What ALICE Requires and Provides for Background Optimisation

ALICE is a dedicated heavy-ion experiment at CERN LHC aiming to study the properties of the quark–gluon plasma. A lead– lead collision might produce several ten thousand new particles. Detailed study of the event requires precise measurements of the particle tracks. A 90 m Time Projection Chamber (TPC) with more than 500 000 read-out pads was built as the main central barrel tracker. Collisions can be recorded at a rate of up to about 1 kHz. The front-end electronics, designed from FPGAs and custom ASICs, performs shaping, amplification, digitisation and digital filtering of the signals. The data is forwarded to DAQ via 216 1.25 Gb/s fibre-optical links. Configuration, control and monitoring is done by an embedded Linux system on the front-end electronics. First results on the performance of the front-end electronics and the distributed detector control system are presented. I. TIME PROJECTION CHAMBER (TPC) The A Large Ion Collider Experiment (ALICE) [1] is using a TPC [2] as the main track-finding detector. A TPC is a gaseous detector. It is shaped like an horizontal barrel and positioned in the same direction as the beam pipe, which is passing through the centre of the barrel. The overall length is 500 cm, divided by a 100 kV Central Electrode (CE) into two identical drift volume. The diameter is 494 cm, though the innermost 170 cm is not part of the TPC to make room for the beam pipe and inner tracking detectors. A schematic view of the TPC can be seen in Figure 1. Collisions will take place in the beam pipe in the centre of the TPC, allowing the particles produced to traverse the TPC and leave tracks of ionised gas along their paths. A strong electric field of from the CE will make the electrons drift towards the end planes, where data read-out is performed. Each end plane is divided into 18 azimuthal sectors, which again are divided into two Multi-Wire Proportional Chambers (MWPC), the Outer and Inner Read-Out Chamber (OROC/IROC). The OROC has four Read-out Partitions (RPs); the IROC two. A RP is an electronic entity for reading out data from read-out pads. The ionistic signal will be amplified by the space charge around the wires of the MWPC. The induced charge on the read-out pads is forwarded to the read-out electronics. In total for both sides there are 557568 pads. The drift volume is filled with counting gas composed of 85.7 % Ne, 9.5 % CO2 and 4.8 % N2. A cold, light gas is used to assure low diffusion and low multiple scattering. Field distortions are minimised because of the high ion mobility and few ionisation electrons per unit length. The electronics design noise figure is 1000 RMS e− (700 actually achieved); not limiting the position resolution will require a signal/noise ratio of at least 20. Apart from tracking—measuring the charged particle momentum and having a good two-track separation—it also provides Particle IDentification (PID). The TPC is expected to perform well at multiplicities as high as dNch/dη=8000 in the particle momentum range [0.1, 100] GeV/c and within |η| 90 %, and the dE/dx resolution better than 10 %. Further, the TPC alone will have a momentum resolution of about 1 % at 2 GeV/c and 10 % at 50 GeV/c. For p–p collisions a read-out rate of ≈1 kHz is expected, while for central Pb–Pb collisions ≈0.2 kHz. Figure 1: Schematic view of the TPC. To the left a singe Read-out Partition (RP) is enlarged for visibility. The support for the sectors is shown on the two end planes. Between them is the Central Electrode (CE). The TPC allows space around the centre of the length axis for beam pipe and inner silicon detectors. II. DATA READ-OUT DESIGN As already mentioned, each sector has six RPs. A RP consists of a Read-out Control Unit (RCU) with up to 25 Front-End Cards (FEC), depending on the radial location. The innermost RPs have the highest number of FECs, as a smaller size for the readout-pads is used to increase the resolution to take into account the higher track density close to the collisions. The electronics for one RP, as well as its connection to the central systems is shown as a block diagram in Figure 2. Eight ALICE TPC Read-Out (ALTRO) [3] chips are mounted on a FEC, each capable of reading out 16 read-out pads. The FECs are attached to the RCU via buses; one for data transfer and one for control/monitoring. Once on the RCU, the data is forwarded to Data Acquisition system (DAQ) and the High Level Trigger (HLT) via a 1.25 Gb/s optical fibre. A Detector Control System (DCS) board equipped with an embedded

