ < 10-2
dE/dx dt/dx
Zukai Wang
Monopoles In NOvA
23
ASIC: Application Specific Integrated Circuit
R = 380 ns
F = 7000 ns
Monopoles In NOvAZukai Wang
: Detector Response
24Monopoles In NOvAZukai Wang
Calibration: Single Cell Hit of a slow Monopole
25
Illustration of APD response of a monopole with passing
through a cell horizontally described by an analytical expression.
F = Fall Time = 7000ns
R = Rise Time= 380ns
Monopoles In NOvAZukai Wang
Simulation: Event Display of High Energy Muon
26
PDG: 13
CosZ: 0.95
PhiXY: 130
X0: 600cm
Y0: 600cm
Z0: 0
P0: 200GeV
Monopoles In NOvAZukai Wang
Simulation: Event Display of Single Monopole
PDG:
CosZ: 0.95
PhiXY: 130
X0: 600cm
Y0: 600cm
Z0: 0
27Monopoles In NOvAZukai Wang
Simulation: Event Display of Single Monopole
28
PDG:
CosZ: 0.95
PhiXY: 130
X0: 600cm
Y0: 600cm
Z0: 0
Monopoles In NOvAZukai Wang
Simulation: Event Display of Single Monopole
29
PDG:
CosZ: 0.95
PhiXY: 130
X0: 600cm
Y0: 600cm
Z0: 0
Monopoles In NOvAZukai Wang
»140-200 Buffer Node Computers
180 Data Concentrator Modules
11,160 Front End Boards
Buffer NodesBuffer Nodes
Buffer NodesBuffer Nodes
Buffer NodesBuffer Nodes
Buffer Nodes
Data
Buffer
Data
Buffer
5ms data
blocks
Data Logger
ARTDAQ Data Driven Triggers
SystemARTDAQ-1
Processor
ARTDAQ-2
Processor
ARTDAQ-N
Processor….
Event builder
Data Slice Pointer Table
Data Time Window Search
Trigger Reception
Gra
nd
Trig
ge
r O
R
Da
taD
ata
Triggered
Data Output Data
Min
imu
m B
ias
0.7
5G
B/S
Str
ea
m
DCM 1DCM 1
DCM 1DCM 1
DCM 1DCMs
CO
tSE
the
rne
t 1
Gb
/s
FEBFEBFEBFEBFEBFEBFEB
Zero Suppressed
at
(6-8MeV/cell)
FEBFEBFEBFEBFEBFEBFEB
Global Trigger
ProcessorBeam Spill Indicator
(Async from FNAL @ .5-.9Hz)
Trig
ge
r B
roa
dca
st
Calib. Pulser ( 50-91Hz)
Da
ta D
riv
en
Trig
. D
eci
sio
ns
11520 FEBs
(368,4600 det. channels)
200 Buffer Nodes
(3200 Compute Cores)
Shared Memory
DDT event stack
30Monopoles In NOvA
Zukai Wang
Shared Milliblock
Shared Milliblock
Hit Unpacker
Hit Unpacker
Hit Producer
Hit Producer
Event DisplayEvent
Display
Hit SorterHit Sorter Hit SlicerHit Slicer
TrackingTracking
CalibrationCalibration
Slow Monopoles
Slow Monopoles
NuMuNuMu
ClusteringClustering
SupernovaSupernova
NuENuE
Fast Monopoles
Fast Monopoles
Live Data
Simulated
Data (MC)
a working version exists
close to a working version
under development
Trigger Signal
Duyang
Martin
Andrew
Andrew
Alec
Zukai
Zukai
Zukai
Brian
Zukai
Brian
Jan
Jan
EvanMartin
Gavin
from M. Frank’s talk in NOvA Collaboration Mtg Jan 2013Monopoles In NOvA 31Zukai Wang
• “3D” Hough Transform
• Take all pairs of hits and find three voting
parameters for each.
• DOCA
• cosθ
• 1/v
• In this 3D Hough space monopoles are
identified as clusters of points, “noise” is
randomly spread out
• Ordinary straight
track reconstruction
algorithm
• This additional
parameter implies a
timing cut in
recognizing a track
with certain velocity
Through-going track.
Background pair.
