arXiv subjects

Mingyi Dong

Publications and source records attributed to Mingyi Dong.

14 recordsLinked to original sources

arXiv2026

Integration and characterization of Readout Electronics System for dN/dx Measurement with Drift Chamber Prototype

To explore the feasibility of high-precision particle identification using the cluster counting technique for the drift chamber, a dedicated readout electronics system with low noise, high bandwidth, and high sampling rate is required. This paper presents the design and performance evaluation of a scalable readout prototype developed for this application. The system architecture integrates a custom front-end with a $1.3\ \text{GSps}$ waveform sampling backend, implemented within a modular 120-channel framework. Laboratory characterization of the 40-channel prototype demonstrates a $-3$ dB analog bandwidth of $460\ \text{MHz}$ and an Equivalent Noise Input current of $0.81\ \mu\text{A}_\text{rms}$. These specifications are essential for preserving the fast temporal features of ionization signals. Furthermore, the system achieves an intrinsic timing jitter of $0.87\ \text{ns}$, which satisfies the timing precision requirements for drift distance measurement. Joint experiments with a drift chamber prototype using cosmic rays verified the system's capability to resolve discrete ionization peaks within piled-up waveforms. These results confirm that the readout electronics provide the signal fidelity and temporal resolution necessary for future cluster counting algorithm development.

physics.ins-det↗

arXiv2026

A Telescope System for Charge and Position Measurement of High Energy Nuclei

A high-granularity telescope system with a large sensitive area and low material budget has been developed for high-energy heavy ion beam tests. The telescope consists of nine layers of silicon microstrip detectors (SSDs), whose performance was validated through a heavy ion beam test at the CERN SPS. A hybrid machine learning algorithm is proposed to address the challenges of nuclear charge measurement with SSDs. The system achieves a spatial resolution of $\mathcal{O}(1) \,$\SI{}{\micro\metre} and a charge resolution better than 0.16 charge units for nuclei from $Z = 1$ to $Z = 29$, with a sensitive area of $8 \times 8 \, \mathrm{cm}^2$. To the best of our knowledge, this represents the most precise charge and spatial resolution simultaneously achieved by a silicon telescope to date.

physics.ins-det↗

arXiv2026

Beam Test Characterization of Silicon Microstrip Detector Flight-Model Ladders for the AMS-02 Upgrade

The AMS-02 experiment plans to install a new silicon microstrip tracker layer (Layer-0) on top of the existing detector, increasing the cosmic-ray acceptance by a factor of 3. Layer-0 employs a design in which multiple silicon microstrip detectors (SSDs) are connected in series to form long detector ladders. We present a detailed performance study of the flight-model ladders using a 350~GeV mixed hadron beam at the CERN SPS. The study focuses on the following aspects: (i) the performance of ladders with different numbers of SSDs, for which the intrinsic spatial resolution at normal incidence varies from $9.5~\mu\mathrm{m}$ to $11.4~\mu\mathrm{m}$ for ladders composed of 8 to 12 SSDs; (ii) the response consistency for particles impacting on the \emph{Head} and \emph{Tail} regions of the ladder; and (iii) the dependence of the detector performance on the particle incidence angle.

physics.ins-det↗

arXiv2025

Squeezing Edge Performance: A Sensitivity-Aware Container Management for Heterogeneous Tasks

Edge computing enables latency-critical applications to process data close to end devices, yet task heterogeneity and limited resources pose significant challenges to efficient orchestration. This paper presents a measurement-driven, container-based resource management framework for intra-node optimization on a single edge server hosting multiple heterogeneous applications. Extensive profiling experiments are conducted to derive a nonlinear fitting model that characterizes the relationship among CPU/memory allocations and processing latency across diverse workloads, enabling reliable estimation of performance under varying configurations and providing quantitative support for subsequent optimization. Using this model and a queueing-based delay formulation, we formulate a mixed-integer nonlinear programming (MINLP) problem to jointly minimize system latency and power consumption, which is shown to be NP-hard. The problem is decomposed into tractable convex subproblems and solved through a two-stage container-based resource management scheme (CRMS) combining convex optimization and greedy refinement. The proposed scheme achieves polynomial-time complexity and supports quasi-dynamic execution under global resource constraints. Simulation results demonstrate that CRMS reduces latency by over 14\% and improves energy efficiency compared with heuristic and search-based baselines, offering a practical and scalable solution for heterogeneous edge environments with dynamic workload characteristics.