ALICE (A Large Ion Collider Experiment) is the heavy-ion experiment at the Large Hadron Collider (LHC) at CERN. As an important part of its upgrade plans, the ALICE experiment will schedule the installation of a new Inner Tracking System (ITS) during the Long Shutdown 2 (LS2) of the LHC. The new ITS layout will consist of seven concentric layers, $\approx$ 12.5 Gigapixel camera covering about 10m$^2$ with Monolithic Active Pixel Sensors (MAPS). This choice of technology has been guided by the tight requirements on the material budget of 0.3$\%$ X/X$_0$ per layer for the three innermost layers and backed by the significant progress in the field of MAPS in recent years. The technology initially chosen for the ITS upgrade is the TowerJazz 180 nm CMOS Technology. It offers a standard epitaxial layer of 15 - 18 $\mu$m with a resistivity between 1 and 5 k$\Omega$~cm$^{-1}$ and a gate oxide thickness below 4 nm, thus being more robust to Total Ionizing Dose (TID). The main subject of this thesis is to implement a novel digital pixel readout architecture for MAPS. This thesis aims to study this novel readout architecture as an alternative to the rolling-shutter readout. However, this must be investigated through the study of several chip readout architectures during the R$\&$D phase. Another objective of this thesis is the study and characterization of TowerJazz, if it meets the Non-Ionizing Energy Loss (NIEL) and Single Event Effects (SEE) of the ALICE ITS upgrade program. Other goals of this thesis are: Implementation of the top-down flow for this CMOS process and the design of multiple readouts for different prototypes up to the assembly of a full-scale prototype. Characterization of the radiation hardness and SEE of the chips submitted to fabrication. Characterization of full custom designs using analog simulations and the generation of digital models for the simulation chain needed for the verification process. \item Implementation and study of different digital readouts to meet the ITS upgrade program in integration time, pixel size and power consumption, from the conceptual idea, production and fabrication phase. SChapter 1 is a brief overview of CERN, the LHC and the detectors complex. The ALICE ITS will be explained, focusing on the ITS upgrade in terms of detector needs and design constraints. Chapter 2 explains the properties of silicon detectors and the detector material and the principles of operation for MAPS. Chapters 3 and 4 describe the ALPIDE prototypes and their readout based on MAPS; this forms the central part of this work, including the multiple families of pixel detectors fabricated in order to reach the final design for the ITS. The ALPIDE3/pALPIDE3B chip, the latest MAPS chip designed, will be explained in detail, as well focusing in the matrix digital readout. In chapter 5 the noise measurements and its characterization are presented including a brief summary of detector response to irradiation with soft X-rays, sources and particle beams. on the ITS upgrade in terms of detector needs and design constraints. Chapter 2 explains the properties of silicon detectors and the detector material and the principles of operation for MAPS. Chapters 3 and 4 describe the ALPIDE prototypes and their readout based on MAPS; this forms the central part of this work, including the multiple families of pixel detectors fabricated in order to reach the final design for the ITS. The ALPIDE3/pALPIDE3B chip, the latest MAPS chip designed, will be explained in detail, as well focusing in the matrix digital readout. In chapter 5 the noise measurements and its characterization are presented including a brief summary of detector response to irradiation with soft X-rays, sources and particle beams.

A Large Ion Collider Experiment (ALICE) is one of the four major experiments at the Large Hadron Collider (LHC) at CERN. The high level trigger (HLT) is a compute cluster, which reconstructs collisions as recorded by the ALICE detector in real-time. It employs a custom online data-transport framework to distribute data and workload among the compute nodes. ALICE employs subdetectors that are sensitive to environmental conditions such as pressure and temperature, e.g., the time projection chamber (TPC). A precise reconstruction of particle trajectories requires calibration of these detectors. Performing calibration in real time in the HLT improves the online reconstructions and renders certain offline calibration steps obsolete speeding up offline physics analysis. For LHC Run 3, starting in 2020 when data reduction will rely on reconstructed data, online calibration becomes a necessity. Reconstructed particle trajectories build the basis for the calibration making a fast online-tracking mandatory. The main detectors used for this purpose are the TPC and Inner Tracking System. Reconstructing the trajectories in the TPC is the most compute-intense step. We present several improvements to the ALICE HLT developed to facilitate online calibration. The main new development for online calibration is a wrapper that can run ALICE offline analysis and calibration tasks inside the HLT. In addition, we have added asynchronous processing capabilities to support long-running calibration tasks in the HLT framework, which runs event-synchronously otherwise. In order to improve the resiliency, an isolated process performs the asynchronous operations such that even a fatal error does not disturb data taking. We have complemented the original loop-free HLT chain with ZeroMQ data-transfer components. The ZeroMQ components facilitate a feedback loop that inserts the calibration result created at the end of the chain back into tracking components at the beginning of the chain, after a short delay. All these new features are implemented in a general way, such that they have use-cases aside from online calibration. In order to gather sufficient statistics for the calibration, the asynchronous calibration component must process enough events per time interval. Since the calibration is valid only for a certain time period, the delay until the feedback loop provides updated calibration data must not be too long. A first full-scale test of the online calibration functionality was performed during 2015 heavy-ion run under real conditions. Since then, online calibration is enabled and benchmarked in 2016 proton-proton data taking. We present a timing analysis of this first online-calibration test, which concludes that the HLT is capable of online TPC drift time calibration fast enough to calibrate the tracking via the feedback loop. We compare the calibration results with the offline calibration and present a comparison of the residuals of the TPC cluster coordinates with respect to offline reconstruction.

