We have searched for intermediate-scale anisotropy in the arrival directions of ultrahigh-energy cosmic rays with energies above 57 EeV in the northern sky using data collected over a 5 yr period by the surface detector of the Telescope Array experiment. We report on a cluster of events that we call the hotspot, found by oversampling using 20 • radius circles. The hotspot has a Li-Ma statistical significance of 5.1σ , and is centered at R.A. = 146. • 7, decl. = 43. • 2. The position of the hotspot is about 19 • off of the supergalactic plane. The probability of a cluster of events of 5.1σ significance, appearing by chance in an isotropic cosmic-ray sky, is estimated to be 3.7 × 10 −4 (3.4σ).

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The Telescope Array (TA) observatory utilizes fluorescence detectors and surface detectors (SDs) to observe air showers produced by ultra high energy cosmic rays in Earth’s atmosphere. Cosmic-ray events observed in this way are termed hybrid data. The depth of air shower maximum is related to the mass of the primary particle that generates the shower. This paper reports on shower maxima data collected over 8.5 yr using the Black Rock Mesa and Long Ridge fluorescence detectors in conjunction with the array of SDs. We compare the means and standard deviations of the observed X max distributions with Monte Carlo X max distributions of unmixed protons, helium, nitrogen, and iron, all generated using the QGSJet II-04 hadronic model. We also perform an unbinned maximum likelihood test of the observed data, which is subjected to variable systematic shifting of the data X max distributions to allow us to test the full distributions, and compare them to the Monte Carlo to see which elements are not compatible with the observed data. For all energy bins, QGSJet II-04 protons are found to be compatible with TA hybrid data at the 95% confidence level after some systematic X max shifting of the data. Three other QGSJet II-04 elements are found to be compatible using the same test procedure in an energy range limited to the highest energies where data statistics are sparse.