The upgrade of the ALICE Inner Tracking System

The Inner Tracking System (ITS) of the ALICE experiment will be upgraded during the second long LHC shutdown in $\mathrm{2019}-\mathrm{2020}$. The main goal of the ALICE ITS Upgrade is to enable high precision measurements of low - momentum particles (< 1 GeV/c) by acquiring a large sample of events, benefiting from the increase of the LHC instantaneous luminosity of $\mathrm{Pb}-\mathrm{Pb}$ collisions to $\mathcal{L} = 6 \cdot 10^{27} cm^{-2} s^{-1}$ during Run 3. Working in this direction the ITS upgrade project is focusing on the increase of the readout rate, on the improvement of the impact parameter resolution, as well as on the improvement of the tracking efficiency and the position resolution. The major setup modification is the substitution of the current ITS with seven layers of silicon pixel detectors. The ALPIDE chip, a CMOS Monolithic Active Pixel Sensor (MAPS), was developed for this purpose and offers a spatial resolution of 5 $\mu$m. The use of MAPS together with a stringent mechanical design allows for the reduction of the material budget down to 0.35% $X_0$ for the innermost layers and 1% $X_0$ for the outer layers. The detector design was validated during the research and development period through a variety of tests ensuring the proper operation for the full lifetime inside ALICE. The production phase is close to completion with all the new assembled components undergoing different tests that aim to characterize the modules and staves and determine their qualification level. This contribution describes the detector design, the measurements performed during the research and development phase, as well as the production status

Upgrade of the ALICE Inner Tracking System

During the Long Shutdown 2 of the LHC in 2018/2019, the ALICE experiment plans the installation of a novel Inner Tracking System. It will replace the current six layer detector system with a seven layer detector using Monolithic Active Pixel Sensors. The upgraded Inner Tracking System will have significantly improved tracking and vertexing capabilities, as well as readout rate to cope with the expected increased Pb-Pb luminosity of the LHC. The choice of Monolithic Active Pixel Sensors has been driven by the specific requirements of ALICE as a heavy ion experiment dealing with rare processes at low transverse momenta. This leads to stringent requirements on the material budget of 0.3$$ per layer for the three innermost layers. Furthermore, the detector will see large hit densities of $\sim 19 \mathrm{cm}^{-2}/\mathrm{event}$ on average for minimum-bias events in the inner most layer and has to stand moderate radiation loads of 700 kRad TID and $1\times 10^{13}$ 1 MeV n$_\mathrm{eq}/\mathrm{cm}^{2}$ NIEL at maximum. The Monolithic Active Pixel Sensor detectors are manufactured using the TowerJazz 0.18 $\mu$m CMOS Imaging Sensor process on wafers with a high-resistivity epitaxial layer. This contribution summarises the recent R&D activities and focuses on results on the large-scale pixel sensor prototypes.Comment: 10 pages, 8 figures, proceedings of VERTEX 2014, 15-19 September 201

Scalable Readout for Proton CT

Denne oppgaven er en del av arbeidet med å utvikle en prototype detektor for proton CT. Den tar for seg første del av data prosessering nødvendig får rekonstruksjon og analyse av dataene og debugging av systemet..Masteroppgave i informatikkINF399MAMN-INFMAMN-PRO

Design and Implementation of a High-Speed Readout and Control System for a Digital Tracking Calorimeter for proton CT