Commissioning and first performances of the ALICE MID RPCs

CARLOSv3 is the third version of a chip that plays a significant role in the data acquisition chain of the A Large Ion Collider Experiment (ALICE) silicon drift detector (SDD). ALICE is one of the foremost high-energy physics experiments (HEPE) conducted within the Large Hadron Collider at CERN, the European Organization for Nuclear Research in Geneva. CARLOSv3 was principally designed and built for the on-line compression of the input dataset originating from a physical bidimensional silicon sensor. To compress a bidimensional dataset, a bidimensional data compressor was required. The compressor was designed for the ALICE SDD Experiment but could be applied to all experiments in which an incoming stream dataset originates from a bidimensional sensor.

ALICE (A Large Ion Collider Experiment) studies the Quark-Gluon Plasma (QGP): a deconfined state of nuclear matter obtained in ultra-relativistic heavy-ion collisions. One of the key probes for QGP characterization is the study of quarkonia and open heavy flavor production, of which ALICE exploits the muonic decay. In particular, a set of Resistive Plate Chambers (RPCs), placed in the forward rapidity region of the ALICE detector, is used for muon identification purposes.The correct operation of these detectors is ensured by the choice of the proper gas mixture. Currently they are operated with a mixture of C2H2F4, i-C4H10 and SF6 but, starting from 2017, new EU regulations have enforced a progressive phase-out of C2H2F4 because of its large Global Warming Potential (GWP), which is making it difficult and costly to purchase. Moreover, CERN asked LHC experiments to reduce greenhouse gases emissions, to which RPC operation contributes significantly.A possible candidate for C2H2F4 replacement is the C3H2F4 (diluted with other gases, such as CO2), which has been extensively tested using cosmic muons. Promising gas mixtures have been devised; the next crucial steps are the detailed in-beam characterization of such mixtures as well as the study of their performance under increasing irradiation levels.This contribution will describe the methodology and results of beam tests carried out at the CERN Gamma Irradiation Facility (equipped with a high activity 137Cs source and muon beam) with an ALICE-like RPC prototype, operated with several mixtures with varying proportions of CO2, C3H2F4, i-C4H10 and SF6 . Absorbed currents, efficiencies, prompt charges, cluster sizes, time resolutions and rate capabilities will be presented, both from digitized (for detailed shape and charge analysis) and discriminated (using the same front-end electronics as employed in ALICE) signals.

ALICE (A Large Ion Collider Experiment) is a general purpose heavy-ion experiment designed for the study of strongly-interacting matter at the extreme energy densities reached in Pb-Pb collisions at the CERN LHC, where the deconfined phase of hadronic matter known as Quark-Gluon Plasma (QGP), is formed. The innermost detector of ALICE is the Inner Tracking System. In its first release, it consists of six cylindrical layers of silicon detectors based on different technologies: two inner layers of pixel sensors (Silicon Pixel Detector), two intermediate layers of drift sensors (Silicon Drift Detector), two outer layers of strip sensors (Silicon Strip Detector). The ITS is used for the reconstruction of primary and secondary vertices, for particle tracking, for a precise determination of the impact parameter and for particle identification at low momentum. In this report, after a brief description of the three subdetectors, the operational experience with the first ITS implementation is summarized, the status and the performance of the detector are described and the lessons learned are discussed after the end of its operation coinciding with the completion of the LHC Run2.

