Related papers: Charged Particle Tracking with Machine Learning on…
In general-purpose particle detectors, the particle-flow algorithm may be used to reconstruct a comprehensive particle-level view of the event by combining information from the calorimeters and the trackers, significantly improving the…
High-Energy Physics experiments are facing a multi-fold data increase with every new iteration. This is certainly the case for the upcoming High-Luminosity LHC upgrade. Such increased data processing requirements forces revisions to almost…
The planned upgrade of the CMS detector for the High Luminosity LHC allows to find tracks in the silicon tracker for every single LHC collision and use them in the first level (hardware) trigger decision. So far, studies by CMS…
Despite significant advances in particle imaging technologies over the past two decades, few advances have been made in particle tracking, i.e. linking individual particle positions across time series data. The state-of-the-art tracking…
We propose a model-independent approach for the search of charged long-lived particles produced in ultraperipheral collisions at the LHC. The main idea is to improve event reconstruction at ATLAS and CMS with the help of their forward…
Charged particle track reconstruction in silicon detectors of collider experiments in high-multiplicity events, such as heavy-ion collisions at LHC, is a difficult and resource-demanding process. The first phase of the procedure is the…
The increasing computing power and bandwidth of FPGAs opens new possibilities in the field of real-time processing of high-energy physics data. The LHCb experiment has implemented a cluster-finder FPGA architecture aimed at reconstructing…
Space-based X-ray detectors are subject to significant fluxes of charged particles in orbit, notably energetic cosmic ray protons, contributing a significant background. We develop novel machine learning algorithms to detect charged…
The planned high-luminosity upgrade of the Large Hadron Collider (LHC) at CERN will bring much higher data rates that are far above the capabilities of currently installed software-based data processing systems. Therefore, new methods must…
Three machine learning models are used to perform jet origin classification. These models are optimized for deployment on a field-programmable gate array device. In this context, we demonstrate how latency and resource consumption scale…
For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as GPGPU, ARM and Intel…
Machine learning entails a broad range of techniques that have been widely used in Science and Engineering since decades. High-energy physics has also profited from the power of these tools for advanced analysis of colliders data. It is…
Real-time data processing is one of the central processes of particle physics experiments which require large computing resources. The LHCb (Large Hadron Collider beauty) experiment will be upgraded to cope with a particle bunch collision…
Power density constraints are limiting the performance improvements of modern CPUs. To address this we have seen the introduction of lower-power, multi-core processors such as GPGPU, ARM and Intel MIC. To stay within the power density…
We study the impact of picosecond precision timing detection systems on the LHC experiments' long-lived particle search program during the HL-LHC era. We develop algorithms that allow us to reconstruct the mass of such charged particles and…
The increasing data rates and complexity of detectors at the Large Hadron Collider (LHC) necessitate fast and efficient machine learning models, particularly for rapid selection of what data to store, known as triggering. Building on recent…
Millions of particles are collided every second at the LHCb detector placed inside the Large Hadron Collider at CERN. The particles produced as a result of these collisions pass through various detecting devices which will produce a…
The growing luminosity frontier at the Large Hadron Collider is challenging the reconstruction and analysis of particle collision events. Increased particle multiplicities are straining latency and storage requirements at the data…
The charged particle production in proton-proton collisions is studied with the LHCb detector at a centre-of-mass energy of ${\sqrt{s} =7}$TeV in different intervals of pseudorapidity $\eta$. The charged particles are reconstructed close to…
Many compelling beyond the Standard Model scenarios predict signals that result in unconventional charged particle trajectories. Signatures for which unusual tracks are the most conspicuous feature of the event pose significant challenges…