First Observation of the Greisen-Zatsepin-Kuzmin Cutoff Gareth
Hughes Rutgers, the State University of New Jersey Advisor: Prof. G
Thomson April 2009
Slide 2
2 Outline Observation of the GZK HiRes Detector Reconstruction
and Monte Carlo Spectrum + Fits Systematics Average Shower Profile
Method to find an average shower Comparisons to Monte Carlo
Gaisser-Hillas Shower shape as a function of energy TA and TALE TA
description Physics TALE description FADC simulations
Slide 3
3 Collaboration S. BenZvi, J. Boyer, B. Connolly, C.B. Finley,
B. Knapp, E.J. Mannel, A. ONeill, M. Seman, S. Westerhoff Columbia
University J.F. Amman, M.D. Cooper, C.M. Hoffman, M.H.
Holzscheiter, P. Huentemeyer, C.A. Painter, J.S. Sarracino, G.
Sinnis, T.N. Thompson, D. Tupa Los Alamos National Laboratory J.
Belz, M. Kirn University of Montana J.A.J. Matthews, M. Roberts
University of New Mexico D.R. Bergman, G. Hughes, D. Ivanov, S.R.
Schnetzer, L. Scott, S. Stratton, G.B. Thomson, A. Zech Rutgers
University N. Manago, M. Sasaki University of Tokyo R.U. Abbasi, T.
Abu-Zayyad, G. Archbold, K. Belov, A. Blake, Z. Cao, W. Deng, W.
Hanlon, C.C.H. Jui, E.C. Loh, K. Martens, J.N. Matthews, D.
Rodriguez, J. Smith, P. Sokolsky, R.W. Springer, B.T. Stokes, J.R.
Thomas, S.B. Thomas, L. Wiencke University of Utah
Slide 4
4 Introduction 1912 Cosmic Radiation discovered by Victor Hess
Charged particles and Nuclei 1934 Auger discovers Extensive Air
showers Already reached 10 15 eV GZK: Predicted over 40 years ago
by Greisen, Zatsepin and Kuzmin Ultra High Energy Extra Galactic
Cosmic Rays E p = 10 20 eV = 10 11 Pion Production off the Cosmic
Microwave Background +,0 takes away 20% of the protons energy If
the source is >50Mpc away cutoff at 6x10 19 eV A test of Large
Scale and Ultra High Energy standard physics
Slide 5
5 Extensive Air Shower Above 10 14 eV direct detection not
possible The flux is too low Indirect detection takes advantage of
the EAS Ground Array Fluorescence Detector
Slide 6
6 HiRes Location HiRes is located on the U.S. Army Dugway
Proving Ground, ~2 hours from The University of Utah campus. The
two detector sites are located 12.6 km apart at 5 Mile Hill and
Camels Back Ridge Operated from 1997 - 2006
Slide 7
7 Detector Design Mirror: 3.72m 2 effective area 256 phototube
camera Each tube covering 1 o of the sky UV transmitting filter
HiRes-I: Sample and hold electronics 21 Mirrors in 1 ring 3 to 17
degrees in elevation HiRes-II: 12.6km South East 42 Mirrors 2 rings
3 to 31 degrees elevation FADC electronics (100ns)
Slide 8
8 Monocular Analysis Pattern recognitionShower detector Plane
Fit Time vs Angle HiRes-I: Profile-constrained time fit 7 o
resolution. HiRes-II: Time fit 5 o resolution. Gaisser-Hillas
fit
Slide 9
9 Back of Envelope Energy Calculation Energy determination is
robust. Based on center of shower, not tails. Easy to Monte
Carlo.
Slide 10
10 Aperture Calculation Need complete simulation of the
detector - create MC sample identical to the data Inputs: Spectrum
as measured by Flys Eye Composition HiRes-MIA, HiRes stereo
experiments CORSIKA showers Detector Simulation: Ray Tracing
Atmospherics Threshold database Simulate Trigger and readout
electronics Write out MC and data in the same format Analyze both
using same analysis programs Compare histograms of data and MC to
judge success (or failure) of simulation Excellent Simulation of
Experiment
Slide 11
11 Spectrum Broken Power Law Fits One Break Point 2 /DOF =
63.0/37 BP = 18.65 Two Beak Points 2 /DOF = 35.1/35 1 st BP =
18.65(5) 2 nd BP = 19.75(4) Two BP with Extension Expect 51.1
events Observe 15 events Poisson probability: P(51.1;15) = 3x10 -9
(5.8 ) Independent statistics: P(43.2;13)=7x10 -8 = 5.3 -2.81(3)
-5.1(7) -3.25(1)
Slide 12
12 ConstantAperture Study Cut at 10 km, 15 km Flatten the
aperture above 10 18 eV Plot histogram of energies, weighted by E 2
to see spectral features See the ankle, high energy suppression, in
the raw data
Slide 13
13 Composition Elongation rate used to measure composition
Compare to pure Monte Carlo Proton and Iron Analyzed using full
detector simulation and reconstruction Consistent with light
composition MIA result shows changing composition
Slide 14
14 Current Spectrum Standard Atmosphere Calibration Correction
Fluorescence Yield Kakimoto and Negano Hillas dE/dx(s) Average
Mirror value 0.81 reflectivity
Slide 15
15 Systematics Atmospheric Database Constant Aperture No Change
in Energy Radiosonnde Database No change in Energy 10gram X max
Shift YAG Calibration Nightly Laser calibration Mirror Reflectivity
Mirror Database Wavelength Dependence Energy Loss dE/dX Nerling et
al Parameterization -8% Shift In Energy Fluorescence Yield New
World Average -2% Energy Implement FLASH Spectra GZK Input Spectra