A Large Ion Collider Experiment (ALICE) experiment is one of the four experiments at the Large Hadron Collider (LHC) designed to investigate the status of matter under very high energy densities produced during heavy-ion collisions. The ALICE inner tracking system (ITS) consists of seven concentric cylindrical layers of monolithic silicon pixel sensors known as ALICE pixel detector (ALPIDE). The sensors are used to reconstruct the paths of charged particles generated in the collisions. The sensor alignment of the detector must be adjusted to a high precision standard. The adjustment objective is to obtain a detector that can undertake high-resolution measurements. This paper introduces a method for measuring the reference markers utilized in sensor alignment determination. Markers engraved at the chip corners have been detected using the Hough transform, Canny edge detection, and template matching techniques. The distances between two markers are measured to determine the accuracy of the pixel sensor alignment before and after assembly. The proposed methods exhibit an accuracy exceeding 99% and demonstrate high speed analysis. The average processing times for detecting the circle and cross markers are 105.9 ms/image and 113.8 ms/image, respectively. The sensor alignment of the detector must be adjusted to a high precision standard. However, recent studies have shown deviations of up to 5 μ m above the desired value in the measured sensor position. Such deviations do not represent a major issue, nevertheless it is important to measure them in order to speed-up and make more accurate the recursive track-based alignment procedure used to reconstruct the position of each pixel sensor in the tracking detector. The proposed method offers a promising solution to deliver precise and rapid measurements for a large number of examined objects.

Quark Gluon Plasma (QGP) is an unavoidable consequence of Quantum Chromodynamics (QCD). High-energy heavy-ion collisions offer the unique possibility to reproduce in the laboratory the conditions expected during the very first stages of the evolution of the Universe. The ALICE (A Large Ion Collider Experiment) experiment at the Large Hadron Collider (LHC) allows the study of the dense nuclear environment created in nucleus-nucleus collisions. Particle Identification (PID) is one of the key features of the ALICE experiment. Identified particle spectra represent a crucial tool to understand the behaviour of the matter created in high-energy heavy-ion collisions. The transverse momentum p T distributions of identified hadrons contain information about the transverse expansion of the system and constrain the freeze-out properties of the system. Hydrodynamic models have proved to be very successful reproducing a large number of features of heavy-ion collisions (e.g., particle p T distributions, radial flow, elliptic flow, Hanbury Brown-Twiss correlations, ...). The measurement of the p T distributions of identified π, K and p in Pb-Pb collisions at $$\sqrt {s_{NN} } = 2.76$$ TeV is presented and discussed in terms of hydrodynamics. The V0 detector allows the selection of events based on the eccentricity of the collision (related with the initial geometry). This makes possible the study of the correlation between the p T distribution of hadrons and elliptic flow on an event-by-event basis. Hadron abundances can be obtained from the principle of maximum entropy using statistical concepts. This allows the extrapolation of the chemical freeze-out parameters from the data. Over the last years it has been proved that the chemical freeze-out temperature T ch is connected with the phase transition temperature T C . The measurements of the freeze-out parameters at the LHC energies are described in detail and the results obtained by various groups at lower energies are extended with the inclusion of the LHC measurement. The LHC measurements cast a new light upon the hydrodynamic and thermal behaviour of the hadron production in heavy-ion collisions. The possible scenarios are described and commented.

A Large Ion Collider Experiment (ALICE) at the Large Hadron Collider (LHC) is planing to upgrade its Time Projection Chamber (TPC) due to the expected higher Pb-Pb collision-rates in the next running period (Run 3) of the LHC starting in 2020. In the upgraded TPC, Gas Electron Multiplier (GEM) chambers and continuous readout system will replace Multi-Wire Proportional (MWP) chambers and conventional triggered readout. In the continuous readout, GEM signals will be processed using a 32 channel SAMPA ASIC. The first version of the SAMPA (MPW1) was delivered in 2014 and the production of final version is in progress. In this paper, the test results obtained for charge injection to the device using pulse generator as well as GEM detector prototype are reported.

With the broader dissemination of digital technologies, visionary concepts like the Internet of Things also affect an increasing number of use cases with interfaces to humans, e.g. manufacturing environments with technical operators monitoring the processes. This leads to additional challenges, as besides the technical issues also human aspects have to be considered for a successful implementation of strategic initiatives like Industrie 4.0. From a technical perspective, complex event processing has proven itself in practice to be capable of integrating and analyzing huge amounts of heterogeneous data and establishing a basic level of situation awareness by detecting situations of interests. Whereas this reactive nature of complex event processing systems may be sufficient for machine-to-machine use cases, the new characteristic of application fields with humans remaining in the control loop leads to an increasing action distance and delayed reactions. Taking human aspects into consideration leads to new requirements, with transparency and comprehensibility of the processing of events being the most important ones. Improving the comprehensibility of complex event processing and extending its capabilities towards an effective support of human operators allows tackling technical and non-technical challenges at the same time. The main contribution of this thesis answers the question of how to evolve state-of-the-art complex event processing from its reactive nature towards a transparent and holistic situation management system. The goal is to improve the interaction among systems and humans in use cases with interfaces between both worlds. Realizing a holistic situation management requires three missing capabilities to be introduced by the contributions of this thesis: First, based on the achieved transparency, the retrospective analysis of situations is enabled by collecting information related to a situation's occurrence and development. Therefore, CEP engine-specific situation descriptions are transformed into a common model, allowing the automatic decomposition of the underlying patterns to derive partial patterns describing the intermediate states of processing. Second, by introducing the psychological model of situation awareness into complex event processing, human aspects of information processing are taken into consideration and introduced into the complex event processing paradigm. Based on this model, an extended situation life-cycle and transition method are derived. The introduced concepts and methods allow the implementation of the controlling function of situation management and enable the effective acquisition and maintenance of situation awareness for human operators to purposefully direct their attention towards upcoming situations. Finally, completing the set of capabilities for situation management, an approach is presented to support the generation and integration of prediction models for predictive situation management. Therefore, methods are introduced to automatically label and extract relevant data for the generation of prediction models and to enable the embedding of the resulting models for an automatic evaluation and execution. The contributions are introduced, applied and evaluated along a scenario from the manufacturing domain.

