Related papers: Calorimeter Assisted Tracking Algorithm for SiD

In 2020, Peter Larsen reported flaws in the methods for centrosymmetry parameter computation in the existing molecular dynamics and analysis packages. He proposed an intuitive an mathematically rigorous formulation for centrosymmetry…

Object detection algorithms for Lidar data have seen numerous publications in recent years, reporting good results on dataset benchmarks oriented towards automotive requirements. Nevertheless, many of these are not deployable to embedded…

Occluded pedestrian re-identification (ReID) in base station environments is a critical task in computer vision, particularly for surveillance and security applications. This task faces numerous challenges, as occlusions often obscure key…

3D multi-object tracking in LiDAR point clouds is a key ingredient for self-driving vehicles. Existing methods are predominantly based on the tracking-by-detection pipeline and inevitably require a heuristic matching step for the detection…

We present a top-down approach to calorimeter clustering. An algorithm based on minimal spanning tree theory is described briefly.

Charged particle reconstruction is one the most computationally heavy components of the full event reconstruction of Large Hadron Collider (LHC) experiments. Looking to the future, projections for the High Luminosity LHC (HL-LHC) indicate a…

Letter of intent describing SiD (Silicon Detector) for consideration by the International Linear Collider IDAG panel. This detector concept is founded on the use of silicon detectors for vertexing, tracking, and electromagnetic calorimetry.…

We present results from parallelizing the unpacking and clustering steps of the raw data from the silicon strip modules for reconstruction of charged particle tracks. Throughput is further improved by concurrently processing multiple events…

In order to achieve the challenging requirements on the CLIC vertex detector, a range of technology options have been considered in recent years. One prominent idea is the use of active sensors implemented in a commercial high-voltage CMOS…

In this article we describe the implementation of Artificial Intelligence models in track reconstruction software for the CLAS12 detector at Jefferson Lab. The Artificial Intelligence based approach resulted in improved track reconstruction…

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…

Tracking in high density environments plays an important role in many physics analyses at the LHC. In such environments, it is possible that two nearly collinear particles contribute to the same hits as they travel through the ATLAS pixel…

Skipper Charge-Coupled Devices (Skipper-CCDs) are ultra-low-threshold detectors capable of detecting energy deposits in silicon at the eV scale. Increasingly used in rare-event searches, one of the major challenges in these experiments is…

3D cell tracking in a living organism has a crucial role in live cell image analysis. Cell tracking in C. elegans has two difficulties. First, cell migration in a consecutive frame is large since they move their head during scanning.…

We provide details on the implementation of a machine-learning based particle flow algorithm for CMS. The standard particle flow algorithm reconstructs stable particles based on calorimeter clusters and tracks to provide a global event…

We present an end-to-end reconstruction algorithm to build particle candidates from detector hits in next-generation granular calorimeters similar to that foreseen for the high-luminosity upgrade of the CMS detector. The algorithm exploits…

Timepix3 pixel detectors have demonstrated great potential for tracking applications. With $256\times 256$ pixels, 55 $\mathrm{\mu}$m pitch and improved resolution in time (1.56 ns) and energy (2 keV at 60 keV), they have become powerful…

We present a design for a high-granularity zero-degree calorimeter (ZDC) for the upcoming Electron-Ion Collider (EIC). The design uses SiPM-on-tile technology and features a novel staggered-layer arrangement that improves spatial…

A real-time autoencoder-based anomaly detection system using semi-supervised machine learning has been developed for the online Data Quality Monitoring system of the electromagnetic calorimeter of the CMS detector at the CERN LHC. A novel…

In the future high-luminosity LHC era, high-energy physics experiments face unprecedented computational challenges for event reconstruction. Employing the LHCb vertex locator as a case study we investigate a novel approach for charged…