Systems and algorithms for low-latency event reconsturction for upgrades of the level-1 triger of the CMS experiment at CERN

With the increasing centre-of-mass energy and luminosity of the Large Hadron Collider (LHC), the Compact Muon Experiment (CMS) is undertaking upgrades to its triggering system in order to maintain its data-taking efficiency. In 2016, the Phase-1 upgrade to the CMS Level- 1 Trigger (L1T) was commissioned which required the development of tools for validation of changes to the trigger algorithm firmware and for ongoing monitoring of the trigger system during data-taking. A Phase-2 upgrade to the CMS L1T is currently underway, in preparation for the High-Luminosity upgrade of the LHC (HL-LHC). The HL-LHC environment is expected to be particularly challenging for the CMS L1T due to the increased number of simultaneous interactions per bunch crossing, known as pileup. In order to mitigate the effect of pileup, the CMS Phase-2 Outer Tracker is being upgraded with capabilities which will allow it to provide tracks to the L1T for the first time. A key to mitigating pileup is the ability to identify the location and decay products of the signal vertex in each event. For this purpose, two conventional algorithms have been investigated, with a baseline being proposed and demonstrated in FPGA hardware. To extend and complement the baseline vertexing algorithm, Machine Learning techniques were used to evaluate how different track parameters can be included in the vertex reconstruction process. This work culminated in the creation of a deep convolutional neural network, capable of both position reconstruction and association through the intermediate storage of tracks into a z histogram where the optimal weighting of each track can be learned. The position reconstruction part of this end-to-end model was implemented and when compared to the baseline algorithm, a 30% improvement on the vertex position resolution in tt̄ events was observed.Open Acces

Complexity-reduced hardware-based track-trigger for CMS upgrade

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe Compact Muon Solenoid (CMS) detector at the Large Hadron Collider (LHC) is designed to study the results of proton-proton collisions. The Tracker sub-detector is designed to detect and reconstruct the trajectories of charged particles produced by the collisions. During the lifetime of the CMS detector, there have been several upgrades aimed at increasing the chance of discovering new physics through increased luminosity levels and instrumentation of advanced technology. The High-Luminosity upgrade optimises the LHC to accelerate high-energy particles with an average of 200 proton-proton interactions per bunch crossing. The Level-1 Trigger system promptly analyses and filters collisions using hardware to reduce the data volume in real-time. For the upgrade, the trigger mechanism will use a particle trajectory estimator that discriminates between particles based on their transverse momentum (pT ). Particles with pT ≥ 2 GeV/c will be transmitted to the Level-1 Track-Trigger system for trajectory reconstruction within a fixed 3 μs latency. This thesis presents a novel Hardware-based Multivariate Linear Fitter (MVLF) system focusing on robustness in tracking efficiency and reduction in logic resource usage within the specified latency. The system components are implemented in Field Programmable Gate Arrays (FPGA), targeting 16 nm FinFET UltraScale+ silicon technology. The development was performed using the High-Level Synthesis (HLS) automation tools and the Hardware acceleration platform for Application-Specific Integrated Circuits (ASIC). A firmware demonstrator has been assembled to verify the feasibility and compatibility of the scaled system with the CMS Level-1 Track-Trigger infrastructure. The system’s performance is compared to past and current system developments, and the results are presented accordingly

Charged Particle Tracking in Real-Time Using a Full-Mesh Data Delivery Architecture and Associative Memory Techniques

We present a flexible and scalable approach to address the challenges of charged particle track reconstruction in real-time event filters (Level-1 triggers) in collider physics experiments. The method described here is based on a full-mesh architecture for data distribution and relies on the Associative Memory approach to implement a pattern recognition algorithm that quickly identifies and organizes hits associated to trajectories of particles originating from particle collisions. We describe a successful implementation of a demonstration system composed of several innovative hardware and algorithmic elements. The implementation of a full-size system relies on the assumption that an Associative Memory device with the sufficient pattern density becomes available in the future, either through a dedicated ASIC or a modern FPGA. We demonstrate excellent performance in terms of track reconstruction efficiency, purity, momentum resolution, and processing time measured with data from a simulated LHC-like tracking detector