Particle therapy, a non-invasive technique for treating cancer using protons and light ions, has become more and more common. For example, a particle treatment facility is currently being built, in Bergen, Norway. Proton beams deposit a large fraction of their energy at the end of their paths, i.e., the delivered dose can be focused on the tumor, sparing nearby tissue with a low entry and almost no exit dose. A novel imaging modality using protons promises to overcome some limitations of particle therapy and allowing to fully exploit its potential. Being able to position the so-called Bragg peak accurately inside the tumor is a major advantage of charged particles, but incomplete knowledge about a crucial tissue property, the stopping power, limits its precision. A proton CT scanner provides direct information about the stopping power. It has the potential to reduce range uncertainties significantly, but no proton CT system has yet been shown to be suitable for clinical use. The aim of the Bergen proton CT project is to design and build a proton CT scanner that overcomes most of the critical limitations of the currently existing prototypes and which can be operated in clinical settings. A proton CT prototype, the Digital Tracking Calorimeter, is being developed as a range telescope consisting of high-granularity pixel sensors. The prototype is a combined position-sensitive detector and residual energy-range detector which will allow a substantial rate of protons, speeding up the imaging process. The detector is single-sided, meaning that it employs information from the beam delivery system to omit tracker layers in front of the phantom. The detector operates by tracking the charged particles traversing through the detector material behind the phantom. The proton CT prototype will be used to determine the feasibility of using proton CT to increase the dose planning accuracy for particle treatment of cancer cells. The detector is designed as a telescope of 43 layers of sensors, where the two front layers act as the position-sensitive detector providing an accurate vector of each incoming particle. The remaining layers are used to measure the residual energy of each particle by observing in which layer they stop and by using the cluster size in each layer. The Digital Tracking Calorimeter employs the ALPIDE sensor, a monolithic active pixel sensor, each utilizing a 1.2Gb/s data link. Each layer of 18×27 cm consists of 108 ALPIDE sensors, roughly corresponding to the width and height of the head of a grown person. The sensors are connected to intermediary transition boards that route the data and control links to dedicated readout electronics and supply the sensors with power. The readout unit is the main component of both the data acquisition and the detector control system. The power control unit controls the power supply and monitors the current usage of the sensors. Both of these devices are mainly implemented in FPGAs. The main purpose of this work has been to explore and implement possible design solutions for the proton CT electronics, including the front-end, as well as the readout electronics architecture. The resulting architecture is modular, allowing the further scale-up of the system in the future. A major obstacle to the design is the high amount of sensors and the corresponding high-speed data links. Thus, a large emphasis has been on the signal integrity of the front-end electronics and a dynamic phase alignment sampling method of the readout electronics firmware. The readout FPGA employs regular I/O pins for the high-speed data interface, instead of high-speed transceiver pins, which significantly reduces the magnitude of the data acquisition system. A consistent design approach with detailed and systematic verification of the FPGA firmware modules, along with a continuous integration build system, has resulted in a stable and highly adaptive system. Significant effort has been put into the testing of the various system components. This also includes the design and implementation of a set of production test tools for use during the manufacturing of the detector front-end.Doktorgradsavhandlin

Hardware and Software Studies for the Alignment of the Proton CT

Proton therapy is a form of particle therapy using protons to irradiate tumors as a form of cancer treatment. It is becoming more and more popular around the world, including in Norway. To locate the tumor, conventional CT scan is used today, which uses x-ray beams. The proton energy deposition is then achieved by conversions that are not optimal. Proton computed tomography has several important advantages over the conventional computed tomography. The two main advantages are giving a lower dose to the patient during imaging compared to the conventional method and eliminating the need for conversion of photon attenuation to stopping power for protons, which is a source of error. This is necessary in particle therapy, because the physical properties of photons and protons are very different. Using the same type of particles for both imaging and therapy will potentially increase the accuracy of particle therapy treatment plans. For proton CT to be possible, the detectors need to accurately detect the proton tracks and energy depositions and for that the layers of the proton detectors have to be aligned. This master's thesis is an attempt at finding a method for the purpose of alignment in a proton CT detector.Masteroppgave i medisinsk teknologiMTEK39

A derivation of the electric field inside MAPS detectors from beam-test data and limited TCAD simulations

Solid semiconductor sensors are used as detectors in high-energy physics experiments, in medical applications, in space missions and elsewhere. A precise knowledge of the electric field inside the basic cells of these sensors is highly important for their characterization and performance understanding. The field governs the charge propagation processes and ultimately determines the size and quality of the electronic signal of the cell. Hence, the simulation of these sensors relies strongly on the electric field knowledge. For a certain voltage applied to the cell, the field depends on the specifics of the device's growth and fabrication. The information about these is often commercially protected or otherwise very difficult to encode in state-of-the-art technology computer-aided-design (TCAD) software. It is therefore practically impossible to obtain the field without some minimal knowledge. In this work, we show that combining public beam-test data and a very limited public TCAD-based knowledge, we are able to effectively reconstruct the 3D electric field function in the pixel cell of one important and widely used example, namely the ALPIDE sensor, a monolithic active pixel sensor (MAPS). Despite its broad usage worldwide, the ALPIDE field is not available to the community as it is under proprietary restriction. We provide the 3D effective field function of the ALPIDE sensor and comment on the process by which it is derived with the help of the Allpix$^2$ software. We also comment on how starting from the same grounds, similar work can be performed for other devices.Comment: 20 pages, 7 figure

Beam test of ALPIDE Sensor

The Alice Pixel Detector (ALPIDE) is developed for the upgrade of the Inner Tracking System of the ALICE experiment at CERN, which will take place during second Long Shutdown in 2019-2020. ALPIDE is a Monolithic Active Pixel Sensor (MAPS), manufactured in a 180 nm CMOS Imaging Process of TowerJazz. Forecoming tracking detectors, based on this technology, will see strong advantages with the application of these sensors as they provide the highest capabilities in spatial resolution and utmost potential for being thin. In this work, the results of the ALPIDE sensor beam test, which took place at the Beam Test Facility of Laboratori Nazionali di Frascati, are presented