The current methods to determine the primary energy of ultra-high energy cosmic rays (UHECRs) are different when dealing with hadron or photon primaries. The current experiments combine two different techniques, an array of surface detectors and fluo
rescence telescopes. The latter allow an almost calorimetric measurement of the primary energy. Thus, hadron-initiated showers detected by both type of detectors are used to calibrate the energy estimator from the surface array (usually the interpolated signal at a certain distance from the shower core S(r0)) with the primary energy. On the other hand, this calibration is not feasible when searching for photon primaries since no high energy photon has been unambiguously detected so far. Therefore, pure Monte Carlo parametrizations are used instead. In this work, we present a new method to determine the primary energy of hadron-induced showers in a hybrid experiment based on a technique previously developed for photon primaries. It consists on a set of calibration curves that relate the surface energy estimator, S(r0), and the depth of maximum development of the shower, Xmax, obtained from the fluorescence telescopes. Then, the primary energy can be determined from pure surface information since S(r0) and the zenith angle of the incoming shower are only needed. Considering a mixed sample of ultra-high energy proton and iron primaries and taking into account the reconstruction uncertainties and shower to shower fluctuations, we demonstrate that the primary energy may be determined with a systematic uncertainty below 1% and resolution around 16% in the energy range from 10^{18.5} to 10^{19.6} eV. Several array geometries, the shape of the energy error distributions and the uncertainties due to the unknown composition of the primary flux have been analyzed as well.
The search for photons at EeV energies and beyond has considerable astrophysical interest and will remain one of the key challenges for ultra-high energy cosmic ray (UHECR) observatories in the near future. Several upper limits to the photon flux hav
e been established since no photon has been unambiguously observed up to now. An improvement in the reconstruction efficiency of the photon showers and/or better discrimination tools are needed to improve these limits apart from an increase in statistics. Following this direction, we analyze in this work the ability of the surface parameter Sb, originally proposed for hadron discrimination, for photon search. Semi-analytical and numerical studies are performed in order to optimize Sb for the discrimination of photons from a proton background in the energy range from 10^18.5 to 10^19.6 eV. Although not shown explicitly, the same analysis has been performed for Fe nuclei and the corresponding results are discussed when appropriate. The effects of different array geometries and the underestimation of the muon component in the shower simulations are analyzed, as well as the Sb dependence on primary energy and zenith angle.
The current methods to determine the primary energy in surface arrays are different when dealing with hadron or photon initiated showers. In this work, we adapt a method previously developed for photon-initiated showers to hadron primaries. We determ
ine the Monte Carlo parametrizations that relate the surface energy estimator and the maximum of shower development for both, proton and Iron primaries. Using for each primary their own set of calibration curves, which is of course impossible in practice, we show that the energy could be inferred with a negligible bias and 12% resolution. However, we show that a mixed calibration could also be performed, including both type of primaries, such that the bias still remains low and the achieved resolution is around 15%. In addition, the method allows the simultaneous determination of Xmax in pure surface arrays with resolution better than 7%.
A new family of parameters intended for composition studies in cosmic ray surface array detectors is proposed. The application of this technique to different array layout designs has been analyzed. The parameters make exclusive use of surface data co
mbining the information from the total signal at each triggered detector and the array geometry. They are sensitive to the combined effects of the different muon and electromagnetic components on the lateral distribution function of proton and iron initiated showers at any given primary energy. Analytical and numerical studies have been performed in order to assess the reliability, stability and optimization of these parameters. Experimental uncertainties, the underestimation of the muon component in the shower simulation codes, intrinsic fluctuations and reconstruction errors are considered and discussed in a quantitative way. The potential discrimination power of these parameters, under realistic experimental conditions, is compared on a simplified, albeit quantitative way, with that expected from other surface and fluorescence estimators.
A new family of parameters intended for composition studies is presented. They make exclusive use of surface data combining the information from the total signal at each triggered detector and the array geometry. We perform an analytical study of the
se composition estimators in order to assess their reliability, stability and possible optimization. The influence of the different slopes of the proton and Iron lateral distribution function on the discrimination power of the estimators is also studied. Additionally, the stability of the parameter in face of a possible underestimation of the size of the muon component by the shower simulation codes, as it is suggested by experimental evidence, is also studied.
The normalization constant of the lateral distribution function (LDF) of an extensive air shower is a monotonous (almost linear) increasing function of the energy of the primary. Therefore, the interpolated signal at some fixed distance from the core
can be calibrated to estimate the energy of the shower. There is, somehow surprisingly, a reconstructed optimal distance, r_{opt}, at which the effects on the inferred signal, S(r_{opt}), of the uncertainties on true core location, LDF functional form and shower-to-shower fluctuations are minimized. We calculate the value of r_{opt} as a function of surface detector separation, energy and zenith angle and we demonstrate the advantage of using the r_{opt} value of each individual shower instead of a same fixed distance for every shower, specially in dealing with events with saturated stations. The effects on the determined spectrum are also shown.
