The Compressed Baryonic Matter (CBM) Experiment at FAIR – Physics, Status and Prospects

Agarwal, Kshitij

doi:10.1088/1402-4896/acbca7

Cited by 4 publications

(3 citation statements)

References 88 publications

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“…The Silicon Tracking System (STS) is the core detector for tracking and momentum determination of charged particles in the CBM experiment [1]. It is designed to reconstruct the trajectories of up to 1000 charged particles per event with high efficiency; it is expected to achieve a momentum resolution better than 2% and to reconstruct complex event topologies, such as the weak decays of strange or charmed hadrons and hypernuclei.…”

Section: Introductionmentioning

confidence: 99%

Vertex reconstruction and tracking performance of the STS detector with the mCBM setup at SIS18

Ramirez Zaldivar

2024

Proceedings of the 32nd International Workshop on Vertex Detectors — PoS(VERTEX2023)

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The Compressed Baryonic Matter (CBM) experiment is one of the experimental pillars at the Facility for Antiproton and Ion Research (FAIR). The Silicon Tracking System (STS) is the central detector for track reconstruction and momentum measurement. It is designed to measure heavy ion collisions at interaction rates up to 10 MHz. It comprises approximately 900 double-sided silicon strip sensors with 1024 strips per side, arranged in 8 tracking stations in a magnetic field of 1 T • m. In the context of the FAIR Phase-0 program, the mCBM setup at SIS18/GSI is a smallscale precursor of the full CBM experiment, consisting of pre-series productions of all major CBM detector subsystems aiming to verify CBM's concepts of free-streaming readout electronics, data transport, and online reconstruction. The mini-STS (mSTS) setup consists of 11 sensors arranged in 2 stations and no magnetic field. Heavy ion collisions in the 1 − 2 AGeV/𝑐 range were measured with an average collision rate of 500 kHz. The primary vertex is reconstructed using the two layers of the mSTS detector by tracks reconstructed as straight lines. Hit reconstruction efficiency was estimated using correlations with downstream detectors.

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Section: Introductionmentioning

confidence: 99%

Vertex reconstruction and tracking performance of the STS detector with the mCBM setup at SIS18

Ramirez Zaldivar

2024

Proceedings of the 32nd International Workshop on Vertex Detectors — PoS(VERTEX2023)

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“…CBM is a fixed-target heavy-ion experiment of the future Facility for Antiproton and Ion Research (FAIR) complex in Darmstadt, Germany; it is dedicated to study the strongly interacting matter under extreme conditions [1].…”

Section: Introduction: Silicon Tracking System Of the Cbm Experimentsmentioning

confidence: 99%

From 3D to 5D tracking: SMX ASIC-based double-sided micro-strip detectors for comprehensive space, time, and energy measurements

Teklishyn,

Rodríguez Rodríguez,

Agarwal

et al. 2024

J. Inst.

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We present the recent development of a lightweight detector capable of accurate spatial, timing, and amplitude resolution of charged particles. The technology is based on double-sided double-metal p+ – n – n+ micro-strip silicon sensors, ultra-light long aluminum-polyimide micro-cables for the analogue signal transfer, and a custom-developed SMX read-out ASIC capable of measurement of the time (Δt ≲ 5 ns) and amplitude. Dense detector integration enables a material budget > 0.3 % X 0. A sophisticated powering and grounding scheme keeps the noise under control. In addition to its primary application in Silicon Tracking System of the future CBM experiment in Darmstadt, our detector will be utilized in other research applications.

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“…At these interaction rates, it is not possible to store the data streams entirely, as they are produced with approximately 1 TB of data per second [11]. To reduce the amount of data that has to be stored, a reduction by approximately three orders of magnitude [12] is required, and can be achieved by selecting only collisions (events) of physicists' interest. However, in CBM, there is no simple criteria for event selection, as the search for rare short-lived particles requires a full event reconstruction [13], including the reconstruction of decays and decay chains.…”

Section: Introductionmentioning

confidence: 99%

A Neural-Network-Based Competition between Short-Lived Particle Candidates in the CBM Experiment at FAIR

2023

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Fast and efficient algorithms optimized for high performance computers are crucial for the real-time analysis of data in heavy-ion physics experiments. Furthermore, the application of neural networks and other machine learning techniques has become more popular in physics experiments over the last years. For that reason, a fast neural network package called ANN4FLES is developed in C++, which will be optimized to be used on a high performance computer farm for the future Compressed Baryonic Matter (CBM) experiment at the Facility for Antiproton and Ion Research (FAIR, Darmstadt, Germany). This paper describes the first application of ANN4FLES used in the reconstruction chain of the CBM experiment to replace the existing particle competition between Ks-mesons and Λ-hyperons in the KF Particle Finder by a neural network based approach. The raw classification performance of the neural network reaches over 98% on the testing set. Furthermore, it is shown that the background noise was reduced by the neural network-based competition and therefore improved the quality of the physics analysis.

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The Compressed Baryonic Matter (CBM) Experiment at FAIR – Physics, Status and Prospects

Cited by 4 publications

References 88 publications

Vertex reconstruction and tracking performance of the STS detector with the mCBM setup at SIS18

Vertex reconstruction and tracking performance of the STS detector with the mCBM setup at SIS18

From 3D to 5D tracking: SMX ASIC-based double-sided micro-strip detectors for comprehensive space, time, and energy measurements

A Neural-Network-Based Competition between Short-Lived Particle Candidates in the CBM Experiment at FAIR

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