Raghunath GanugapatiNewt

1
Search for prompt muons in the
downgoing atmospheric muon flux with the
AMANDA Detector
Raghunath Ganugapati(Newt)
Paolo Desiati
2

• Backgrounds
• Conventional Atmospheric µ
• dF/dE E-3.7
• Conventional Atmospheric n
• from decay of (p , K )
• dF/dE E-3.7
• Possible nm components from
• decay of atmospheric charmed
• particles.
• dF/dE E-2.7

3
Interaction VS Decay
Ref Costa, C G S
hep-ph/0010306 v3 19 Jan 2001
4
Prompt Leptons

• Charmed mesons decay before interacting hence the
  generated µ are called prompt

• Prompt µ flux differs qualitatively from
  conventional µ

• The Energy spectrum is flatter E-2.7 vs E-3.7
  for
• conventional µ due to interaction

• The angular distribution is isotropic

5
Neutrino Fluxes

• The ZHV-D (Charm-D - Volkova) model of prompt n
  could not be constrained by looking at the
  neutrino data for one single year with AMANDA-II
• Can it be constrained with the down going µ data
  in contrast to n data?
• Can do better with down going µ ?

6
Neutrino Vs Muon Fluxes
7
Uncertainty in Prompt Lepton Cross
Sections

• The uncertainty 3 orders
• Need for accelerator data extrapolation
• Crossover between 40TeV and 3 PeV

ZhVd
8
Charm Showers

• Production of D takes up most of the energy and
  momentum of the primary 90.
• Accompanying p and K are negligible to first
  order in the estimation of the flux at the
  surface of the earth

Ref Doctoral thesis of Prof.Varieschi
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Analysis Description
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Signal ,Background Simulation
and Data
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. Use of muo0 weights
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Strategies for separation of Signal
from Background

• Cuts designed to to improve sensitivity for
  prompt µ
• Observables
• Zenith Angle(L3)
• Event Quality Related(L4)
• Topology(single muon and a bundle of muons)(L5)
• Energy(L6)
• Note that L2 is the standard minimum bias data

12
Zenith distribution
? gt 65o
(Eµgt 50 TeV)
True track
Reco Track(BG)
Reco Track
TrueTrack(BG)
Reco Track(S)
True track(S)
Cut these out
Cos(zenith)
B/S vs Cos(zenith)

• 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.

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Quality Cuts

• Track Length(gt120m)
• Distance between direct hits projected on to
  the length of the track
• Smoothness(lt0.26)
• Measure of how smoothly the hits are
  distributed along the track
• Reduced Chi square(lt7.3)
• Chisquare computed using time residuals and
  divided by total number of hits
• Cascade to track likelihood Ratio(lt1)
• Tracks that have a sphericity in the
  pattern of timing like cascades are hard to
  reconstruct(High energy muons with stochastic
  losses)

A1
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Energy Spectra
singles
multiples
signal
log10(energy at cpd) GeV
Number of Hits Vs log10(energy at cpd) GeV

• True muon energy at detector correlates with
  energy released inside the detector. Observed
  through parameters like NCH,NHITS
• The multiple muon background goes with the same
  slope as the signal so the signal will be masked
  in the fluctuations of the multiple muon
  background

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Muon Multiplicity at AMANDA depth
Nhits 150-200
Mean multiplicity increases as function of energy
(observable)
Nhits 200-250
Nhits 250-300
multiplicity
Muon multiplicity real problem for doing
Physics!!!
Average Multiplicity vs Nhits
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A new method to separate single muons from
multiple muons using the hit topology information

• Idea1 Single Muons should have no early hits
  with greater than 3.0 photoelectron.

• Idea2 Truncated Cherenkov cone timing pattern
  fits the multiple muon hypothesis better than the
  ordinary cone.

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Early Hit Illustration(Idea1)

• Cherenkov cone BCD from reconstructed track
  propagating in time relative to the tracks.
• Random Noise hits
• (3.0 photo electron cut)
• Use hits closer than 50 m
• Misreconstructed single muon
• ( Good angular resolution vital )

• The hit at B is earlier by time
• length(AB)/cice

A2
A3
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Truncated cone illustration(Idea 2)






Use Pandel fit as fixed parameters and fit the
parameter r Better fit multiple muon. Plane
wave lt r Cherenkov cone gt r from reco track

Truncated Cone timing pattern
Lateral Width(2r)
Muon1
Muon2
Muon3
Muon4
Typical lateral widths around 50m for 10TeV
muons (monte-carlo)
Reco Track
Muon5
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Early Hits
Take these
Distance (hperp)
?tlt-15ns ?dlt50m ?Agt3pe
Take these
-75
Take these

• Separation of high energy single muons using
  early hits
• Not confuse with early hits from noise and
  misreconstructed muon