32
Monopoles In NOvA
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Zukai Wang
33
Time Slicer
Remove Noise
Space Slicer
Nue Calibration
TDC Sorter
……
Monopoles In NOvAZukai Wang
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Global Pattern
Recognition
Time Slicer
Remove Noise
Space Slicer
Nue Calibration
TDC Sorter
Monopoles Supernova ……
Monopoles In NOvAZukai Wang
Making Pairs
• Looping over all hits combinations
• Calculating the voting parameters for each pair
Partitioning• Partition by DCM and Time Slice: this step reduces the
number of combinations
Peak Identification
• Transform results of each pair are put into corresponding containers
• Making selections of each container to register a peak(track)
Monopoles In NOvA 35Zukai Wang
Monopoles In NOvA 36Zukai Wang
Monopoles In NOvA 37Zukai Wang
DCM Boundary
Algorithm Illustration
38
Here is an example of simulated cosmic events in
500 µs, containing ~10,000 hits.
Our goal is to quickly pick out the all the hits
belonging to any track.
Monopoles In NOvAZukai Wang
Illustration: Cosmic Raw Hits
39Monopoles In NOvAZukai Wang
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Combinations with Vpro > 7ns/cm have been cut off (supposed to
contain all hits of cosmic rays).Monopoles In NOvAZukai Wang
Signature of a Slow Monopole track
“Ground Floor” of Hough Space
41
No Slow Monopoles on this floor
500 µs of cosmics
“Ground Floor” of
Hough Space
Monopoles In NOvA
Zukai Wang
Illustration: Reconstructed 2D Tracks
42Monopoles In NOvAZukai Wang
Result
• A test using a cosmic simulation of 50 ms live
time has been done: containing ~5,000 cosmic
tracks with 1,004,344 hits in FD.
• Timing & Overall Performance:
Finds all tracks that hit more than 2 planes
~5 times faster than previous reconstruction module
43
# of total tracks # of tracks longer than 2 planes
MC Truth 4840 2987
Reco Info 3272 2987(100% reconstructed!)
Monopoles In NOvAZukai Wang
Limit: ΝΟνΑ Potential: Overburden
Vertical Overburden:
6” barite: 68.3 g/cm2
55” concrete: 347.9 g/cm2
atmosphere: 1030.0 g/cm2
Zukai Wang Monopoles In NOvA 44
Limit: ΝΟνΑ Potential
45
The ΝΟνΑ potential curve is generated with a toy MC with a simplified
calculation of energy loss of monopoles from outer space.Monopoles In NOvAZukai Wang
Sensitivity: ΝΟνΑ Potential
46Monopoles In NOvAZukai Wang
• Sensitivity goes as surface area: πFA, where F is the flux
• Our acceptance is not yet known: we hope we can do better for
80% for high-mass monopoles and perhaps half that for low-mass
• Eventually, if the acceptance is large enough, we can beat MACRO
• Should be able to beat SLIM for intermediate-mass monopoles
• Simulation: Overlay Mechanism;
• Reconstruction & Trigger: Current pattern
recognition package is still not fast enough;
• Efficiency Estimation
47Monopoles In NOvAZukai Wang
Acknowledgement
• Vladimir Ivanchenko: advices in using
Monopole package of Geant4
• Eric Katsavounidis: his PHD thesis(1995 in
Caltech) on MACRO and advices
• Fermilab Artists (Chris Green, Mark F Paterno,
etc)
• UVA Folks (Craig Dukes, Craig Group, Ralf
Ehrlich, Martin Frank, etc)
Zukai Wang Monopoles In NOvA 48
Back Up: Problem 1: Split Tracks
49Monopoles In NOvAZukai Wang
Back Up: Problem: Split Tracks
Monopoles In NOvA 50
No matter how loose
the binning is, you
always have a chance to
split the Hough peak.
To prevent looping over
all hits again, the
binning is pre-
determined.
Binning boundary
Zukai Wang
Potential Solution: Combining Grids
Corp The entire time slice
Division Division Division
Monopoles In NOvA 51
Partitioned by DCM
boundaries
Hough
Transform
Looping over each combination of cells in the
division, and combining all the ballots from all
divisions.
CompanyCompany Company
Each Hough result is put
into the cubic grids:
c × d × v✗✓✓
Above significance
threshold
regiment Combining only adjacent (let me explain this in the next slide)
grids
Below significance
threshold
Zukai Wang
Defining Adjacent Grids
• Now we have grids in the cube (v bins in vpro, etc), and each grid can be labeled as:
• The distance of the two grids and is defined as following:
• Two grids are adjacent to each other if their distance is below 4.
Monopoles In NOvA 52
v × c × d
Zukai Wang
Algorithm: General Organizing
Monopoles In NOvA 53
Hough
Transform
Looping over each combination of cells in the
division, and combining all the ballots from all
divisions.
CompanyCompany Company
Each Hough result is put
into the cubic grids:
c × d × v✗✓✓
Above significance
threshold
Below significance
threshold✓✓
regiment regiment
Aristophanes’ ProcessLet me explain later..
platoonplatoon
Platoon: hit list, which contains all the hits in a track (if perfectly done).
