Speaker
Description
Next-generation e+e- colliders, such as the Circular Electron Positron Collider (CEPC) and the Future Circular Collider (FCC-ee), demand unprecedented precision in tracking and particle identification (PID) to fully exploit their high-luminosity environments. Ultra-light drift chambers operating with cluster counting (dN/dx) techniques represent a highly promising solution to meet these stringent requirements while minimizing the material budget.
In this work, we present recent progress in performance studies and R&D for a drift chamber designed for the CEPC [1]. The detector has a total length of 5.8 m and spans radii from 0.6 m to 1.8 m. It is filled with a 90% helium and 10% isobutane gas mixture, which facilitates dN/dx measurements owing to its low cluster density, low drift velocity, small average cluster size, and reduced single-electron diffusion. Full simulations based on Garfield++, combined with data-driven digitization, have been performed. Moreover, innovative deep-learning-based dN/dx reconstruction algorithms have been developed for both simulated and experimental data [2][3]. PID performance, evaluated using the full simulation, shows promising results for hadrons with momenta up to tens of GeV/c.
To experimentally validate the dN/dx method, a small multi-cell prototype drift chamber with a total length of 53 cm has been constructed. A beam test was conducted at the CERN T9 beamline, which provides low-momentum particles, using a high-sampling-rate, high-bandwidth pre-amplifier and a dedicated DAQ system. The multi-cell configuration enables straightforward tracking, allowing not only effective background suppression but also precise determination of the track length for dN/dx measurements. Preliminary analysis of the beam test data will be presented, demonstrating the feasibility of the dN/dx technique.
References:
[1] CEPC Study Group, CEPC Technical Design Report – Reference Detector, arXiv: 2510.05260.
[2] Guang Zhao et. al., Peak finding algorithm for cluster counting with domain adaptation, Comp. Phys. Comm. 300 (2024) 109208.
[3] Zhefei Tian, Guang Zhao et. al., Cluster counting algorithm for the CEPC drift chamber using LSTM and DGCNN, Nucl. Sci. and Tech. (2025) 36:113.
