Dark Matter Search Results from 1.54 Tonne·Year Exposure of PandaX-4T

Directory Structure

.
├── open_csv/
│   ├── Run0_DM_candidates.csv   # Run 0 dark matter candidate events
│   └── Run1_DM_candidates.csv   # Run 1 dark matter candidate events
└── script/
    └── plot.py                  # Visualization script

Data Description

CSV Files (`open_csv/`)

Both CSV files contain dark matter candidate events with the following columns:

Column	Description	Units
qS1	Corrected S1 signal	PE
qS2B	Corrected S2 signal (bottom PMT array)	PE
qS2	Corrected S2 signal (top + bottom PMT arrays)	PE
x	Reconstructed X position	mm
y	Reconstructed Y position	mm
z	Reconstructed Z position	mm
t	Event timestamp	UTC
set_label	Dataset identifier	-

Run 0: 1,117 events (data taking period: Nov 2020 – Jun 2021)
Run 1: 1,373 events (data taking period: Nov 2021 – Jun 2022)

Plot Script (`script/plot.py`)

A Python script to reproduce the key analysis plots from the paper. It generates three-panel figures showing:

Lg vs S1 — Discrimination parameter log₁₀(S2ᵦ/S1) vs S1 with nuclear recoil energy contours
Y vs X — XY position distribution of events
Z vs R² — Z position vs squared radial position

Requirements

pip install numpy pandas matplotlib

Usage

# Auto-detect run from data
python script/plot.py open_csv/Run0_DM_candidates.csv

# Specify run explicitly
python script/plot.py open_csv/Run1_DM_candidates.csv --run 1

# Custom output path
python script/plot.py open_csv/Run0_DM_candidates.csv plots/my_plot.png

Output is saved as a high-resolution PNG (300 DPI) in a plots/ directory by default.

Run Parameters

The script uses the following detector parameters for each run:

Parameter	Run 0	Run 1
g1 (S1 gain)	0.0997	0.0907
g2b (S2 bottom gain)	4.12	5.029
Electric field	92.8 V/cm	84.4 V/cm

Citation

If you use this data, please cite the original paper:

@article{PandaX4T:2025,
  title = {Dark Matter Search Results from 1.54 Tonne·Year Exposure of PandaX-4T},
  journal = {Phys. Rev. Lett.},
  volume = {134},
  pages = {011805},
  year = {2025},
  doi = {10.1103/PhysRevLett.134.011805}
}

License

This data is released under the Creative Commons Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0) license.

You are free to:

Share — copy and redistribute the material in any medium or format Under the following terms:
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
No Derivatives — If you remix, transform, or build upon the material, you may not distribute the modified material. This ensures the original data remains unaltered and attributable to the PandaX collaboration.

Full license text: https://creativecommons.org/licenses/by-nd/4.0/

You are here