Simulation Studies of Digital Filters for the Phase-II Upgrade of the Liquid-Argon Calorimeters of the ATLAS Detector at the High-Luminosity LHC

Am Large Hadron Collider und am ATLAS-Detektor werden umfangreiche Aufrüstungsarbeiten vorgenommen. Diese Arbeiten sind in mehrere Phasen gegliedert und umfassen unter Anderem Änderungen an der Ausleseelektronik der Flüssigargonkalorimeter; insbesondere ist es geplant, während der letzten Phase ihren Primärpfad vollständig auszutauschen. Die Elektronik besteht aus einem analogen und einem digitalen Teil: während ersterer die Signalpulse verstärkt und sie zur leichteren Abtastung verformt, führt letzterer einen Algorithmus zur Energierekonstruktion aus. Beide Teile müssen während der Aufrüstung verbessert werden, damit der Detektor interessante Kollisionsereignisse präzise rekonstruieren und uninteressante effizient verwerfen kann. In dieser Dissertation werden Simulationsstudien präsentiert, die sowohl die analoge als auch die digitale Auslese der Flüssigargonkalorimeter optimieren. Die Korrektheit der Simulation wird mithilfe von Kalibrationsdaten geprüft, die im sog. Run 2 des ATLAS-Detektors aufgenommen worden sind. Der Einfluss verschiedener Parameter der Signalverformung auf die Energieauflösung wird analysiert und die Nützlichkeit einer erhöhten Abtastrate von 80 MHz untersucht. Des Weiteren gibt diese Arbeit eine Übersicht über lineare und nichtlineare Energierekonstruktionsalgorithmen. Schließlich wird eine Auswahl von ihnen hinsichtlich ihrer Leistungsfähigkeit miteinander verglichen. Es wird gezeigt, dass ein Erhöhen der Ordnung des Optimalfilters, der gegenwärtig verwendete Algorithmus, die Energieauflösung um 2 bis 3 % verbessern kann, und zwar in allen Regionen des Detektors. Der Wiener Filter mit Vorwärtskorrektur, ein nichtlinearer Algorithmus, verbessert sie um bis zu 10 % in einigen Regionen, verschlechtert sie aber in anderen. Ein Zusammenhang dieses Verhaltens mit der Wahrscheinlichkeit fälschlich detektierter Kalorimetertreffer wird aufgezeigt und mögliche Lösungen werden diskutiert.:1 Introduction 2 An Overview of High-Energy Particle Physics 2.1 The Standard Model of Particle Physics 2.2 Verification of the Standard Model 2.3 Beyond the Standard Model 3 LHC, ATLAS, and the Liquid-Argon Calorimeters 3.1 The Large Hadron Collider 3.2 The ATLAS Detector 3.3 The ATLAS Liquid-Argon Calorimeters 4 Upgrades to the ATLAS Liquid-Argon Calorimeters 4.1 Physics Goals 4.2 Phase-I Upgrade 4.3 Phase-II Upgrade 5 Noise Suppression With Digital Filters 5.1 Terminology 5.2 Digital Filters 5.3 Wiener Filter 5.4 Matched Wiener Filter 5.5 Matched Wiener Filter Without Bias 5.6 Timing Reconstruction, Optimal Filtering, and Selection Criteria 5.7 Forward Correction 5.8 Sparse Signal Restoration 5.9 Artificial Neural Networks 6 Simulation of the ATLAS Liquid-Argon Calorimeter Readout Electronics 6.1 AREUS 6.2 Hit Generation and Sampling 6.3 Pulse Shapes 6.4 Thermal Noise 6.5 Quantization 6.6 Digital Filters 6.7 Statistical Analysis 7 Results of the Readout Electronics Simulation Studies 7.1 Statistical Treatment 7.2 Simulation Verification Using Run-2 Data 7.3 Dependence of the Noise on the Shaping Time 7.4 The Analog Readout Electronics and the ADC 7.5 The Optimal Filter (OF) 7.6 The Wiener Filter 7.7 The Wiener Filter with Forward Correction (WFFC) 7.8 Final Comparison and Conclusions 8 Conclusions and Outlook AppendicesThe Large Hadron Collider and the ATLAS detector are undergoing a comprehensive upgrade split into multiple phases. This effort also affects the liquid-argon calorimeters, whose main readout electronics will be replaced completely during the final phase. The electronics consist of an analog and a digital portion: the former amplifies the signal and shapes it to facilitate sampling, the latter executes an energy reconstruction algorithm. Both must be improved during the upgrade so that the detector may accurately reconstruct interesting collision events and efficiently suppress uninteresting ones. In this thesis, simulation studies are presented that optimize both the analog and the digital readout of the liquid-argon calorimeters. The simulation is verified using calibration data that has been measured during Run 2 of the ATLAS detector. The influence of several parameters of the analog shaping stage on the energy resolution is analyzed and the utility of an increased signal sampling rate of 80 MHz is investigated. Furthermore, a number of linear and non-linear energy reconstruction algorithms is reviewed and the performance of a selection of them is compared. It is demonstrated that increasing the order of the Optimal Filter, the algorithm currently in use, improves energy resolution by 2 to 3 % in all detector regions. The Wiener filter with forward correction, a non-linear algorithm, gives an improvement of up to 10 % in some regions, but degrades the resolution in others. A link between this behavior and the probability of falsely detected calorimeter hits is shown and possible solutions are discussed.:1 Introduction 2 An Overview of High-Energy Particle Physics 2.1 The Standard Model of Particle Physics 2.2 Verification of the Standard Model 2.3 Beyond the Standard Model 3 LHC, ATLAS, and the Liquid-Argon Calorimeters 3.1 The Large Hadron Collider 3.2 The ATLAS Detector 3.3 The ATLAS Liquid-Argon Calorimeters 4 Upgrades to the ATLAS Liquid-Argon Calorimeters 4.1 Physics Goals 4.2 Phase-I Upgrade 4.3 Phase-II Upgrade 5 Noise Suppression With Digital Filters 5.1 Terminology 5.2 Digital Filters 5.3 Wiener Filter 5.4 Matched Wiener Filter 5.5 Matched Wiener Filter Without Bias 5.6 Timing Reconstruction, Optimal Filtering, and Selection Criteria 5.7 Forward Correction 5.8 Sparse Signal Restoration 5.9 Artificial Neural Networks 6 Simulation of the ATLAS Liquid-Argon Calorimeter Readout Electronics 6.1 AREUS 6.2 Hit Generation and Sampling 6.3 Pulse Shapes 6.4 Thermal Noise 6.5 Quantization 6.6 Digital Filters 6.7 Statistical Analysis 7 Results of the Readout Electronics Simulation Studies 7.1 Statistical Treatment 7.2 Simulation Verification Using Run-2 Data 7.3 Dependence of the Noise on the Shaping Time 7.4 The Analog Readout Electronics and the ADC 7.5 The Optimal Filter (OF) 7.6 The Wiener Filter 7.7 The Wiener Filter with Forward Correction (WFFC) 7.8 Final Comparison and Conclusions 8 Conclusions and Outlook Appendice