Development of Trigger and Control Systems for CMS

During the year of 2007, the Large Hadron Collider (LHC) and its four main detectors will begin operation with a view to answering the most pressing questions in particle physics. However before one can analyse the data produced to find the rare phenomena being looked for, both the detector and readout electronics must be thoroughly tested to ensure that the system will operate in a consistent way. The Compact Muon Solenoid (CMS) is one of the two general-purpose detectors at CERN. The tracking component of the design produces more data than any previous detector used in particle physics, with approximately ten million detector channels. The data from the detector is processed by the tracker Front End Driver (FED). The large data volume necessitated the development of a buffering and throttling system to prevent buffer overflow both on and off the detector. A critical component of this system is the APV emulator (APVe), which vetoes trigger decisions based on buffer status in the tracker. The commissioning of these components, along with a large part of the Timing, Trigger and Control (TTC) system is discussed, including the various modifications that were made to improve the robustness of the full system. Another key piece of the CMS electronics is the calorimeter trigger system, responsible for identifying âinteresting' physical events in a background of well-understood phenomena using calorimetric information. Calorimeter information is processed to identify various trigger objects by the Global Calorimeter Trigger (GCT). The first component of this system is the Source card, which has been developed to transfer data from the Regional Calorimeter Trigger (RCT) to the Leaf card, the processing engine of the GCT. The use of modern programmable logic with high speed optical links is discussed, emphasising its use for data concentration and the benefit it confers to the processing algorithms. Looking forward to Super-LHC, a possible addition to the CMS Level-1 trigger system is discussed, incorporating information from a new pixel detector with an alternative stacked geometry that allows the possibility of on-detector data rate reduction by means of a transverse momentum cut. A toy Monte Carlo was developed to study detector performance. Issues with high-speed reconstruction and the complications of on-detector data rate reduction are also discussed

EUDAQ - A data acquisition software framework for common beam telescopes

EUDAQ is a generic data acquisition software developed for use in conjunction with common beam telescopes at charged particle beam lines. Providing high-precision reference tracks for performance studies of new sensors, beam telescopes are essential for the research and development towards future detectors for high-energy physics. As beam time is a highly limited resource, EUDAQ has been designed with reliability and ease-of-use in mind. It enables flexible integration of different independent devices under test via their specific data acquisition systems into a top-level framework. EUDAQ controls all components globally, handles the data flow centrally and synchronises and records the data streams. Over the past decade, EUDAQ has been deployed as part of a wide range of successful test beam campaigns and detector development applications

Research and development for the data, trigger and control card in preparation for Hi-Lumi lhc

When the Large Hadron Collider (LHC) increases its luminosity by an order of magnitude in the coming decade, the experiments that sit upon it must also be upgraded to continue to their physics performance in the increasingly demanding environment. To achieve this, the Compact Muon Solenoid (CMS) experiment will make use of tracking information in the Level-1 trigger for the first time, meaning that track reconstruction must be achieved in less than 4 μs in an all-FPGA architecture. MUonE is an experiment aiming to make an accurate measurement of the the hadronic contribution to the anomalous magnetic moment of the muon. It will achieve this by making use of similar apparatus to that designed for CMS and benefit from the research and development efforts there. This thesis presents both development and testing work for the readout chain from tracker module to back-end processing card, as well as the results and analysis of a beam test used to validate this chain for both CMS and the MUonE experiment.Open Acces

ATLAS Upgrade Instrumentation in the US

Planned upgrades of the LHC over the next decade should allow the machine to operate at a center of mass energy of 14 TeV with instantaneous luminosities in the range 5--7e34 cm^-2 s^-1. With these parameters, ATLAS could collect 3,000 fb^-1 of data in approximately 10 years. However, the conditions under which this data would be acquired are much harsher than those currently encountered at the LHC. For example, the number of proton-proton interactions per bunch crossing will rise from the level of 20--30 per 50 ns crossing observed in 2012 to 140--200 every 25 ns. In order to deepen our understanding of the newly discovered Higgs boson and to extend our searches for physics beyond that new particle, the ATLAS detector, trigger, and readout will have to undergo significant upgrades. In this whitepaper we describe R&D necessary for ATLAS to continue to run effectively at the highest luminosities foreseen from the LHC. Emphasis is placed on those R&D efforts in which US institutions are playing a leading role.Comment: Snowmass contributed paper, 24 pages, 12 figure

Infrastructure for Detector Research and Development towards the International Linear Collider

The EUDET-project was launched to create an infrastructure for developing and testing new and advanced detector technologies to be used at a future linear collider. The aim was to make possible experimentation and analysis of data for institutes, which otherwise could not be realized due to lack of resources. The infrastructure comprised an analysis and software network, and instrumentation infrastructures for tracking detectors as well as for calorimetry.Comment: 54 pages, 48 picture