[Paper Review] Search for large-scale anisotropies with the Auger Observatory

E. Armengaud|arXiv (Cornell University)|Jun 18, 2007

Astrophysics and Cosmic Phenomena11 citations

TL;DR

This study analyzes over two years of data from the Pierre Auger Observatory to search for large-scale anisotropies in the cosmic ray sky distribution, particularly modulations in right ascension. Using Fourier analysis, East-West comparisons, and exposure-corrected Rayleigh scans, it finds no significant anisotropy, setting a 95% upper limit of 1.4% on first-harmonic modulation at 1–3 EeV, consistent with isotropy despite earlier AGASA claims of a 4% signal.

ABSTRACT

We use more than two years of data from the Pierre Auger Observatory to search for anisotropies on large scales in different energy windows. We account for various systematics in the acceptance, in particular due to the array growth and weather variations. We present the results of analyses and consistency checks looking for patterns in the right ascension modulation of the cosmic ray distribution. No significant anisotropies of this kind are observed.

Motivation & Objective

• To search for large-scale anisotropies in the cosmic ray sky distribution using data from the Pierre Auger Observatory.
• To test the hypothesis of a 4% right ascension modulation reported by AGASA in the 1–2 EeV energy range.
• To account for systematic effects in detector acceptance, including array growth, maintenance, and weather variations.
• To set robust upper limits on large-scale anisotropies using multiple complementary analysis techniques.
• To assess the significance of potential sidereal or anti-sidereal modulations due to instrumental or atmospheric effects.

Proposed method

• Performs Fourier analysis on modified event times $ t_{\text{mod}}(i) = t_i + \text{RA}(i) - \text{RA}_0(i) $ to isolate sidereal modulations in the event rate.
• Applies the East-West method to compare event counts in eastward and westward directions, canceling direction-independent acceptance effects to first order.
• Uses the Rayleigh distribution to model the expected noise in harmonic amplitudes, deriving 95% upper limits from the empirical distribution.
• Constructs exposure maps using detector deployment logs, dead time records, and atmospheric parameterizations (pressure/temperature) to correct for acceptance variations.
• Employs the CIC method for energy calibration above 10 EeV, enabling analytic exposure estimation due to saturated acceptance.
• Compares results across energy bins and declination bands to test for energy- or direction-dependent patterns.

Experimental results

Research questions

• RQ1 Is there a significant first-harmonic modulation in the right ascension distribution of cosmic rays above 1 EeV?
• RQ2 Can the 4% right ascension modulation reported by AGASA be confirmed or ruled out with Auger data?
• RQ3 To what extent do detector acceptance variations—due to array growth, maintenance, and weather—induce spurious modulations?
• RQ4 What is the 95% upper limit on the amplitude of a large-scale anisotropy in the cosmic ray sky at EeV energies?
• RQ5 How do different analysis methods (Fourier, East-West, exposure-corrected Rayleigh) compare in sensitivity and systematics control?

Key findings

• No significant large-scale anisotropy is observed in the right ascension distribution of cosmic rays across the energy range 1–10 EeV.
• The 95% upper limit on the first-harmonic amplitude of a right ascension modulation is 1.4% in the 1–3 EeV energy range, after correcting for exposure and systematics.
• The measured sidereal amplitude after East-West subtraction is (0.7 ± 0.4)%, corresponding to a 24% chance probability of being a statistical fluctuation.
• In the 1–3 EeV range, the Rayleigh amplitude is below 1% and the Rayleigh noise is ~0.6%, consistent with isotropy.
• Above 10 EeV, with ~1,400 events, the 95% upper limit on a right ascension modulation is 8.6%, due to low statistics and high systematics.
• Systematic uncertainty in exposure estimation contributes ~0.4% to the upper limit, derived from differences between exposure models.