The ATLAS Beam Condition Monitor (BCM) based on radiation hard pCVD diamond sensors and event-by-event measurements of environment close to interaction point (z=±184 cm, r=5.5 cm) has been installed in the Pixel detector since early 2008 and together with the Pixel detector in the ATLAS cavern since June 2008. The sensors and front end electronics were shown to withstand 50 Mrad and 10 particles/cm expected in LHC lifetime. Recently the full readout chain, partly made of radiation tolerant electronics, still inside of the ATLAS spectrometer and partly in the electronics room, was completed and the system was operated in time of the first LHC single beams and is ready now for the first collisions which will follow after the LHC repair.

The study of the bio-recognition phenomena behind a biological process is nowadays considered a useful tool to deeply understand physiological mechanisms allowing the discovery of novel biological target and the development of new lead candidates. Moreover, understanding this kind of phenomena can be helpful in characterizing absorption, distribution, metabolism, elimination and toxicity properties of a new drug (ADMET parameters). Recent estimations show that about half of all drugs in development fail to make it to the market because of ADMET deficiencies; thus a rapid determination of ADMET parameters in early stages of drug discovery would save money and time, allowing to choose the better compound and to eliminate any losers. The monitoring of drug binding to plasma proteins is becoming essential in the field of drug discovery to characterize the drug distribution in human body. Human serum albumin (HSA) is the most abundant protein in plasma playing a fundamental role in the transport of drugs, metabolites and endogenous factors; so the study of the binding mechanism to HSA has become crucial to the early characterization of the pharmacokinetic profile of new potential leads. Furthermore, most of the distribution experiments carried out in vivo are performed on animals. Hence it is interesting to determine the binding of new compounds to albumins from different species to evaluate the reliability of extrapolating the distribution data obtained in animals to humans. It is clear how the characterization of interactions between proteins and drugs determines a growing need of methodologies to study any specific molecular event. A wide variety of biochemical techniques have been applied to this purpose. High-performance liquid affinity chromatography, circular dichroism and optical biosensor represent three techniques that can be able to elucidate the interaction of a new drug with its target and with others proteins that could interfere with ADMET parameters.

A gas-jet monitor has been developed and commissioned by the QUASAR Group at the Cockcroft Institute, UK. It is designed to measure the transverse profile of a beam by crossing it with a neutral supersonic gas-jet. An array of high voltage electrodes is used to extract ions from the region where the beam and gas-jet interact. These ions first hit a micro-channel plate (MCP) and are then imaged through a phosphor screen and a CCD camera. It is important to understand and characterise the measured ion distribution in order to extract the beam profile. Therefore, numerical investigations using the commercial COMSOL and OPERA codes were carried out benchmarking profile measurements obtained from a low energy electron beam. This paper presents results from these studies. It compares measurements based on the interaction of the primary beam with the residual gas or the ultra-cold gas curtain, and discusses the comparisons of simulated profiles and extraction field configurations on the measured profile.

The CIP2K trigger system has become an integral part of the H1 detector for the HERA II run. Its purpose is the reconstruction of the interaction point. Using this z-vertex position events from positron-proton interactions are separated from residual gas background on the first trigger level. A total of 8500 channels transmitted by optical links from a multi-wire proportional chamber are analyzed at a speed of 10.4 MHz in parallel, synchronized to the accelerator clock. The trigger latency is 1 us. The signals are analyzed on 16 Trigger Cards, each holding two Altera APEX20kE400 FPGAs. The system design and first results from the HERA II run are presented.