Test of machine learning at the CERN LINAC4

The CERN H− linear accelerator, LINAC4, served as a test bed for advanced algorithms during the CERN Long Shutdown 2 in the years 2019/20. One of the main goals was to show that reinforcement learning with all its benefits can be used as a replacement for numerical optimization and as a complement to classical control in the accelerator control context. Many of the algorithms used were prepared before- hand at the electron line of the AWAKE facility to make the best use of the limited time available at LINAC4. An overview of the algorithms and concepts tested at LINAC4 and AWAKE will be given and the results discussed.peer-reviewe

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

AREUS - a software framework for ATLAS Readout Electronics Upgrade Simulation

The design of readout electronics for the LAr calorimeters of the ATLAS detector to be operated at the future High-Luminosity LHC (HL-LHC) requires a detailed simulation of the full readout chain in order to find optimal solutions for the analog and digital processing of the detector signals. Due to the long duration of the LAr calorimeter pulses relative to the LHC bunch crossing time, out-of-time signal pileup needs to be taken into account. For this purpose, the simulation framework AREUS has been developed. It models analog-to-digital conversion, gain selection, and digital signal processing at bit precision, including digitization noise and detailed electronics effects. Trigger and object reconstruction algorithms are taken into account in the optimization process. The software implementation of AREUS, the concepts of its main functional blocks, as well as optimization considerations will be presented. Various approaches to introduce parallelism into AREUS will be compared against each other

