raghunath ganugapati(newt) && paolo desiati

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1 Raghunath Ganugapati(Newt) && Paolo Desiati Event Topology Studies fo etection of prompt muons in the dow oing muon flux IceCube Collaboration Meeting,March 23 rd ,2005,Berkeley

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Event Topology Studies for detection of prompt muons in the down going muon flux. IceCube Collaboration Meeting,March 23 rd ,2005,Berkeley. Raghunath Ganugapati(Newt) && Paolo Desiati. Detection With AMANDA-II. - PowerPoint PPT Presentation

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Page 1: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

1

Raghunath Ganugapati(Newt) && Paolo Desiati

Event Topology Studies for detection of prompt muons in the down going muon flux

IceCube Collaboration Meeting,March 23rd,2005,Berkeley

Page 2: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Detection With AMANDA-II

• Extra Terrestrial Neutrinos• High energy spectrum hypothesis d/dE ~ E-2

• Backgrounds

• Conventional Atmospheric µ , from decay of (π± , K± ) d/dE ~ E-3.7

• Possible components from

decay of atmospheric charmed particles. d/dE ~ E-2.7

Page 3: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Uncertainty in Prompt Lepton Cross Sections

• The uncertainty ~3 orders

• Need for accelerator data extrapolation

• Crossover between 40TeV and 3 PeV

ZhVd

AMANDA II (neutrinos)

Page 4: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Neutrino Vs Muon Fluxes

Ref:GGV,hep-ph/0209111 v1 10 Sep 2002

Essentially same to ~100TeV at sea level

• Constraint on a prompt µ is equivalent to a constraint on prompt

Use down going muon data

Page 5: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Analysis Description

Page 6: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Signal Simulation Single µ with an assumed energy spectrum of prompt µ (RPQM) and isotropic in zenith and azimuth angle at the surface of the earth

Standard AMANDA codes used for propagation and detector response. Charm-D model will also be used.

Signal ,Background Simulation and Data

The conventional muons produced from the π± and K± decay is the B.G.

CORSIKA 6.02 with the QGSJET01 model of hadron interactions and decay used.

Background Data

70 days life time worth data taken by the AMANDA II during 2001 will be studied.

Page 7: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Analysis levels

• L2 standard minimum bias data • L3 Zenith Angle Cut

• L4 Event Quality Cuts

• L5 Topology cut (single muon and a bundle of muons)• Early Hit (Topology1)• dE/dX method (Topology2)

• L6 Energy Cut

Strategies for separation of Signal from Background

Page 8: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Zenith distribution(L3)

True track

Reco Track

Cos(zenith) B/S vs Cos(zenith)

True track(S)Reco Track(S)

Reco Track(BG)

TrueTrack(BG)

• S/B ratio improves near the horizon

• Lots of misreconstructed muon near horizon

• Angular resolution very important to see enhancement of S/B near the horizon.

Cut these out

Page 9: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Quality Cuts(L4)

• Track Length(>120m) Distance between direct hits

projected on to the length of the track • Number of Direct Hit(>6) The more the number of direct hits

the better the guess track and less likely to converge to a false minimum

• Reduced Chi square(<7.3) Chisquare computed using time

residuals and divided by total number of hits

• Pre and Post hits (prehit<1.5 and posthit<1.5) Well reconstructed muon have very

few hits that arrive later or before in time (Peter Stefan's dE/dX method)

SinglesSingles(after QC)

MultiplesMultiples(after QC)

Angular Resolution

Improve from 8 to 3.5 degrees

Page 10: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Muon Bundles

log10(energy at cpd) GeV

Singles

MultiplesSignal

• The multiple muon background goes with same slope as the signal

• Need to improve the sensitivityOf our instrument to prompt muon

Page 11: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Topology 1 (Early Hit)(L5)

snapshot

Cherenkov cone BCD from reconstructed track propagating in time relative to the tracks.

• Limitations

•Random Noise hits (3.0 photo electron cut)

• Misreconstructed single muon ( Good angular resolution vital )

Muon1

Muon2

Early Hit

Reconstructed track

A

B

Δθ

•The hit at B is earlier by time

length(AB)/cice

C

D

Page 12: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Topology 1(Eview Earlyhits)

EarlyhitAmplitude>3pe (proximity cut)(Noise Hits suppressed)

Distance<50m (proximity cut)

timedelay<-15ns

Reconstructed Track

Well reconstructed single muon should not have this

Muon Bundle Single Muon (misreco)

Page 13: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Time Residuals and Convoluted Pandel

Time delay(16 PPandel) Time delay(64 CPandel)

Excess Earlyhits in MC

Data

BG MC

Page 14: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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EarlyHits

0 degree2 degree5 degree

Cut these out

Does retainA decent bit of single muon

Earlyhits

1 muon

234-10

10-2525-50

Cut these

Muon Multiplicity

Resolution effect on single muon track

Multiplicity effect on true tracks

Filtering Efficiency (Topology 1)

Frac

tion

ret

aine

d

Page 15: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Topology 2 (Energy Deposition dE/dX)(L5)

Page 16: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Hit Selection and Estimators(L5)

Quality Cuts (already discussed)

I choose only direct hits(-15ns to 75 ns)(less effected by ice properties)

Use hits with in 50m radius cylinder

around the track(less scattered)

Take only hits with amplitude greater 3.0 P.E for reconstruction.

