arXiv subjects

Hangil Jang

Publications and source records attributed to Hangil Jang.

3 recordsLinked to original sources

arXiv2026

Development and demonstration of the Korea ALICE Telescope using electron beams at KEK PF-AR

The development of ultra-low-mass, high-precision vertex detectors is a key requirement for future collider experiments and motivates extensive research and development of novel silicon tracking technologies. In this work, we present the development and beam-test demonstration of the Korea ALICE Telescope (KATS), a silicon-tracking telescope designed to support R&D on next-generation cylindrical vertex detectors, such as the proposed ALICE ITS3 upgrade. The telescope consists of six ALPIDE Monolithic Active Pixel Sensors (MAPS) used as reference tracking planes, a bent ALPIDE sensor serving as the device under test, and a scintillating-fiber-based trigger system, all housed in a light-tight modular enclosure. This setup enables precise track reconstruction and detailed performance studies of both planar and curved silicon sensors. Beam tests were carried out using high-energy electron beams at the KEK Photon Factory Advanced Ring (PF-AR). The telescope system operated stably under realistic beam conditions, and its tracking performance was successfully validated. The bent ALPIDE sensor was operated at a bending radius of approximately 18 mm, consistent with ITS3's design goals, without any observable degradation in detection performance. The measured results confirm that the KATS provides a versatile and reliable platform for studies of curved MAPS technologies, alignment precision, and tracking performance. These results provide important experimental validation of key technologies for future low-mass cylindrical silicon vertex detectors and establish KATS as a valuable facility for ongoing and future detector R&D.

physics.ins-det↗

arXiv2025

Exploring an image-based $b$-jet tagging method using convolution neural networks

Jet flavor tagging, the identification of jets originating from $c$-quarks, $b$-quarks, and other quarks (light quarks and gluons), is a crucial task in high-energy heavy-ion physics, as it enables the investigation of flavor-dependent responses within the hot and dense nuclear medium produced in heavy-ion collisions. Recently, several methods based on deep learning techniques, such as deep neural networks and graph neural networks, have been developed. These deep-learning-based methods demonstrate significantly improved performance compared to traditional methods that rely on track impact parameters and secondary vertices. In the tagging algorithms, various properties of jets and constituent charged particles are used as input parameters. We explore a new method based on images surrounding the primary vertex, utilizing charged particles within the jet cone, which can be measured using a silicon tracking system. For this initial experimental study, we assume the ideal performance of the tracking system. To analyze these images, we employed convolutional neural networks. The image-based flavor tagging method shows an 80-90% $b$-jet tagging efficiency for jets in the transverse momentum range from 20 to 100 GeV/$c$. This approach has the potential to significantly improve the accuracy of jet flavor tagging in high-energy nuclear physics experiments.

physics.ins-det↗

arXiv2025

Further Characterisation of Digital Pixel Test Structures Implemented in a 65 nm CMOS Process

The next generation of MAPS for future tracking detectors will have to meet stringent requirements placed on them. One such detector is the ALICE ITS3 that aims to be very light at 0.07% X/X$_{0}$ per layer and have a low power consumption in the active area of 40 mW/cm$^{2}$ by implementing wafer-scale MAPS bent into cylindrical half layers. To address these challenging requirements, the ALICE ITS3 project, in conjunction with the CERN EP R&D on monolithic pixel sensors, proposed the Tower Partners Semiconductor Co. 65 nm CMOS process as the starting point for the sensor. After the initial results confirmed the detection efficiency and radiation hardness, the choice of the technology was solidified by demonstrating the feasibility of operating MAPS in low-power consumption regimes, < 50 mW/cm$^{2}$, while maintaining high-quality performance. This was shown through a detailed characterisation of the Digital Pixel Test Structure (DPTS) prototype exposed to X-rays and ionising beams, and the results are presented in this article. Additionally, the sensor was further investigated through studies of the fake-hit rate, the linearity of the front-end in the range 1.7-28 keV, the performance after ionising irradiation, and the detection efficiency of inclined tracks in the range 0-45$^\circ$.

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