ZukaiWang University of Virginia Zukai Wang Monopoles In ...

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

3P.A.M Dirac (1902-1984) Video obtained at: http://moedal.web.cern.ch/

Monopoles In NOvAZukai Wang

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

To accommodate magnetic monopoles in classic electromagnetism,

let’s rewrite the Maxwell Equations in a symmetric way:

Scalar

pseudoscalar

vector

pseudovector

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…

Rutherford Scattering

Correction by considering the electron spin (Y. Kazama, C. N. Yang, and

A. S. Goldhaber, Phys. Rev. D 15, 2287 (1977) )

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.

Bethe-Bloch Analog (Ahlen Formula)

Generalized Lindhard Theory

: Monopole Physics: Energy Loss

Geant4 simulation

of monopole

transportation in

Silicon.

And the a linear

interpolation was

implemented to

the unknown

region.

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

Neutrino Oscillation

Zukai Wang Monopoles In NOvA 14

http://arxiv.org/abs/1006.2359

15.6m x 15.6m x 66.9m

14 kTon

344,064 Cells

3.9 cm x 6.0cm x 15.6 cm

ΝΟνΑ Monopole Search Strategy

2. Look for sub-luminal, penetrating particles

• Covers the low-ββββ range: ββββ < 10-2

dE/dx dt/dx

Zukai Wang

Monopoles In NOvA

ASIC: Application Specific Integrated Circuit

R = 380 ns

F = 7000 ns

: Detector Response

Calibration: Single Cell Hit of a slow Monopole

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

Simulation: Event Display of High Energy Muon

PDG: 13

CosZ: 0.95

PhiXY: 130

X0: 600cm

Y0: 600cm

P0: 200GeV

Simulation: Event Display of Single Monopole

CosZ: 0.95

PhiXY: 130

X0: 600cm

Y0: 600cm

CosZ: 0.95

PhiXY: 130

X0: 600cm

Y0: 600cm

CosZ: 0.95

PhiXY: 130

X0: 600cm

Y0: 600cm

»140-200 Buffer Node Computers

180 Data Concentrator Modules

11,160 Front End Boards

Buffer NodesBuffer Nodes

Buffer Nodes

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

Triggered

Data Output Data

DCM 1DCM 1

DCM 1DCMs

FEBFEBFEBFEBFEBFEBFEB

Zero Suppressed

(6-8MeV/cell)

FEBFEBFEBFEBFEBFEBFEB

Global Trigger

ProcessorBeam Spill Indicator

(Async from FNAL @ .5-.9Hz)

Calib. Pulser ( 50-91Hz)

11520 FEBs

(368,4600 det. channels)

200 Buffer Nodes

(3200 Compute Cores)

Shared Memory

DDT event stack

30Monopoles In NOvA

Zukai Wang

Shared Milliblock

Hit Unpacker

Hit Producer

Event DisplayEvent

Display

Hit SorterHit Sorter Hit SlicerHit Slicer

TrackingTracking

CalibrationCalibration

Slow Monopoles

NuMuNuMu

ClusteringClustering

SupernovaSupernova

NuENuE

Fast Monopoles

Live Data

Simulated

Data (MC)

a working version exists

close to a working version

under development

Trigger Signal

Duyang

Martin

Andrew

EvanMartin

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.

Monopoles In NOvA

Zukai Wang

Time Slicer

Remove Noise

Space Slicer

Nue Calibration

TDC Sorter

……

Global Pattern

Recognition

Time Slicer

Remove Noise

Space Slicer

Nue Calibration

TDC Sorter

Monopoles Supernova ……

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

DCM Boundary

Algorithm Illustration

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.

Illustration: Cosmic Raw Hits

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

No Slow Monopoles on this floor

500 µs of cosmics

“Ground Floor” of

Hough Space

Monopoles In NOvA

Zukai Wang

Illustration: Reconstructed 2D Tracks

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

# of total tracks # of tracks longer than 2 planes

MC Truth 4840 2987

Reco Info 3272 2987(100% reconstructed!)

Limit: ΝΟνΑ Potential: Overburden

Vertical Overburden:

6” barite: 68.3 g/cm2

55” concrete: 347.9 g/cm2

atmosphere: 1030.0 g/cm2

Limit: ΝΟνΑ Potential

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

• 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

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,

• UVA Folks (Craig Dukes, Craig Group, Ralf

Ehrlich, Martin Frank, etc)

Back Up: Problem 1: Split Tracks

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

Partitioned by DCM

boundaries

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)

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.

v × c × d

Zukai Wang

Algorithm: General Organizing

Transform

divisions.

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

Hits associated

with a shower

noiseA hit caused

by a cosmic

Back Up: Problem 2: Fake Tracks

Hits associated

with a shower

noiseA hit caused

by a cosmic

Accidentally, these hits meet the timing

requirements to be filled into the same

velocity grid.

Back Up: Path Length Inside Cell

200,000 Isotropic generated monopole’s distribution.

Back Up:Number of Cells Hits per Monopole in FD

Back Up:Number of Saturated Cells Hits per

Monopole in FD

Note: assuming hits with PE > 1500 will be saturated, without

considering attenuation. Monopoles In NOvAZukai Wang

Back Up: Energy Deposit per Monopole in FD

Back Up: Path Length Inside FD

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:

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.

• 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

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

Quickly identifying all hits from each straight track;

Zukai Wang

Quickly pick out the monopole tracks among them (in

case there are some);

Zukai Wang

Quickly pick out the monopole tracks among them (in

case there are some);

Quickly generating a trigger window for each track.

Zukai Wang

Partitioned by DCM

boundaries

Zukai Wang

Partitioned by DCM

boundaries

Transform

divisions.

Zukai Wang

Partitioned by DCM

boundaries

Transform

divisions.

c × d × v✗✓✓

Above significance

threshold

Below significance

threshold

Zukai Wang

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

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

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