Estimator1

B= Nphoton Observed Photon Nphoton expected from MIM

Estimator1 gives Estimator2

y = σ B/<B>

Page 17: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Filtering Efficiency(L5)

Result (Reco track) True track(Ideal)

y = σ B/<B> y = σ B/<B>

Cut these out

Cut these out

Signal

BG

Page 18: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Energy Cut(L6)

Nhits(Energy Observable)

2001 exp data

2001 signal(RPQM)+BG

BGSignal

Integral Spectra

Data Description

Avg Upper limit

0% sys)

10% sys

(20% sys)

(30% sys)

(40% sys)

Best Cut Nhit=310,Signal=9.4,B.G=6

MRF=0.7(30%SYS)

MRF

Data observed=16 Signal Expectation (RPQM)=9.4

B.G Expectation=6.0 Event upper limit=22.4

MRFsim=0.70 (30% SYS)

MRFdata=22.4/9.4= 2.3(very preliminary)

Nhits(Energy Observable)

Page 19: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Constraining Charm Neutrino models by analysis of downgoing Muon Data

A Restrictive limit means enhanced sensitivity to diffuse neutrinos

AMANDA II(muons)

ZHVdPreliminary Limit (70days)

Page 20: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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BACK UP SLIDES

Page 21: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Energy Correlation

Number of Hits Vs log10(energy at cpd) GeV

Page 22: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Note that the distribution of less than 3.0P.E. hits remains almost flat outside 50m.

Could be noise?(Randomness)

Why than does it fall down as we come close to the track?

There is a pile up in amplitude for noise hits inside 50m from the track as the pulse from early noise hit gets smeared out with the actual hits from muons

Greater than 3.0P.E hits

Less than 3.0P.E hits

Perpendicular distance from reconstructed track for

BGMC muons(m)

Goodhits

Random Hits

~10 timesgreater

Amplitude-Perpendicular distance to the Hit space

Δt<-15ns only

Dump this space out

Page 23: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Dust

Dust

Clear Ice

Reconstructed track in dataTrue track

Geometrical Effect

Reconstructed track in simulation

•The Monte Carlo tracks are reconstructed away from the true track than in the data because of various assumptions and the way the time delay is calculated.

•The tracks are reconstructed pivoted about the centre of the detector so any discrepancies in timing tend to scale roughly as the distance from the centre and hence outer strings become more susceptible to the differences than the inner ones.

Δθ

Leverarm(AB)*Δθ

A

B

Page 24: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Done with all hits (not just direct hits)

SinglesMultiples

KeepThese

Filtering Efficiency(L5)

When all hits are chosen notice what happens?

Any possible separation of S-Bis destroyed by the fluctuationof ice properties

Page 25: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Amplitude-Time Residual space

Amplitude(P.E) Amplitude(P.E)

Data

Background

DataBackground

A projection of the amplitude for a region of space in time residual less than –15ns is shown; there appears to be some disagreement between the data and the simulation in the low amplitude regime.

This bin(0-2 P.E) has significantly large number of hits compared with the other neighboring bins. What are these hits?Noise?

Ignore these

R2

Page 26: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Ice Properties Ice properties themselves

introduce some fluctuations into the observed amplitude

Think what the optical properties of a dust layer could do to the Photo Electron recorded?

May be need to apply corrections to the PE recorded depending on the layer of ice to retrieve information in original form to undo what ice does (for Horizontal muons this gets tricky!!!)

Page 27: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Dust

Dust

Clear Ice

True track

Δθ

A

B

Reco Track

Large Amplitude Seen when lower is expected from reco track hypothesis

Small Amplitude Seen when large is expected from reco track hypothesis

Reconstruction Errors

Page 28: Raghunath  Ganugapati(Newt)                &&         Paolo Desiati

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Data Agreement(16fold-ppandel)

Number of Hits

DataB.GSignal

The Overall Agreement is not extremely good within the limit of systematics (30-40%)

A possibility to improve the scenario is to use a 64-iteration Convoluted Pandel and repeat the whole procedure described