cs.DC↗

arXiv2025

dN/dx Reconstruction with Deep Learning for High-Granularity TPCs

Particle identification (PID) is essential for future particle physics experiments such as the Circular Electron-Positron Collider and the Future Circular Collider. A high-granularity Time Projection Chamber (TPC) not only provides precise tracking but also enables dN/dx measurements for PID. The dN/dx method estimates the number of primary ionization electrons, offering significant improvements in PID performance. However, accurate reconstruction remains a major challenge for this approach. In this paper, we introduce a deep learning model, the Graph Point Transformer (GraphPT), for dN/dx reconstruction. In our approach, TPC data are represented as point clouds. The network backbone adopts a U-Net architecture built upon graph neural networks, incorporating an attention mechanism for node aggregation specifically optimized for point cloud processing. The proposed GraphPT model surpasses the traditional truncated mean method in PID performance. In particular, the $K/\pi$ separation power improves by approximately 10% to 20% in the momentum interval from 5 to 20 GeV/c.

hep-ex↗

arXiv2025

Beam test result and digitization of TaichuPix-3: A Monolithic Active Pixel Sensors for CEPC vertex detector

The Circular Electron-Positron Collider (CEPC), as the next-generation electron-positron collider, is tasked with advancing not only Higgs physics but also the discovery of new physics. Achieving these goals requires high-precision measurements of particles. Taichu seires, Monolithic Active Pixel Sensor (MAPS), a key component of the vertex detector for CEPC was designed to meet the CEPC's requirements. For the geometry of vertex detector is long barrel with no endcap, and current silicon lacks a complete digitization model, precise estimation of cluster size particularly causing by particle with large incident angle is needed. Testbeam results were conducted at the Beijing Synchrotron Radiation Facility (BSRF) to evaluate cluster size dependence on different incident angles and threshold settings. Experimental results confirmed that cluster size increases with incident angle. Simulations using the Allpix$^2$ framework replicated experimental trends at small angles but exhibited discrepancies at large angles, suggesting limitations in linear electric field assumptions and sensor thickness approximations. The results from both testbeam and simulations have provided insights into the performance of the TaichuPix chip at large incident angles, offering a crucial foundation for the establishment of a digital model and addressing the estimation of cluster size in the forward region of the long barrel. Furthermore, it offers valuable references for future iterations of TaichuPix, the development of digital models, and the simulation and estimation of the vertex detector's performance.

physics.ins-det↗

arXiv2024

Beam test of a baseline vertex detector prototype for CEPC

The Circular Electron Positron Collider (CEPC) has been proposed to enable more thorough and precise measurements of the properties of Higgs, W, and Z bosons, as well as to search for new physics. In response to the stringent performance requirements of the vertex detector for the CEPC, a baseline vertex detector prototype was tested and characterized for the first time using a 6 GeV electron beam at DESY II Test Beam Line 21. The baseline vertex detector prototype is designed with a cylindrical barrel structure that contains six double-sided detector modules (ladders). Each side of the ladder includes TaichuPix-3 sensors based on Monolithic Active Pixel Sensor (MAPS) technology, a flexible printed circuit, and a carbon fiber support structure. Additionally, the readout electronics and the Data Acquisition system were also examined during this beam test. The performance of the prototype was evaluated using an electron beam that passed through six ladders in a perpendicular direction. The offline data analysis indicates a spatial resolution of about 5 um, with detection efficiency exceeding 99 % and an impact parameter resolution of about 5.1 um. These promising results from this baseline vertex detector prototype mark a significant step toward realizing the optimal vertex detector for the CEPC.

physics.ins-det↗

arXiv2024

Cluster Counting Algorithm for the CEPC Drift Chamber using LSTM and DGCNN

The particle identification (PID) of hadrons plays a crucial role in particle physics experiments, especially in flavor physics and jet tagging. The cluster-counting method, which measures the number of primary ionizations in gaseous detectors, is a promising breakthrough in PID. However, developing an effective reconstruction algorithm for cluster counting remains challenging. To address this challenge, we propose a cluster-counting algorithm based on long short-term memory and dynamic graph convolutional neural networks for the CEPC drift chamber. Experiments on Monte Carlo simulated samples demonstrate that our machine-learning-based algorithm surpasses traditional methods. It improves the $K/\pi$ separation of PID by 10\%, meeting the PID requirements of CEPC.

hep-ex↗

arXiv2024

Peak finding algorithm for cluster counting with domain adaptation

Cluster counting in drift chamber is the most promising breakthrough in particle identification (PID) technique in particle physics experiment. Reconstruction algorithm is one of the key challenges in cluster counting. In this paper, a semi-supervised domain adaptation (DA) algorithm is developed and applied on the peak finding problem in cluster counting. The algorithm uses optimal transport (OT), which provides geometric metric between distributions, to align the samples between the source (simulation) and target (data) samples, and performs semi-supervised learning with the samples in target domain that are partially labeled with the continuous wavelet transform (CWT) algorithm. The model is validated by the pseudo data with labels, which achieves performance close to the fully supervised model. When applying the algorithm on real experimental data, taken at CERN with a 180 GeV/c muon beam, it shows better classification power than the traditional derivative-based algorithm, and the performance is stable for experimental data samples across varying track lengths.

