The ALPIDE chip is a CMOS Monolithic Active Pixel Sensor being developed for the Upgrade of the ITS of the ALICE experiment at the CERN Large Hadron Collider. The ALPIDE chip is implemented with a ...180nm CMOS Imaging Process and fabricated on substrates with a high-resistivity epitaxial layer. It measures 15mm×30mm and contains a matrix of 512×1024pixels with in-pixel amplification, shaping, discrimination and multi-event buffering. The readout of the sensitive matrix is hit driven. There is no signaling activity over the matrix if there are no hits to read out and power consumption is proportional to the occupancy. The sensor meets the experimental requirements of detection efficiency above 99%, fake-hit probability below 10−5 and a spatial resolution of 5μm. The capability to read out Pb–Pb interactions at 100kHz is provided. The power density of the ALPIDE chip is projected to be less than 35mW/cm2 for the application in the Inner Barrel Layers and below 20mW/cm2 for the Outer Barrel Layers, where the occupancy is lower. This contribution describes the architecture and the main features of the final ALPIDE chip, planned for submission at the beginning of 2016. Early results from the experimental qualification of full scale prototype predecessors are also reported.
•The ALPIDE chip, an innovative CMOS pixel particle detector is described.•It achieves excellent detection performance figures and very low power consumption.•The characterization of prototypes confirms the achievement of the specifications.
A new 10m2 inner tracking system based on seven concentric layers of Monolithic Active Pixel Sensors will be installed in the ALICE experiment during the second long shutdown of LHC in 2019–2020. The ...monolithic pixel sensors will be fabricated in the 180nm CMOS Imaging Sensor process of TowerJazz. The ALPIDE design takes full advantage of a particular process feature, the deep p-well, which allows for full CMOS circuitry within the pixel matrix, while at the same time retaining the full charge collection efficiency. Together with the small feature size and the availability of six metal layers, this allowed a continuously active low-power front-end to be placed into each pixel and an in-matrix sparsification circuit to be used that sends only the addresses of hit pixels to the periphery. This approach led to a power consumption of less than 40mWcm−2, a spatial resolution of around 5μm, a peaking time of around 2μs, while being radiation hard to some 10131MeVneq/cm2, fulfilling or exceeding the ALICE requirements.
Over the last years of R & D, several prototype circuits have been used to verify radiation hardness, and to optimize pixel geometry and in-pixel front-end circuitry. The positive results led to a submission of full-scale (3cm×1.5cm) sensor prototypes in 2014. They are being characterized in a comprehensive campaign that also involves several irradiation and beam tests. A summary of the results obtained and prospects towards the final sensor to instrument the ALICE Inner Tracking System are given.
Abstract
A new forward calorimeter (FoCal), covering the pseudorapidity range 3.4 ≤
η
≤ 5.8, is proposed in order to extend the physics reach of ALICE during the LHC Run 4. The FoCal comprises a ...high-granularity electromagnetic calorimeter with silicon pixel and pad readout as well as a hadronic calorimeter. FoCal gives access to the nuclear gluon densities down to Bjorken-x ∼ 10
−6
, where they are not constrained by other measurements and their evolution may be affected by non-linear effects of quantum chromodynamics. The hadronic subsystem of FoCal (FoCal-H) will be based on capillary copper tubes with scintillating fibers inside. A full-length prototype was assembled and it was exposed to a non-separated charged particle beam in the H2 SPS CERN beamline in November 2022. An energy scan from 60 to 350 GeV was performed and the reconstructed signals are processed in a custom developed ROOT based environment. The design of the 2022 prototype as well as the first results from the energy reconstruction are presented.
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