arXiv subjects

Evgeny Shulga

Publications and source records attributed to Evgeny Shulga.

4 recordsLinked to original sources

arXiv2026

A Second EIC Detector: Physics Case and Conceptual Design

This document is the closeout report for LDRD 23-050, a type-A LDRD project awarded in FY2022 under the title "A Second EIC Detector: Physics Case and Conceptual Design". The project was motivated by the strong interest within the EIC community in a second general-purpose detector and interaction region, and by the recognition that such a detector is essential to fully exploit the scientific potential of the EIC over its multi-decade lifetime. The key goals of the LDRD were to (i) strengthen the case for a second EIC detector, building on the community Yellow Report; (ii) develop a realistic detector concept complementary to the project detector, ePIC, in terms of physics reach, precision, and control of systematics; and (iii) broaden the overall EIC physics program. Since a possible second detector is expected to be realized with a delay of several years relative to the first detector, the project explicitly aimed at identifying technologies that are not yet sufficiently mature for ePIC but could be deployed on the later timescale of a second detector, thereby providing genuine complementarity and room for innovation. As envisioned in the original proposal, the expected outcome was a document detailing the physics potential and requirements of a second EIC detector, accompanied by a conceptual design and an outline of the remaining R&D needs. This report summarizes progress toward these goals, consolidating the physics studies, detector concepts, and technology assessments developed under this LDRD, and situating them within the broader context of worldwide detector R&D. Despite evolving EIC priorities and the effort devoted to ePIC, the work documented here is intended to provide a foundation and reference for future efforts toward a second detector. We hope this report will serve as a useful guide for colleagues advancing this program in the near- and mid-term future.

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arXiv2025

Realizing the Scientific Program with Polarized Ion Beams at EIC

Polarized ion beams at the Electron Ion Collider are essential to address some of the most important open questions at the twenty-first century frontiers of understanding of the fundamental structure of matter. Here, we summarize the science case and identify polarized $^2$H, $^3$He, $^6$Li and $^7$Li ion beams as critical technology that will enable experiments which address the most important science. Further, we discuss the required ion polarimetry and spin manipulation in EIC. The current EIC accelerator design is presented. We identify a significant R\&D effort involving both national laboratories and universities that is required over about a decade to realize the polarized ion beams and estimate (based on previous experience) that it will require about 20 FTE over 10 years (or a total of about 200 FTE-years) of personnel, including graduate students, postdoctoral researchers, technicians and engineers. Attracting, educating and training a new generation of physicists in experimental spin techniques will be essential for successful realization. AI/ML is seen as having significant potential for both acceleration of R\&D and amplification of discovery in optimal realization of this unique quantum technology on a cutting-edge collider. The R\&D effort is synergistic with research in atomic physics and fusion energy science.

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arXiv2024

Variable Rate Neural Compression for Sparse Detector Data

High-energy large-scale particle colliders generate data at extraordinary rates. Developing real-time high-throughput data compression algorithms to reduce data volume and meet the bandwidth requirement for storage has become increasingly critical. Deep learning is a promising technology that can address this challenging topic. At the newly constructed sPHENIX experiment at the Relativistic Heavy Ion Collider, a Time Projection Chamber (TPC) serves as the main tracking detector, which records three-dimensional particle trajectories in a volume of a gas-filled cylinder. In terms of occupancy, the resulting data flow can be very sparse reaching $10^{-3}$ for proton-proton collisions. Such sparsity presents a challenge to conventional learning-free lossy compression algorithms, such as SZ, ZFP, and MGARD. In contrast, emerging deep learning-based models, particularly those utilizing convolutional neural networks for compression, have outperformed these conventional methods in terms of compression ratios and reconstruction accuracy. However, research on the efficacy of these deep learning models in handling sparse datasets, like those produced in particle colliders, remains limited. Furthermore, most deep learning models do not adapt their processing speeds to data sparsity, which affects efficiency. To address this issue, we propose a novel approach for TPC data compression via key-point identification facilitated by sparse convolution. Our proposed algorithm, BCAE-VS, achieves a $75\%$ improvement in reconstruction accuracy with a $10\%$ increase in compression ratio over the previous state-of-the-art model. Additionally, BCAE-VS manages to achieve these results with a model size over two orders of magnitude smaller. Lastly, we have experimentally verified that as sparsity increases, so does the model's throughput.

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arXiv2020

Measurement of the ion blocking by the passive bi-polar grid

The ion backflow is the main limiting factor for operating time projection chambers at high event rates. A significant effort is invested by many experimental groups to solve this problem. This paper explores a solution based on operating a passive bi-polar wire grid. In the presence of the magnetic field, the grid more effectively attenuates the ion current than the electron current going through it. Transparencies of the grid to electrons and ions are measured for different gas mixtures and magnitudes of the magnetic field. The results suggest that in a sufficiently strong magnetic field, the bi-polar wire grid can be used as an effective and independent device to suppress the ion backflow in time projection chambers.

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