The Method Of Discriminating Primary Cosmic Ray At The "Knee" In ARGO Experiment

The energy spectrum of cosmic rays (proton and nuclei from the universe) follows a negative power law: dN/dE∝E^r, but the all-particle energy spectrum ofcosmic rays shows a distinctive feature around 4 PeV, where the spectral index of the power-law changes from -2.7 to approximately -3.1. This feature is commonly called the the "knee", and the corresponding energy region is called the "knee" region. Existence of this feature has been well established experimentally, but there still remain controversial arguments on its origin. To explain this feature, several mechanisms have been proposed. In some of these theoretical models, it is believed that the knee is an intrinsic property of the energy spectrum, related to the acceleration and propagation of the cosmic ray. While in other models, the knee is explained as a new type of interaction at very high energy. Most of these models can describe the obsvered all-particle energy spectrum very well, but the predictions of the individual element spectra in some modles are quite different. So the precise measurements of the individual element spectra at the knee energy region are important for understanding the origin, acceleration and propagation of the cosmic rays.Since the flux of the cosmic rays decreases rapidly with energy according to a negative power law, the cosmic ray particles with very high energy (VHE) can't be directly detected by balloon- and satellite-borne detectors. These VHE particles can only be indirectly detected by the ground-based detector arrays, which can record the secondary particles in the extensive air shower (EAS) induced by them. The key point in the study of the physics at the knee region in the groud based experiments is to efficiently identify the EAS's induced by different primary particles. To achieve this aim, it requires that the detector array can records sufficient information of EAS, and an effective method to discriminate primary cosmic rays is needed.The ARGO-YBJ experiment, a collaboration between Chainese and Intalian institutions, is a groud-based EAS detector array, located at the Yangbajing Cosmic Ray Observatory (atmospheric detpth: 606 g/cm2,4300m a.s.1) in Tibet (P.R. China). This experiment utlize a full coverage detector array consisting of Resistive Plate Chambers (RPC). The high coverage (above 90%), good time resolution and fine space granularity makes it able to measure the time and lateral distributions of the secondary particles in a EAS with sufficient precision.With the analog read-out of the RPCs charge, the array can measure the cosmic rays with energies up to the knee region. In addition, at the observation level of this experiment, the EAS induced by cosmic ray particles with energies at "knee" region reach a maximum development, irrespective of the primary mass, so that the shower size is less fluctuated and the energy determination is more precise and less dependent upon the unknown composition. These advantages, together with an effective data analysis method, make it possible to get individual element spectrum in the "knee" region. These experimental information could be helpful for the study of the origin of "knee". In this work we try to find a method for identifying the primary cosmic ray particles with energies at the "knee" region by using Monte Carlo generated data, and study the feasibility of measuring the individuale element spectra in the "knee" region.The EASs induced by different primary particles are simulated using CORSIKA program. In order to estimate the influence of hadronic interaction models on the identification results, we chose two interaction models for the Monte Carlo simulation: QGSJET-II and SIBYLL, which are representative and have good agreement with the experimental results. We have initiated the EAS with high energy protons, helium, CNO nuclei, Mg-Si nuclei and iron nuclei with energies ranging from 100TeV to 10PeV. The transportation of the EAS particles in ARGO detector and the detector response are simulated indetail with a detector simulation program based on GEANT3. Monte carlo events with sufficient statistics are thus obtained.After examining the space-time information of the EAS induced by different primaries by using the selected Monte Carlo events, we found that following 5 parameters can be used to characterize the difference between proton and other nuclei induced showers: N_Hits,, R₈₀, S_front, Ratio₈₀. With these parameters as inputs to an artificial neural network (ANN), a multi-parameter analysis is performed. To check the influence of hadronic interaction models, two ANN is trained and tested by QGSJET-II data and SIBYLL data respectively, and also the cross-examination is done (test the QGSJET-II ANN with SIBYLL data and vice versa). The dependence on hadronic interaction models is very weak, and primary proton events can be identified effectively from other events by use of ANN method. The ANN can pick out about 40% proton events and the rejection ratio for other nuclei is about 94%. Using the selected proton events, the energy spectrum of proton in the knee region is reconstructed. The reconstructed result is in good agreement with the assumed spectrum in the simulation.Meanwhile, multi-scale analysis method is used to study the feasibility of identifying the primary iron nucleus with energies at the knee region. After the multi-fractal analysis and wavelet transformation analysis are applied to the distribution of the secondary particles on the detecting surface, two characteristic parameters are got: the exponents of multi-scale moment and wavelet transform moment. Using the exponents at the order q equal to 4, 6, 8 as the inputs, an artificial neural network that can be used to identify the component of primary iron is constructed and trained and tested using Monte Carlo data sample. The data sample is divided into groups according to different hits number, and multi-parameter analysis is applied to each group. The best result is gotten in the group with hit number greater than 20000, It can pick out about 56.4% iron events and the rejection ratio for other nuclei is about 98.3%, the quality factor is 4.36.In Summary, based on Monte Carlo simulation of ARGO-YBJ experiment, the space-time information of the charged particles in Extensive Air Showers is used to study the difference between showers induced by different primaries. Multi-parameter analysis is done by using an ANN method with several parameters which can efficiently pick out primary proton induced showers as inputs. With weak model dependence the ANN can efficiently pick out the proton induced events from others. The proton spectrum from 100 Tev to 10 PeV can be obtained using the proton events selected by ANN. Meanwhile, multi-scale analysis method is used to study the feasibility of identifying the primary iron nucleus with energies at the knee region. With several parameters which can describe the fractal characteristics of the event image as inputs, a multi-parameter analysis is done by using ANN method. The result shows that this ANN could efficiently discriminate the primary iron nucleus in "knee" region.