anisotropy in cosmic ray arrival directions using icecube and icetop frank mcnally iscra

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Anisotropy in Cosmic Ray Arrival Directions Using IceCube and IceTop Frank McNally ISCRA

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Page 1: Anisotropy in Cosmic Ray Arrival Directions Using IceCube and IceTop Frank McNally ISCRA

Anisotropy in Cosmic Ray Arrival Directions Using IceCube and IceTop

Frank McNally

ISCRA

Page 2: Anisotropy in Cosmic Ray Arrival Directions Using IceCube and IceTop Frank McNally ISCRA

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IceCube and IceTop IceCube

Rate: ~ 2 kHz Energy Range: ~100 GeV – 1

PeV Data in Data Storage and

Transfer (DST) format contains limited information

IceTop Rate: ~ 20 Hz Energy Range: ~100 TeV –

1EeV More information per event

Page 3: Anisotropy in Cosmic Ray Arrival Directions Using IceCube and IceTop Frank McNally ISCRA

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Anisotropy in IceCube (Published)

IC59 Relative Intensity Map

Median Energy: ~20 TeV

IC59 Dipole & Quadropole Fit Residuals (20o smoothing)

Abbasi et al., ApJ, 740, 16, 2011 arxiv/1105.2326

Page 4: Anisotropy in Cosmic Ray Arrival Directions Using IceCube and IceTop Frank McNally ISCRA

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Anisotropy in IceCube (Preliminary)

Median Energy: ~20 TeV

Dipole & Quadropole Fit Residuals (5o smoothing)

4 years of data (IC59 – IC86-II) 1.24 x 1011 events

IceCube Preliminary

Relative Intensity

Page 5: Anisotropy in Cosmic Ray Arrival Directions Using IceCube and IceTop Frank McNally ISCRA

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IT59 + IT73 + IT81

Anisotropy in IceTop

Median energy: ~400 TeV

Median energy:~2 PeV

IT59 + IT73 + IT81+ IT81-II

High energy

IceTop Preliminary

IceTop Published Aartsen et al., ApJ 765, 55, 2013 arxiv/1210.5278

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Page 14: Anisotropy in Cosmic Ray Arrival Directions Using IceCube and IceTop Frank McNally ISCRA

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Taking the Next Step

Goal Study anisotropy as a

function of energy and composition

New energy estimator Use additional

information provided by IceTop for more accurate energy and composition reconstruction

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Likelihood-based Energy Reconstruction – Building the tables

Using simulation, create histograms that store: Primary information

Composition, energy, zenith, and distances from tanks to shower core

Observables Charge registered at each

tank

Environment Snow depth at each tank

Bin all information 110 Energy Bins, 4 Zenith Bins, 4

Snow Bins, 70 Distance Bins, 46 Charge Bins

Normalize histograms, so a bin [C, E, Z, Q, S, D] gives the probability that……a particle with: composition C, energy E, and zenith angle Zdeposited a charge Q at a tank with snow depth S at a distance D from the

shower core

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Reconstruction

Iterative grid search tests core positions across array

Returns best core position, energy, and corresponding likelihood for each composition

Example of likelihood space for a fine grid search

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Performance

Log

10(E

_reco

/

E_t

rue (

GeV

))

Core

_reco

-

Core

_tru

e (

m)

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Composition Separation

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Energy Split Example (IT73+IT81):Split by NStations

3 stations

4 stations

5 stations

6 stations

7 stations

8 - 9 stations

10 - 14 stations

15 + stations

9.69x107

6.54x107

4.74x107

3.22x107

2.17x107

2.47x107

1.72x107

6.05x106

Relative Intensity Plots

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Summary & Moving Forward Large Scale

Anisotropy appears to change as a function of energy

Small scale Significant structure visible at 5o scale with IceCube

data Future Goals

More data now available: IT81-III / IC86-III

New energy estimation Use likelihood-based energy reconstruction to look at

anisotropy as a function of energy and potentially composition