# Data Analysis Framework for Silicon Strip Detecor in CSHINE-III

**Repository Path**: DB-weixiaobao/ana-framework

## Basic Information

- **Project Name**: Data Analysis Framework for Silicon Strip Detecor in CSHINE-III
- **Description**: Data Analysis Framework for Silicon Strip Detector in Compact Spectrometer for Heavy-IoN Experiments (CSHINE)
- **Primary Language**: C++
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2023-09-05
- **Last Updated**: 2025-04-24

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Data Analysis Framework for Silicon Strip Detecor in CSHINE-III

#### 介绍
Data Analysis Framework for Silicon Strip Detector in Compact Spectrometer for Heavy-IoN Experiments (CSHINE)

# CSHINE-SSDTAna 

#### Description

The Compact Spectrometer for Heavy IoN Experiments (CSHINE) system has been constructed to explore the equation of state of nuclear matter (nEOS) near and below the saturation density at the Fermi energies regime, which has been installed at the final focal plane of the Radioactive Ion Beam Line at Lanzhou (RIBLL-I). As the core detector system of the CSHINE spectrometer, the silicon strip telescope necessitates an efficient data processing architecture. To meet this requirement, a comprehensive ROOT-based framework specifically developed for the CSHINE SSDTs, integrating advanced detector calibration and track reconstruction methodologies. The silicon strip detectors are precisely calibrated through systematic pulse analysis and radioactive $\alpha$-source measurements, while the CsI(Tl) scintillation crystals are calibrated utilizing the $\Delta E_{2}$-$E$ relationship following accurate particle identification (PID). The track reconstruction algorithm that has been implemented integrates geometric and energy constraints. This integration enables the algorithm to effectively address charge sharing phenomena and multi-hit ambiguities.

#### Contribution

1.F.H. Guan provided the source code for the data processing framework for CSHINE-II SSDTs, which is available on GitHub (https://github.com/gfh16/Fission2019-Unified-Analysis-Framework/).

2.The data processing methods were improved by Y.J. Wang, X.B. Wei, C.W. Ma, and Z.G. Xiao.