Untersuchung differenzieller Verteilungen für die Streuung zweier Eichbosonen → am Large Hadron Collider

The electroweak symmetry breaking (abbr. EWSB) is a crucial test of the Standard Mo del and an imp ortant starting p oint for physics b eyond the Standard Mo del. The EWSB is b est investigated by means of longitudinally p olarized vector b osons. However, this vector b oson scattering (VBS) interferes with many background pro cesses of the same final state; these background pro cesses may b e purely electroweak (just as VBS) or partially strong. In this thesis, the interference b etween all purely electroweak pro cesses (including VBS) on the one hand and all partially strong pro cesses on the other hand is investigated. A weight change function 1+ is parameterized and applied to the QCD background in order to merge the QCD background and the interference. Thus, one can substract b oth terms from the measurement signal

Development of ATLAS Liquid Argon Calorimeter Readout Electronics for the HL-LHC

The LHC high-luminosity upgrade in 2024-2026 requires the associated detectors to operate at luminosities about 5-7 times larger than assumed in their original design. The pile-up is expected to increase to up to 200 events per proton bunch-crossing. To be able to retain interesting physics events even at rather low transverse energy scales, increased trigger rates are foreseen for the ATLAS detector. At the hardware selection stage acceptance rates of 1 MHz are planned, combined with longer latencies up to 60 micro-seconds in order to read out the necessary data from all detector channels. Under these conditions, the current readout of the ATLAS Liquid Argon (LAr) Calorimeters does not provide sufficient buffering and bandwidth capabilities. Furthermore, the expected total radiation doses are beyond the qualification range of the current front-end electronics. For these reasons a replacement of the LAr front-end and back-end readout system is foreseen for all 182,500 readout channels, with the exception of the cold pre-amplifier and summing devices of the hadronic LAr Calorimeter. The new low-power electronics must be able to capture the triangular detector pulses of about 400-600 nano-seconds length with signal currents up to 10 mA and a dynamic range of 16 bit. Different technologies to meet these requirements are under evaluation: A preamplifier in 130nm CMOS technology with two gain stages can cover the desired dynamic range while meeting the required noise levels and non-linearity values. Alternatively, developments of pre-amplifier, shaper as well as ADCs are performed in 65 nm CMOS technology. Due to the lower voltage range, 2-gain and 4-gain designs of the analog part are studied with programmable peaking time to optimize the noise level in presence of signal pile-up. Radiation-hard, 14 bit ADC operating at 40 or 80 MHz are also being studied. Results from performance-simulation of the calorimeter readout system for the different options and results from design studies and first tests of the components will be presented

AREUS - a software framework for ATLAS Readout Electronics Upgrade Simulation

The design of readout electronics for the LAr calorimeters of the ATLAS detector to be operated at the future High-Luminosity LHC (HL-LHC) requires a detailed simulation of the full readout chain in order to find optimal solutions for the analog and digital processing of the detector signals. Due to the long duration of the LAr calorimeter pulses relative to the LHC bunch crossing time, out-of-time signal pile-up needs to be taken into account and realistic pulse sequences must be simulated together with the response of the electronics. For this purpose, the ATLAS Readout Electronics Upgrade Simulation framework (AREUS) has been developed based on the Observer design pattern to provide a fast and flexible simulation tool. Energy deposits in the LAr calorimeters from fully simulated HL-LHC collision events are taken as input. Simulated and measured analog pulse shapes proportional to these energies are then combined in discrete time series with proper representation of electronics noise. Analog-to-digital conversion, gain selection and digital signal processing are modeled at bit precision, including digitization noise and detailed electronics effects. In this way signal processing techniques can be optimized with respect to physics parameters like reconstructed energy and signal time in each channel. Finally, trigger and object reconstruction algorithms are taken into account in the optimization process. The software implementation of AREUS, the concepts of its main functional blocks and examples of obtained simulation results will be presented

