Related papers: Pushing compute and AI onto detector silicon

For large scale applications, hybrid pixel detectors, in which sensor and read-out IC are separate entities, constitute the state of the art in pixel detector technology to date. They have been developed and start to be used as tracking…

We present a novel methodology of augmenting the scattering data measured by small angle neutron scattering via an emerging deep convolutional neural network (CNN) that is widely used in artificial intelligence (AI). Data collection time is…

Future strategic X-ray missions, such as the Advanced X-ray Imaging Satellite (AXIS) and those targeted by the Great Observatories Maturation Program (GOMaP), require fast, low-noise X-ray imaging spectrometers. To achieve the speed and…

Deep learning using convolutional neural networks (CNNs) is quickly becoming the state-of-the-art for challenging computer vision applications. However, deep learning's power consumption and bandwidth requirements currently limit its…

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…

With the decreasing sizes of integrated-circuit components, the semiconductor industry is in growing need of high-throughput strain mapping techniques that offer high precision and spatial resolution, with desired industry goals of…

This is part of a document, which is devoted to the developments of pixel detectors in the context of the International Linear Collider. From the early developments of the MIMOSAs to the proposed DotPix I recall some of the major…

With the rise of AI in recent years and the increase in complexity of the models, the growing demand in computational resources is starting to pose a significant challenge. The need for higher compute power is being met with increasingly…

Optical computing has been recently proposed as a new compute paradigm to meet the demands of future AI/ML workloads in datacenters and supercomputers. However, proposed implementations so far suffer from lack of scalability, large…

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 pixel detectors have been investigated as radiation-hard candidates for the innermost layers of the HL-LHC upgrade of the ATLAS pixel detector. 3D detectors are already in use today in the ATLAS IBL and AFP experiments. These are…

The upgrade for ATLAS detector will undergo different phase towards super-LHC. The first upgrade for the Pixel detector will consist of the construction of a new pixel layer which will be installed during the first shutdown of the LHC…

For the Phase-II Upgrade of the ATLAS detector at CERN, the current ATLAS Inner Detector will be replaced with the ATLAS Inner Tracker. The ATLAS Inner Tracker will be an all-silicon detector, consisting of a pixel tracker and a strip…

Cameras are the defacto sensor. The growing demand for real-time and low-power computer vision, coupled with trends towards high-efficiency heterogeneous systems, has given rise to a wide range of image processing acceleration techniques at…

The rapidly increasing demands for computational throughput, bandwidth, and memory capacity fueled by breakthroughs in machine learning pose substantial challenges for conventional electronic computing platforms. For digital scaling to keep…

The emergence of "big data" offers unprecedented opportunities for not only accelerating scientific advances but also enabling new modes of discovery. Scientific progress in many disciplines is increasingly enabled by our ability to examine…

The development of Hybrid CMOS Detectors (HCDs) for X-Ray telescope focal planes will place them in con- tention with CCDs on future satellite missions due to their faster frame rates, flexible readout scenarios, lower power consumption,…

Classical computing is beginning to encounter fundamental limits of energy efficiency. This presents a challenge that can no longer be solved by strategies such as increasing circuit density or refining standard semiconductor processes. The…

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…

Hand-sized Deoxyribonucleic acid (DNA) sequencing machines are of growing importance in several life sciences fields as their small footprints enable a broader range of use cases than their larger, stationary counterparts. However, as…