Cutoff not an Input to Monte Carlo Cutoff is sharper than
measured
Slide 16
A Measurement of the Average Longitudinal Shower Development
Profile
Slide 17
17 Motivation Highest energy interactions on Earth! We dont see
1 st 200g/cm 2 Future experiments will be able to see up to 1 st
100g/cm 2 (TALE) Best method is Fluorescence Work first done in:
HiRes/MIA Prototype T. Abu-Zayyad et al., A Measurement of the
average Longitudinal Development Profile of CR Air showers,
Astropart. Phys., 16, 1 (2001) Now: More statistics Improved Monte
Carlo 2 orders of magnitude higher in energy range
Slide 18
18 Shower in x (g/cm 2 ) Make quality cuts well defined showers
Standard spectrum cuts Track length > 200g/cm 2 < 110 o Extra
Bracketing -50g/cm 2 Cerenkov Fraction < 0.35 Locally Fit Shower
Profiles Near N max N max and X max Normalize:
Slide 19
19 Shower in s (age) Gaisser-Hillas: With 2 free parameters:
Gaussian in Age: One free parameter: Shower Width Symmetric about
s=1
Slide 20
20 Black points mean of the blue Gaussian fits in bins of age
Fit to Normalized Gaisser-Hillas Gaussian in Age Average Shower:
Data
Slide 21
21 Average Shower: Monte Carlo Corsika shower library QGSJET
Proton and Iron Put through detailed Detector Simulation
Resolution
Slide 22
22 Data Monte Carlo Comparison Top: Good agreement between Data
and Monte Carlo Black: Data Red: Monte Carlo Bottom: Ratio of
Data/Monte Carlo Flat from 0.6 to 1.3 in Age E > 10 18.5 eV
Slide 23
23 Resolution in Energy dependant resolution effects profile
reconstruction Geometric bias Top and Bottom of mirrors Mirror
edges Compare Monte Carlo reconstructed with True value of and R p
Shows us age range we can fit 19.5 20.0 19.0 19.5 18.5 19.0 18.0
18.5 17.5 18.0 Log 10 (Energy) 2.7 2.9 3.9 6.1 10.0 Resolution
(degrees) 1.200.50 1.500.45 1.350.60 1.400.70 1.250.85 Upper
AgeLower Age
Slide 24
24 Fits to Average Showers Black points mean of the blue
Gaussian fits in bins of age Make average showers for half decade
bins in energy Good fits above 10 18.5 eV 2 /dof ~ few 2.693.1518.5
20.0 2.15 19.5 20.0 1.541.7619.0 -19.5 1.852.1518.5 19.0 Gaussian
in Age 2 /DOF Gaisser- Hillas 2 /DOF Log10(Energy)
Slide 25
25 Average Shower Widths , Monte Carlo CORSIKA(QGSJET) 80%
Proton and 20% Iron Get back what we put in Consistent across all
energies
Slide 26
26 Data and Monte Carlo Results Good agreement Same falling
behavior Within errors 3.5 difference in highest energy bin. What
is this? Low statistics (10 data events)
Slide 27
Telescope Array
Slide 28
28 Telescope Array Northern Hemisphere Hybrid Detector Delta,
Utah 507 Surface Detectors 1.2km spacing 100% duty cycle 3
Fluorescence Detectors 10% duty cycle Taking data since November
2007
Slide 29
29 TA Physics SD fully efficient > 10 18.8 eV GZK
Extra-galactic Anisotropy FD Monocular > 10 17.5 eV Spectrum
Large Scale Anisotropy FD Stereo > 10 19.0 eV Spectrum
Composition FD SD Hybrid > 10 18.0 eV Spectrum Composition Point
Source Anisotropy
Slide 30
30 TA Physics What TA cannot do: Ankle in Stereo FD Energy of 2
nd Knee Composition at 2 nd Knee Definitive study of extra-
Galactic Galactic transition Would be interesting to look at
spectrum and composition from 10 16.5 eV Cross calibrate with TA
Consistent measurement 10 16.5 eV 10 20 eV TALE Need Low Energy
Extension: TALE
Slide 31
31 TA Low Energy Extension 6km Fluorescence site Close to Long
Ridge (Stereo) Infill array 400m spacing Including buried detectors
Tower Detector Increase low energy aperture 3x HiRes Mirrors View
up to 72 0 elevation Successfully tested with HiRes-I Summer 2007
Single mirror Ring 4 (44 0 -53 0 ) Events seen in Ring 1 and 4 just
as expected
Slide 32
32 Faster FADC Low EnergyNearby Showers Increased Angular Speed
Could a faster FADC improve Resolution? Use Monte Carlo to compare
100ns and 25ns integration time Use Tower Prototype Monte Carlo
Throw Standard inputs HiRes Spectrum HiRes MIA/HiRes Stereo
Composition Output MC photon number and times in 5ns bins
Reconstruct using 100 and 25ns integration times Compare to thrown
values
Slide 33
33 Results Below 10 17 eV improved and R p resolution 17 0 7 0
in 10% 4% in R p Reconstruction efficiency reduced Vary electronics
filter time constant Using test 25, 32 and 50ns Recover events
without losing resolution
Slide 34
34 Conclusion HiRes has observed the G.Z.K. cutoff with a
significance > 5 Phys. Rev. Lett. 100, 101101 (2008) We have a
developed a method to measure the Average Longitudinal Shower
Measured shower parameters as a function of energy Good fit for
both Gaisser-Hillas and Gaussian in Age. Monte Carlo shows good
agreement Using 25ns FADC and 50ns significantly improves
geometrical resolution Will be implemented in TALE electronics