AREUS - a software framework for ATLAS Readout Electronics Upgrade Simulation

The design of readout electronics for the LAr calorimeters of the ATLAS detector to be operated at the future High-Luminosity LHC (HL-LHC) requires a detailed simulation of the full readout chain in order to find optimal solutions for the analog and digital processing of the detector signals. Due to the long duration of the LAr calorimeter pulses relative to the LHC bunch crossing time, out-of-time signal pileup needs to be taken into account. For this purpose, the simulation framework AREUS has been developed. It models analog-to-digital conversion, gain selection, and digital signal processing at bit precision, including digitization noise and detailed electronics effects. Trigger and object reconstruction algorithms are taken into account in the optimization process. The software implementation of AREUS, the concepts of its main functional blocks, as well as optimization considerations will be presented. Various approaches to introduce parallelism into AREUS will be compared against each other

Simulation Studies of Digital Filters for the Phase-II Upgrade of the Liquid-Argon Calorimeters of the ATLAS Detector at the High-Luminosity LHC

Am Large Hadron Collider und am ATLAS-Detektor werden umfangreiche Aufrüstungsarbeiten vorgenommen. Diese Arbeiten sind in mehrere Phasen gegliedert und umfassen unter Anderem Änderungen an der Ausleseelektronik der Flüssigargonkalorimeter; insbesondere ist es geplant, während der letzten Phase ihren Primärpfad vollständig auszutauschen. Die Elektronik besteht aus einem analogen und einem digitalen Teil: während ersterer die Signalpulse verstärkt und sie zur leichteren Abtastung verformt, führt letzterer einen Algorithmus zur Energierekonstruktion aus. Beide Teile müssen während der Aufrüstung verbessert werden, damit der Detektor interessante Kollisionsereignisse präzise rekonstruieren und uninteressante effizient verwerfen kann. In dieser Dissertation werden Simulationsstudien präsentiert, die sowohl die analoge als auch die digitale Auslese der Flüssigargonkalorimeter optimieren. Die Korrektheit der Simulation wird mithilfe von Kalibrationsdaten geprüft, die im sog. Run 2 des ATLAS-Detektors aufgenommen worden sind. Der Einfluss verschiedener Parameter der Signalverformung auf die Energieauflösung wird analysiert und die Nützlichkeit einer erhöhten Abtastrate von 80 MHz untersucht. Des Weiteren gibt diese Arbeit eine Übersicht über lineare und nichtlineare Energierekonstruktionsalgorithmen. Schließlich wird eine Auswahl von ihnen hinsichtlich ihrer Leistungsfähigkeit miteinander verglichen. Es wird gezeigt, dass ein Erhöhen der Ordnung des Optimalfilters, der gegenwärtig verwendete Algorithmus, die Energieauflösung um 2 bis 3 % verbessern kann, und zwar in allen Regionen des Detektors. Der Wiener Filter mit Vorwärtskorrektur, ein nichtlinearer Algorithmus, verbessert sie um bis zu 10 % in einigen Regionen, verschlechtert sie aber in anderen. Ein Zusammenhang dieses Verhaltens mit der Wahrscheinlichkeit fälschlich detektierter Kalorimetertreffer wird aufgezeigt und mögliche Lösungen werden diskutiert.:1 Introduction 2 An Overview of High-Energy Particle Physics 2.1 The Standard Model of Particle Physics 2.2 Verification of the Standard Model 2.3 Beyond the Standard Model 3 LHC, ATLAS, and the Liquid-Argon Calorimeters 3.1 The Large Hadron Collider 3.2 The ATLAS Detector 3.3 The ATLAS Liquid-Argon Calorimeters 4 Upgrades to the ATLAS Liquid-Argon Calorimeters 4.1 Physics Goals 4.2 Phase-I Upgrade 4.3 Phase-II Upgrade 5 Noise Suppression With Digital Filters 5.1 Terminology 5.2 Digital Filters 5.3 Wiener Filter 5.4 Matched Wiener Filter 5.5 Matched Wiener Filter Without Bias 5.6 Timing Reconstruction, Optimal Filtering, and Selection Criteria 5.7 Forward Correction 5.8 Sparse Signal Restoration 5.9 Artificial Neural Networks 6 Simulation of the ATLAS Liquid-Argon Calorimeter Readout Electronics 6.1 AREUS 6.2 Hit Generation and Sampling 6.3 Pulse Shapes 6.4 Thermal Noise 6.5 Quantization 6.6 Digital Filters 6.7 Statistical Analysis 7 Results of the Readout Electronics Simulation Studies 7.1 Statistical Treatment 7.2 Simulation Verification Using Run-2 Data 7.3 Dependence of the Noise on the Shaping Time 7.4 The Analog Readout Electronics and the ADC 7.5 The Optimal Filter (OF) 7.6 The Wiener