Supplemental data for characterization of alpha and beta interactions using the HeXe setup [Eur. Phys. J. C 82, 361]

Repository with supplemental data to:
Characterization of alpha and beta interactions in liquid xenon. Jörg, F., Cichon, D., Eurin, G. et al. Eur. Phys. J. C 82, 361 (2022) 10.1140/epjc/s10052-022-10259-3
A pre-print of the article is available on arXiv: 2109.13735

Note: When re-using the data, please make sure to cite the article (and not only the dataset)

The files contain the measured data points (as well as their statistical and systematic uncertainties) as shown in the publication.
All datasets are stored in the .csv format.

• 20210924_yields_hexe_kr83m.csv
  This file contains the normalized light and charge yields as a function of the applied field from the measurement with the ^83mKr source. The data is shown in Figure 16 (dots) of the publication. Furthermore the file contains the LY ratio between the two Isomeric transitions of the ^83mKr source, shown in Figure 17 of the article.
• 20210924_yields_hexe_rn222.csv
  This file contains the normalized light and charge yields as a function of the applied field from the measurement with the ²²²Rn source. The data is shown in Figure 18 (blue-ish points) of the publication
• 20210924_drift_velocity_hexe_rn222.csv
  This file contains the measured electron drift velocity in liquid xenon at a temperature of 174.4 K in dependence of the field. The data was acquired using the  ²²²Rn source. Drift velocity is given in units of mm/µs and the datapoints are shown in Figure 20 (black dots) of the publication 
• 20210924_drift_velocity_hexe_kr83m.csv
  This file contains the measured electron drift velocity in liquid xenon at a temperature of 174.4 K in dependence of the field. The data was acquired using the  ^83mKr source. Drift velocity is given in units of mm/µs and are not displayed in the publications due to visibility reasons.

Minimum working example to plot the drift velocity using the ^83mKr data:

  1 import numpy as np
  2 import matplotlib.pyplot as plt
  3 
  4 # load the data set
  5 data = np.loadtxt("20220427_drift_velocity_hexe_kr83m.csv", delimiter=",")
  6 
  7 # Plot the systematic uncertainty on the drift field
  8 plt.errorbar(data[:,0], data[:,2], xerr=data[:,1], fmt="o", capsize=2, ecolor="darkgray",
  9              alpha=0.7, elinewidth=3, color="black")
 10 
 11 # Plot the actual data points
 12 plt.errorbar(data[:,0], data[:,2], yerr=data[:,3], fmt="o", color="black")
 13 
 14 # Label the axis and define the range
 15 plt.ylabel("Drift Velocity [mm/µs]")
 16 plt.xlabel("Drift Field [kV/cm]")
 17 plt.xscale("log")
 18 plt.xlim(0.006, 2)
 19 plt.ylim(0, 2.4)
 20 plt.show()