Spectroscopy of VUV luminescence in dual-phase xenon detectors

Résumé fourni par la source

Note: Please ensure that the article is properly cited when reusing the data, in addition to acknowledging the dataset itself. This repository contains data derived from spectroscopic measurements of xenon luminescence conducted within a dual-phase (liquid-gas) time projection chamber. Thorium-228 α decays excited the liquid, resulting in the formation of singlet and triplet excimers that emit vacuum ultraviolet (VUV) scintillation, commonly termed the S1 signal. Ionisation electrons were drifted to the liquid surface and extracted into the vapour, where they produced VUV electroluminescence known as the S2 signal. The file spectra.json provides the wavelength spectra for these two signal components. Gaussian parameterisations of these data are included in the publication, while more complex spline parameterisations are available in splines.json. The file load_data.ipynb demonstrates how to load and visualise the data. Data in spectra.json The file spectra.json contains a python dictionary of all spectra presented in the publication. It includes: the S1 and S2 spectra for liquid and vapour in equilibium, combining all tested pressures (1.3, 1.7, and 2.2 bar); the S1 and S2 spectra for room-temperature gas; and the S1 spectra where a cutoff has been applied to predominantly isolate triplet emission. Each spectrum contains three lists: wavelength The centre of each wavelength bin. photons/X.XXnm The number of detected photons per X.XX nanometer-wide bin, after having applyied efficiency corrections. statistical uncertainty The statistical uncertainty on photons/X.XXnm. Data in splines.json The file splines.json contains a dictionary of spline parameterisations for the S1 spectrum from liquid, the S2 spectrum from vapour in equilibium with the liquid, and the S1 triplet-enhanced spectrum from liquid. Each spline is characterised by: knots A list of the spline knots. coefficients A list of the spline coefficients. normalise to 1 A multiplicative factor that normalises the integral of the spline to 1. normalise to spectrum A multiplicative factor that normalises the spline to photons/X.XXnm. boundaries The lower and upper boundaries of the region where the spline provides reliable results, defined as the region where the spline exceeds one standard deviation above the flat background rate. Loading/visualising the data with load_data.ipynb The file load_data.ipynb is a Python Jupyter Notebook that plots the spectral data stored in spectra.json. It also includes a function to generate a spline based on the parameters specified in splines.json. To run this notebook successfully, please ensure that jupyter, json, numpy, and matplotlib are installed in your Python environment. You can launch the notebook by executing "jupyter lab" within your environment and then opening the file through the file browser.

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