Filter 7.7 The Wiener Filter with Forward Correction (WFFC) 7.8 Final Comparison and Conclusions 8 Conclusions and Outlook AppendicesThe Large Hadron Collider and the ATLAS detector are undergoing a comprehensive upgrade split into multiple phases. This effort also affects the liquid-argon calorimeters, whose main readout electronics will be replaced completely during the final phase. The electronics consist of an analog and a digital portion: the former amplifies the signal and shapes it to facilitate sampling, the latter executes an energy reconstruction algorithm. Both must be improved during the upgrade so that the detector may accurately reconstruct interesting collision events and efficiently suppress uninteresting ones. In this thesis, simulation studies are presented that optimize both the analog and the digital readout of the liquid-argon calorimeters. The simulation is verified using calibration data that has been measured during Run 2 of the ATLAS detector. The influence of several parameters of the analog shaping stage on the energy resolution is analyzed and the utility of an increased signal sampling rate of 80 MHz is investigated. Furthermore, a number of linear and non-linear energy reconstruction algorithms is reviewed and the performance of a selection of them is compared. It is demonstrated that increasing the order of the Optimal Filter, the algorithm currently in use, improves energy resolution by 2 to 3 % in all detector regions. The Wiener filter with forward correction, a non-linear algorithm, gives an improvement of up to 10 % in some regions, but degrades the resolution in others. A link between this behavior and the probability of falsely detected calorimeter hits is shown and possible solutions are discussed.:1 Introduction 2 An Overview of High-Energy Particle Physics 2.1 The Standard Model of Particle Physics 2.2 Verification of the Standard Model 2.3 Beyond the Standard Model 3 LHC, ATLAS, and the Liquid-Argon Calorimeters 3.1 The Large Hadron Collider 3.2 The ATLAS Detector 3.3 The ATLAS Liquid-Argon Calorimeters 4 Upgrades to the ATLAS Liquid-Argon Calorimeters 4.1 Physics Goals 4.2 Phase-I Upgrade 4.3 Phase-II Upgrade 5 Noise Suppression With Digital Filters 5.1 Terminology 5.2 Digital Filters 5.3 Wiener Filter 5.4 Matched Wiener Filter 5.5 Matched Wiener Filter Without Bias 5.6 Timing Reconstruction, Optimal Filtering, and Selection Criteria 5.7 Forward Correction 5.8 Sparse Signal Restoration 5.9 Artificial Neural Networks 6 Simulation of the ATLAS Liquid-Argon Calorimeter Readout Electronics 6.1 AREUS 6.2 Hit Generation and Sampling 6.3 Pulse Shapes 6.4 Thermal Noise 6.5 Quantization 6.6 Digital Filters 6.7 Statistical Analysis 7 Results of the Readout Electronics Simulation Studies 7.1 Statistical Treatment 7.2 Simulation Verification Using Run-2 Data 7.3 Dependence of the Noise on the Shaping Time 7.4 The Analog Readout Electronics and the ADC 7.5 The Optimal Filter (OF) 7.6 The Wiener Filter 7.7 The Wiener Filter with Forward Correction (WFFC) 7.8 Final Comparison and Conclusions 8 Conclusions and Outlook Appendice

Machine Learning Platform: Deploying and Managing Models in the CERN Control System

Recent advances make machine learning (ML) a powerful tool to cope with the inherent complexity of accelerators, the large number of degrees of freedom and continuously drifting machine characteristics. A diverse set of ML ecosystems, frameworks and tools are already being used at CERN for a variety of use cases such as optimization, anomaly detection and forecasting. We have adopted a unified approach to model storage, versioning and deployment which accommodates this diversity, and we apply software engineering best practices to achieve the reproducibility needed in the mission-critical context of particle accelerator controls. This paper describes CERN Machine Learning Platform - our central platform for storing, versioning and deploying ML models in the CERN Control Center. We present a unified solution which allows users to create, update and deploy models with minimal effort, without constraining their workflow or restricting their choice of tools. It also provides tooling to automate seamless model updates as the machine characteristics evolve. Moreover, the system allows model developers to focus on domain-specific development by abstracting infrastructural concerns