Related papers: On-chip probabilistic inference for charged-partic…
There can be numerous electronic components on a given PCB, making the task of visual inspection to detect defects very time-consuming and prone to error, especially at scale. There has thus been significant interest in automatic PCB…
As deep learning models are deployed on resource constrained edge platforms in autonomous driving systems, reli able knowledge of hardware behavior under resource degradation becomes an essential requirement. Therefore, we introduce a…
Neural simulation-based inference is a powerful class of machine-learning-based methods for statistical inference that naturally handles high-dimensional parameter estimation without the need to bin data into low-dimensional summary…
The increasing data rates in modern high-energy physics experiments such as ALICE at the LHC and the upcoming ePIC experiment at the Electron-Ion Collider (EIC) present significant challenges in real-time event selection and data storage.…
The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environments and operational constraints. Harnessing this data for…
Particle-in-cell codes are the most widely used simulation tools for kinetic studies of ultra-intense laser-plasma interactions. Using the motion of a single electron in a plane electromagnetic wave as a benchmark problem, we show…
The high-luminosity upgrade of the CERN LHC requires the replacement of the CMS tracking detector to cope with the increased radiation fluence while maintaining its excellent performance. An extensive R\&D program, aiming at using 3D pixel…
3D silicon detectors, in which the electrodes penetrate the sensor bulk perpendicular to the surface, have recently undergone a rapid development from R\&D over industrialisation to their first installation in a real high-energy-physics…
Future high-luminosity hadron colliders demand tracking detectors with extreme radiation tolerance, high spatial precision, and sub-nanosecond timing. 3D diamond pixel sensors offer these capabilities due to diamond's radiation hardness and…
We present the concept of a new type of silicon tracking sensor called Enhanced Lateral Drift (ELAD) sensor. In ELAD sensors the spatial resolution of the impact position of ionising particles is improved by a dedicated charge sharing…
Silicon sensors are the most diffuse position sensitive device in particle physics 8 experiments and in countless applications in science and technology. They had a spectacular progress in performance over almost 40 years since their first…
The ATLAS experiment, at the Large Hadron Collider, will incorporate discrete, high-resolution tracking sub-systems in the form of segmented silicon detectors with 40MHz radiation-hard readout electronics. In the region closest to the pp…
Probabilistic circuits (PCs) offer a promising avenue to perform embedded reasoning under uncertainty. They support efficient and exact computation of various probabilistic inference tasks by design. Hence, hardware-efficient computation of…
Resource-constrained Edge Devices (EDs), e.g., IoT sensors and microcontroller units, are expected to make intelligent decisions using Deep Learning (DL) inference at the edge of the network. Toward this end, there is a significant research…
The accurate and precise extraction of information from a modern particle physics detector, such as an electromagnetic calorimeter, may be complicated and challenging. In order to overcome the difficulties we propose processing the detector…
The development of an innovative position sensitive pixelated sensor to detect and measure with high precision the coordinates of the ionizing particles is proposed. The silicon avalanche pixel sensors (APiX) is based on the vertical…
A method is presented which allows to obtain the position-dependent electric field and charge density by fits to velocity profiles from edge-TCT data from silicon strip-detectors. The validity and the limitations of the method are…
The capacitance of the charge collection node of a sensor system is an important parameter for the design of the analog front-end electronics. The analog front-end of high-granularity sensors like for example hybrid pixel detectors need to…
Silicon pixel detectors developed to meet LHC requirements were tested in a beam at CERN in the framework of the ATLAS collaboration. The experimental behaviour of irradiated and not-irradiated sensors in a magnetic field is discussed. The…
Long-lived charged particles are predicted by various theories beyond the Standard Model, leading to unique signatures that could reveal new physics. At the LHC, the CMS detector enables searches for these massive particles, identifiable by…