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Time Delay Distributions

Angular Res H.Muons-3.5o V.Muons-1.8o
A4
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64-Iteration Convoluted Pandel Vs
16-fold Patched Pandel

• The Convoluted Pandel
• Convoluting gaussian PMT noise smearing with
  Pandel function using Confluent Hyper geometric
  functions (George and Mathieu)
• Much better Angular resolution and description
  of time delay distributions

High energy Muon With nhitsgt200
Time delay (ns) (16-fold ppandel)
1-fold iterated Convoluted Pandel has
approximately same angular resolution Of a
16-fold ppandel -Mathieu Ribordy (AMANDA
collaboration meeting,Mons)
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Multiplicity Parameters
MC multi
MC single
Signal
16-iter pandel
EarlyHits
Preliminary study of EarlyHit cut
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Multiplicity Parameters
Data
BG M.C
Signal
Cut these out
Cut these out
Nearly(Tru)-Nearly(Che)
EarlyHits
Preliminary study of EarlyHit cut
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Event Retention Plot
Quality cuts
EarlyHit cut
Energy cut

• The levels are as defined
• previously.The reduction is
• from beginning to final level is
  approximately 1 in 5107
• A cut of nhits gt150 is applied to the minimum
  bias data to speeden up processing and so the
  level between 2 and 3

?

Cut Level
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Data Agreement
Data
B.G

• Data Agreement reasonable with in the range
  of allowable systematics (30)!!!
• Much credit to the 64 iteration
  Convoluted Pandel fit

Signal
Cut out To speeden up Proceessing time
Number Of Hits
A5
A6
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Model Rejection Factor
Integral spectrum
Systematics
No systematics (no minima)
Avg Upper limit
MRF goes up
10
20
30
40
50
Number Of Hits(Energy)
Number Of Hits(Energy)

Best cut330 MRF0.77 Signal 8.2 Background6.0
This is on the RPQM model
A7
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MRF on ZHV-D model
Integral Spectrum

• Data observed9.0
• Signal Expectation70.13
• B.G Expectation6.0
• Event upper limit10.4
• MRFsim0.09 accurate systematics
• (work in progress)
• MRF(data)10.4/700.14(preliminary)
• The Halzen D model could not be constrained from
  the neutrino data for one full year AMANDAII but
  we could constrain it by an order of magnitude
  with just 75 days worth data

Avg Upper limit

MRF
Number Of Hits
Best cut330 MRF0.09 Signal70.13
Background6.0
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Constraining Charm Neutrino models by
analysis of downgoing Muon Data

• Very preliminary sensitivity on ZHV-D model
• Systematics to be well understood
• Potential to set a more restrictive limit than
  neutrino diffuse analyses

ZHVd
AMANDA II (muons)
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Conclusions And Future Work

• A restrictive limit on prompt neutrinos means
  enhanced sensitivity
• to diffuse extraterrestrial neutrinos for
  instruments like ice cube
• The systematic un certainties need to be studied
  in detail
• other models of hadronic interaction for
  Corsika needs to be looked
• The problem of separation of high energy single
  muon from multiple muon will be studied in
  greater detail

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BACK UP SLIDES
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Angular Resolution
Background
Background (after Q.C)

• Horizontal muons with greater than 65o
  reconstructed zenith angle had an angular
  resolution of 70 before the quality cuts and
  3.50 after quality cuts

Signal
Signal (after Q.C)
Angular Resolution(??)
R1
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Amplitude-Time Residual space
Data
Data
Background
Background
Ignore these
Amplitude(P.E)
Amplitude(P.E)
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?

R2
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Amplitude-Perpendicular distance to the Hit space

• 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
?tlt-15ns only
Less than 3.0P.E hits
Good hits
Random Hits
10 times greater
Dump this space out
Perpendicular distance from reconstructed track
for BGMC muons(m)
R3
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Geometrical Effect
Reconstructed track in data
True track
B
Leverarm(AB)??
Dust
Reconstructed track in simulation
??
Clear Ice
A
Dust

• 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.

R4
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Data Agreement(16fold-ppandel)
Data
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

B.G
Signal
Number of Hits
R5
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Angular Resolution

• Estimate the angular resolution for the data and
  compare it with the M.C for the final sample.
• How can we quantify Angular resolution for
  experimental data?
• Mathieus method by reordering and dividing the
  sample into two halves based on optical module
  and not hits(more appropriate to high energy).
• Resolution2.3o(mean)

Data
B.G
Signal
Angular Resolution
R6
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Data Agreement and Model Rejection Factor(NCH)
Differential spectrum for data agreement
Integral spectrum
Avg Upper limit
Data
MRF
B.G
Signal
Number of Channel
Number of Channel
Best cut195 MRF0.96 Signal5.05
Background2.4
R7