physics.ins-det↗

arXiv2024

Performance study of the JadePix-3 telescope from a beam test

We present the results of a beam test conducted on a telescope using the JadePix-3 pixel sensor, developed with TowerJazz 180 nm CMOS imaging technology. The telescope is composed of five planes, each equipped with a JadePix-3 sensor with pitches of 26 um x 16 um and 23.11 um x 16 um. In addition, it features an FPGA-based synchronous readout system. The telescope underwent testing using an electron beam with energy ranging from 4 to 6 GeV. At an electron energy of 5.4 GeV, the telescope demonstrated superior spatial resolutions of 2.6 and 2.3 um in two dimensions. By designating the central plane as the device under test, we evaluated the JadePix-3 sensor's spatial resolutions as 5.2 and 4.6 um in two dimensions, achieving a detection efficiency of over 99%.

hep-ex↗

arXiv2023

Beam test of a 180 nm CMOS Pixel Sensor for the CEPC vertex detector

The proposed Circular Electron Positron Collider (CEPC) imposes new challenges for the vertex detector in terms of pixel size and material budget. A Monolithic Active Pixel Sensor (MAPS) prototype called TaichuPix, based on a column drain readout architecture, has been developed to address the need for high spatial resolution. In order to evaluate the performance of the TaichuPix-3 chips, a beam test was carried out at DESY II TB21 in December 2022. Meanwhile, the Data Acquisition (DAQ) for a muti-plane configuration was tested during the beam test. This work presents the characterization of the TaichuPix-3 chips with two different processes, including cluster size, spatial resolution, and detection efficiency. The analysis results indicate the spatial resolution better than 5 $\mu m$ and the detection efficiency exceeds 99.5 % for both TaichuPix-3 chips with the two different processes.

physics.ins-det↗

arXiv2023

Simulation study of BESIII with stitched CMOS pixel detector using ACTS

Reconstruction of tracks of charged particles with high precision is very crucial for HEP experiments to achieve their physics goals. As the tracking detector of BESIII experiment, the BESIII drift chamber has suffered from aging effects resulting in degraded tracking performance after operation for about 15 years. To preserve and enhance the tracking performance of BESIII, one of the proposals is to add one layer of thin CMOS pixel sensor in cylindrical shape based on the state-of-the-art stitching technology, between the beam pipe and the drift chamber. The improvement of tracking performance of BESIII with such an additional pixel detector compared to that with only the existing drift chamber is studied using the modern common tracking software ACTS, which provides a set of detector-agnostic and highly performant tracking algorithms that have demonstrated promising performance for a few high energy physics and nuclear physics experiments.

physics.ins-det↗

arXiv2022

Simulation study of particle identification using cluster counting technique for the BESIII drift chamber

The particle identification of charged hadrons, especially for the separation of $K$ and $\pi$, is crucial for the flavour physics study. Ionization measurement with the cluster counting technique, which has much less fluctuation than traditional $dE/dx$ measurement, is expected to provide better particle identification for the BESIII experiment. Simulation studies, including a Garfield++ based waveform analysis and a performance study of K/\pi identification in the BESIII, offline software system have been performed. The results show that $K/\pi$ separation power and PID efficiency would be improved significantly in the momentum range above 1.2 GeV/c using cluster counting technique even with conservative resolution assumption.

hep-ex↗

arXiv2015

Study of the Tracking Method and Expected Performance of the Silicon Pixel Inner Tracker Applied in BESIII

The inner drift chamber of the BESIII is encountering serious aging problem after five year's running. For the first layer, the decrease in gas gain is about 26% from 2009 to 2013. The upgrade of the inner tracking detector has become an urgent problem for the BESIII experiment. An inner tracker using CMOS pixel sensors is an important candidate because of its great advantages on spatial resolution and radiation hardness. In order to carry out a Monte Carlo study on the expected performance, a Geant4-based full simulation for the silicon pixel detector has been implemented. The tracking method combining the silicon pixel inner tracker and outer drift chamber has been studied and a preliminary reconstruction software was developed. The Monte Carlo study shows that the performances including momentum resolution, vertex resolution and the tracking efficiency are significantly improved due to the good spatial resolution and moderate material budget of the silicon pixel detector.

physics.ins-det↗