Poley, L. et al, Lacasta, C., & Soldevila, U. (2016). Characterisation of strip silicon detectors for the ATLAS Phase-II Upgrade with a micro-focused X-ray beam. J. Instrum., 11, P07023–12pp.
Abstract: The planned HL-LHC (High Luminosity LHC) in 2025 is being designed to maximise the physics potential through a sizable increase in the luminosity up to 6.10(34) cm(-2) s(-1). A consequence of this increased luminosity is the expected radiation damage at 3000 fb(-1) after ten years of operation, requiring the tracking detectors to withstand fluences to over 1.10(16) 1 MeV n(eq)/cm(2) . In order to cope with the consequent increased readout rates, a complete re-design of the current ATLAS Inner Detector (ID) is being developed as the Inner Tracker (ITk). Two proposed detectors for the ATLAS strip tracker region of the ITk were characterized at the Diamond Light Source with a 3 μm FWHM 15 keV micro focused X-ray beam. The devices under test were a 320 μm thick silicon stereo (Barrel) ATLAS12 strip mini sensor wire bonded to a 130 nm CMOS binary readout chip (ABC130) and a 320 μm thick full size radial (end-cap) strip sensor – utilizing bi-metal readout layers – wire bonded to 250 nm CMOS binary readout chips (ABCN-25). A resolution better than the inter strip pitch of the 74.5 μm strips was achieved for both detectors. The effect of the p-stop diffusion layers between strips was investigated in detail for the wire bond pad regions. Inter strip charge collection measurements indicate that the effective width of the strip on the silicon sensors is determined by p-stop regions between the strips rather than the strip pitch.
|
Pierre Auger Collaboration(Abreu, P. et al), & Pastor, S. (2011). The exposure of the hybrid detector of the Pierre Auger Observatory. Astropart Phys., 34(6), 368–381.
Abstract: The Pierre Auger Observatory is a detector for ultra-high energy cosmic rays. It consists of a surface array to measure secondary particles at ground level and a fluorescence detector to measure the development of air showers in the atmosphere above the array. The “hybrid” detection mode combines the information from the two subsystems. We describe the determination of the hybrid exposure for events observed by the fluorescence telescopes in coincidence with at least one water-Cherenkov detector of the surface array. A detailed knowledge of the time dependence of the detection operations is crucial for an accurate evaluation of the exposure. We discuss the relevance of monitoring data collected during operations, such as the status of the fluorescence detector, background light and atmospheric conditions, that are used in both simulation and reconstruction.
|
Pierre Auger Collaboration(Abreu, P. et al), & Pastor, S. (2011). Anisotropy and chemical composition of ultra-high energy cosmic rays using arrival directions measured by the Pierre Auger Observatory. J. Cosmol. Astropart. Phys., 06(6), 022–17pp.
Abstract: The Pierre Auger Collaboration has reported. evidence for anisotropy in the distribution of arrival directions of the cosmic rays with energies E > E-th = 5.5 x 10(19) eV. These show a correlation with the distribution of nearby extragalactic objects, including an apparent excess around the direction of Centaurus A. If the particles responsible for these excesses at E > E-th are heavy nuclei with charge Z, the proton component of the sources should lead to excesses in the same regions at energies E/Z. We here report the lack of anisotropies in these directions at energies above E-th/Z (for illustrative values of Z = 6, 13, 26). If the anisotropies above E-th are due to nuclei with charge Z, and under reasonable assumptions about the acceleration process, these observations imply stringent constraints on the allowed proton fraction at the lower energies.
|
Menjo, H. et al, Faus-Golfe, A., & Velasco, J. (2011). Monte Carlo study of forward pi(0) production spectra to be measured by the LHCf experiment for the purpose of benchmarking hadron interaction models at 10(17) eV. Astropart Phys., 34(7), 513–520.
Abstract: The LHCf experiment aims to improve knowledge of forward neutral particle production spectra at the LHC energy which is relevant for the interpretation of air shower development of high energy cosmic rays. Two detectors, each composed of a pair of sampling and imaging calorimeters, have been installed at the forward region of IP1 to measure pi(0) energy spectra above 600 GeV. In this paper, we present a Monte Carlo study of the pi(0) measurements to be performed with one of the LHCf detectors for proton-proton collisions at root s = 14 TeV. In approximately 40 min of operation at luminosity 0.8 x 10(29) cm(-2) s(-1) during the beam commissioning phase of LHC, about 1.5 x 10(4) pi(0) events are expected to be obtained at two transverse positions of the detector. The backgrounds from interactions of secondary particles with beam pipes and interactions of beam particles with residual gas in the beam pipes are expected to be less than 0.1% of the signal from pi(0)s. We also discuss the capability of LHCf measurements to discriminate between the various hadron interaction models that are used for simulation of high energy air showers, such as DPMJET3.03, QGSJETII-03, SIBYLL2.1 and EPOS1.99.
|
KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Calvo, D., Carretero, V., Colomer, M., Corredoira, I., et al. (2020). Event reconstruction for KM3NeT/ORCA using convolutional neural networks. J. Instrum., 15(10), P10005–39pp.
Abstract: The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches.
|