Zukai Wang
Back Up::Problem 2: Fake Tracks
54
noise
Hits associated
with a shower
noiseA hit caused
by a cosmic
Muon
Monopoles In NOvAZukai Wang
Back Up: Problem 2: Fake Tracks
55
noise
Hits associated
with a shower
noiseA hit caused
by a cosmic
Muon
Accidentally, these hits meet the timing
requirements to be filled into the same
velocity grid.
Monopoles In NOvAZukai Wang
Back Up: Path Length Inside Cell
56
200,000 Isotropic generated monopole’s distribution.
Monopoles In NOvAZukai Wang
Back Up:Number of Cells Hits per Monopole in FD
57
200,000 Isotropic generated monopole’s distribution.
Monopoles In NOvAZukai Wang
Back Up:Number of Saturated Cells Hits per
Monopole in FD
58
Note: assuming hits with PE > 1500 will be saturated, without
considering attenuation. Monopoles In NOvAZukai Wang
Back Up: Energy Deposit per Monopole in FD
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200,000 Isotropic generated monopole’s distribution.
Monopoles In NOvAZukai Wang
Back Up: Path Length Inside FD
60
200,000 Isotropic generated monopole’s distribution.
Monopoles In NOvAZukai Wang
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1 2 3 4 5 6
B 0.248 0.672 1.022 1.243 1.464 1.685
K 0.406 0.346 0.346 0.346 0.346 0.346
Mean Ionization Potential:
Shifting Parameters:
Monopoles In NOvAZukai Wang
62
Assuming the monopole passes through a degenerate Fermi gas of non-
interacting electrons (this assumption is applicable when the monopole is
slow enough: ):
as the monopole’s velocity decreases, fewer electrons of the Fermi sea
are “available” for ionizing.
Monopoles In NOvAZukai Wang
• Sensitivity roughly proportional to detector area
• Very high-mass monopoles come isotropically from
all sides, unlike cosmic rays, lower mass monopoles
from above
• The observed isotropic rate is: R = πFAε• F is the flux of monopoles (cm-2sr-1)
• A is the total detector area (cm2)
• ε is the detector efficiency, livetime, etc.
• What we are after is not R, but the flux F = R/πAε• If we see no monopoles assume R = 2.3 to get the
90% CL limit:
• F(90% CL) = 2.3 / πAε
Monopole Sensitivity
Zukai Wang
Monopoles In NOvA 63
Some areas
NOvA: 4290 m2
MACRO: 3482 m2
SLIM: 427 m2
OHYA: 2000 m2
• Assume each cell hit is a soldier…
Cell hit ID: 007……700
Monopoles In NOvA 64Zukai Wang
• Assume each cell hit is a soldier…
Monopoles In NOvA 65
Quickly identifying all hits from each straight track;
Zukai Wang
• Assume each cell hit is a soldier…
Monopoles In NOvA 66
Quickly identifying all hits from each straight track;
Quickly pick out the monopole tracks among them (in
case there are some);
Zukai Wang
• Assume each cell hit is a soldier…
Monopoles In NOvA 67
Quickly identifying all hits from each straight track;
Quickly pick out the monopole tracks among them (in
case there are some);
Quickly generating a trigger window for each track.
Zukai Wang
Corp The entire time slice
Division Division Division
Monopoles In NOvA 68
Partitioned by DCM
boundaries
Zukai Wang
Corp The entire time slice
Division Division Division
Monopoles In NOvA 69
Partitioned by DCM
boundaries
Hough
Transform
Looping over each combination of cells in the
division, and combining all the ballots from all
divisions.
Zukai Wang
Corp The entire time slice
Division Division Division
Monopoles In NOvA 70
Partitioned by DCM
boundaries
Hough
Transform
Looping over each combination of cells in the
division, and combining all the ballots from all
divisions.
CompanyCompany Company
Each Hough result is put
into the cubic grids:
c × d × v✗✓✓
Above significance
threshold
Below significance
threshold
Zukai Wang
Monopoles In NOvA 71
The statue of Aristophanes and Menander
Remember, the elements we pushed
back into the companies are pairs of
cell hits.
We need to pick out all the individual
hits from a regiment to form a
platoon.
The challenge is to avoid pushing back
a same hit twice. And this is achieved
by using “unordered_set”.
Zukai Wang
Monopoles In NOvA 72
0101101…0010001 000101111110 10111001
Hash function compares the unique id (64
bits) of every soldier:
Last 44 bits of TDC 12 bits: Plane 8 bits: Cell
Almost impossible for an ID collision of 2 hits in a
time slice.
Note: this is theoretically possible only when the
slice is longer than ……
Zukai Wang