The LHCb vertex locator upgrade — the detector calibration overview

The Vertex Locator (VELO) is a silicon tracking detector in the spectrometer of the Large Hadron Collider beauty (LHCb) experiment. LHCb explores and investigates CP violation phenomena in b- and c- hadron decays and is one of the experiments operating on the Large Hadron Collider (LHC) at CERN. After run 1 and run 2 of LHC data taking (2011–2018), the LHCb detectors are being modernized within the LHCb upgrade I program. The upgrade aims to adjust the spectrometer to readout at full LHC 40 MHz frequency, which requires radical changes to the technologies currently used in LHCb. The hardware trigger is removed, and some of the detectors replaced. The VELO changes its tracking technology and silicon strips are replaced by 55 μm pitch silicon pixels. The readout chip for the VELO upgrade is the VeloPix ASIC. The number of readout channels increases to over 40 million, and the hottest ASIC is expected to produce the output data rate of 15 Gbit/s. New conditions challenge the software and the hardware side of the readout system and put special attention on the detector monitoring. This paper presents the upgraded VELO design and outlines the software aspects of the detector calibration in the upgrade I. An overview of the challenges foreseen for the upgrade II is given.

Beam test results of silicon sensor module prototypes for the Phase-2 Upgrade of the CMS Outer Tracker

The start of the High-Luminosity LHC (HL-LHC) in 2027 requires upgrades to the Compact Muon Solenoid (CMS) experiment. In the scope of the upgrade program the complete silicon tracking detector will be replaced. The new CMS Tracker will be equipped with silicon pixel detectors in the inner layers closest to the interaction point and silicon strip detectors in the outer layers. The new CMS Outer Tracker will consist of two different kinds of detector modules called PS and 2S modules. Each module will be made of two parallel silicon sensors (a macro-pixel sensor and a strip sensor for the PS modules and two strip sensors for the 2S modules). Combining the hit information of both sensor layers, it is possible to estimate the transverse momentum of particles in the magnetic field of 3.8 T at the full bunch-crossing rate of 40 MHz directly on the module. This information will be used as an input for the first trigger stage of CMS. It is necessary to validate the Outer Tracker module functionality before installing the modules in the CMS experiment. Besides laboratory-based tests several 2S module prototypes have been studied at test beam facilities at CERN, DESY and FNAL. This article concentrates on the beam tests at DESY during which the functionality of the module concept was investigated using the full final readout chain for the first time. Additionally the performance of a 2S module assembled with irradiated sensors was studied. By choosing an irradiation fluence expected for 2S modules at the end of HL-LHC operation, it was possible to investigate the particle detection efficiency and study the trigger capabilities of the module at the beginning and end of the runtime of the CMS experiment.

Hybrid quantum classical graph neural networks for particle track reconstruction

The Large Hadron Collider (LHC) at the European Organisation for Nuclear Research (CERN) will be upgraded to further increase the instantaneous rate of particle collisions (luminosity) and become the High Luminosity LHC (HL-LHC). This increase in luminosity will significantly increase the number of particles interacting with the detector. The interaction of particles with a detector is referred to as “hit”. The HL-LHC will yield many more detector hits, which will pose a combinatorial challenge by using reconstruction algorithms to determine particle trajectories from those hits. This work explores the possibility of converting a novel graph neural network model, that can optimally take into account the sparse nature of the tracking detector data and their complex geometry, to a hybrid quantum-classical graph neural network that benefits from using variational quantum layers. We show that this hybrid model can perform similar to the classical approach. Also, we explore parametrized quantum circuits (PQC) with different expressibility and entangling capacities, and compare their training performance in order to quantify the expected benefits. These results can be used to build a future road map to further develop circuit-based hybrid quantum-classical graph neural networks.

Searching for the Muon Decay to Three Electrons with the Mu3e Experiment

Mu3e is a dedicated experiment designed to find or exclude the charged lepton flavor violating μ→ eee decay at branching fractions above 10−16. The search is pursued in two operational phases: Phase I uses an existing beamline at the Paul Scherrer Institute (PSI), targeting a single event sensitivity of 2·10−15, while the ultimate sensitivity is reached in Phase II using a high intensity muon beamline under study at PSI. As the μ→ eee decay is heavily suppressed in the Standard Model of particle physics, the observation of such a signal would be an unambiguous indication of the existence of new physics. Achieving the desired sensitivity requires a high rate of muons (108 stopped muons per second) along with a detector with large kinematic acceptance and efficiency, able to reconstruct the low momentum of the decay electrons and positrons. To achieve this goal, the Mu3e experiment is mounted with an ultra thin tracking detector based on monolithic active pixel sensors for excellent momentum and vertex resolution, combined with scintillating fibers and tiles for precise timing measurements.

Performance of a geometric deep learning pipeline for HL-LHC particle tracking

The Exa.TrkX project has applied geometric learning concepts such as metric learning and graph neural networks to HEP particle tracking. Exa.TrkX’s tracking pipeline groups detector measurements to form track candidates and filters them. The pipeline, originally developed using the TrackML dataset (a simulation of an LHC-inspired tracking detector), has been demonstrated on other detectors, including DUNE Liquid Argon TPC and CMS High-Granularity Calorimeter. This paper documents new developments needed to study the physics and computing performance of the Exa.TrkX pipeline on the full TrackML dataset, a first step towards validating the pipeline using ATLAS and CMS data. The pipeline achieves tracking efficiency and purity similar to production tracking algorithms. Crucially for future HEP applications, the pipeline benefits significantly from GPU acceleration, and its computational requirements scale close to linearly with the number of particles in the event.

Manufacturing technologies and joining methods of metallic thin-walled pipes for use in high pressure cooling systems

Small diameter thin-walled pipes, typically with a diameter less than 20 mm and a ratio of outer diameter to wall thickness is 20 or above, have increasingly become a key value adding factor for a number of industries including medical applications, electronics and chemical industries. In high-energy physics experiments, thin-walled pipes are needed in tracking detector cooling systems where the mass of all components needs to be minimised for physics measurement reasons. The pipework must reliably withstand the cooling fluid operation pressures (of up to 100 bar), but must also be able to be reliably and easily joined within the cooling system. Suitable standard and/or commercial solutions combining the needed low mass and reliable high-pressure operation are poorly available. The following review of literature compares the various techniques that exist for the manufacture and joining of thin-walled pipes, both well-established techniques and novel methods which have potential to increase the use of thin-walled pipes within industrial cooling systems. Gaps in knowledge have been identified, along with further research directions. Operational challenges and key considerations which have to be identified when designing a system which uses thin-walled pipes are also discussed.