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XENON1T dark matter data analysis: Signal reconstruction, calibration, and event selection

E. Aprile et al. (XENON Collaboration)
Phys. Rev. D 100, 052014 – Published 25 September 2019
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  • INTRODUCTION
  • DETECTOR OPERATION AND STABILITY
  • SIGNAL RECONSTRUCTION AND SIMULATION
  • POSITION RECONSTRUCTION AND RELATED…
  • SIGNAL CORRECTIONS
  • SELECTION CRITERIA AND THEIR ACCEPTANCES
  • OPTIMIZATION OF THE FIDUCIAL VOLUME
  • SIGNAL AND BACKGROUND DISCRIMINATION
  • SUMMARY AND OUTLOOK
  • ACKNOWLEDGMENTS
    • References

    Abstract

    The XENON1T experiment at the Laboratori Nazionali del Gran Sasso is the most sensitive direct detection experiment for dark matter in the form of weakly interacting particles (WIMPs) with masses above 6  GeV/c2 scattering off nuclei. The detector employs a dual-phase time projection chamber with 2.0 metric tons of liquid xenon in the target. A one metric ton×year exposure of science data was collected between October 2016 and February 2018. This article reports on the performance of the detector during this period and describes details of the data analysis that led to the most stringent exclusion limits on various WIMP-nucleon interaction models to date. In particular, signal reconstruction, event selection, and calibration of the detector response to nuclear and electronic recoils in XENON1T are discussed.

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    • Received 12 June 2019

    DOI:https://doi.org/10.1103/PhysRevD.100.052014

    © 2019 American Physical Society

    Physics Subject Headings (PhySH)

    1. Research Areas
    Particle dark matter
    Particles & Fields

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    Issue

    Vol. 100, Iss. 5 — 1 September 2019

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    Images

    • Figure 1
      Figure 1

      Accumulated data live time acquired with the XENON1T detector in dark matter search mode and corrected for data quality conditions (Sec. 6a). The black dashed vertical lines mark the end of SR0 and the start of SR1. The various colored bands represent periods of detector calibration with Rn220 (magenta), Kr83m (red), Am241Be (cyan), and neutron generator (blue) sources and with blue LED light (gray).

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    • Figure 2
      Figure 2

      PMT gains measured by LED calibrations as a function of time for three representative stable PMTs (green, blue, and magenta) and two examples in which the gain decreased due to small vacuum leaks (red and black).

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    • Figure 3
      Figure 3

      S1 signal reconstruction efficiency estimated from waveform simulations, as a function of number of PMT hits. Hits are converted into S1 signal size (top axis) using a double PE emission probability at the photocathode of 21.9% [10]. The data-driven efficiency from Rn220 calibration is overlaid for comparison.

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    • Figure 4
      Figure 4

      S1 (left) and S2 (right) signal size reconstruction bias B and its 1σ width as estimated from simulations. The bands are derived by varying the data-driven model parameters within their uncertainties and hence represent the credible region of the shown values.

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    • Figure 5
      Figure 5

      xobs−yobs distribution of Kr83m events as reconstructed by the fann algorithm integrated over zobs. The distortions at high radii coincide with the 24 PTFE reflector panels (black segments) that are not in contact with the ring-shaped electrodes surrounding the TPC for drift field shaping. Magenta segments indicate the panels that are in contact with the electrodes.

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    • Figure 6
      Figure 6

      Maximum TPC radius reconstructed from signals of surface events in three time intervals and in bins of z. Open (filled) markers show radii before (after) position correction. Horizontal error bars indicate the radial width of the event distribution. Vertical error bars mark the z bin width. The black dashed vertical line indicates the geometrical TPC radius.

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    • Figure 7
      Figure 7

      Absolute radial difference (ΔR) reconstructed between 32.1 and 9.4 keV signals from Kr83m in bins of R2. The corresponding R scale is shown on the upper horizontal axis. The vertical error bars represent the standard deviation of the ΔR distribution, while horizontal error bars indicate the R2 bin width.

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    • Figure 8
      Figure 8

      Radial position resolution σR in bins of S2 signal size for surface events. Vertical uncertainties are derived from the Gaussian fit, while horizontal error bars mark the S2 bin width. The red dashed line indicates the best fit of an empirical function.

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    • Figure 9
      Figure 9

      Electron lifetime evolution during the two science runs measured from Kr83m (black), Rn222 (red), and Po218 (green) decays. Decreases are caused by releases of impurities due to changes in detector operation parameters like the detector’s cooling power and the gas flow in the purification system. The temporal fine structure is modeled based on the α measurements (gray line), while the absolute scale of the electron lifetime is determined from the Kr83m measurement.

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    • Figure 10
      Figure 10

      Spatial dependence of the relative light collection efficiency Lc on z (left) and ϕ (right) for different radial bins (color code). Data points are connected by straight lines to guide the eye.

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    • Figure 11
      Figure 11

      Distribution of S1 signal sizes vs S2pre/Δt as measured in Rn220 calibration data. The threshold in S2pre/Δt above which events are rejected regardless of their own properties is indicated by the red line.

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    • Figure 12
      Figure 12

      Distribution of the measured S2 width parameter r50 normalized to the width r50theory expected from diffusion as a function of S2 signal size for simulated (top) and combined Rn220 and Am241Be calibration data (bottom). Yellow points mark the 0.3% and 99.7% quantiles for simulated data, and red solid lines show the chosen cut definition. The red dashed line marks r50=r50theory.

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    • Figure 13
      Figure 13

      Fraction of lone S1 signals (color scale) between 0 and 70 PE observed by each PMT (circles) in the bottom array during Rn220 calibrations. Numbers in the circles indicate PMT IDs. Magenta stars mark the points where internal calibration sources are injected into the detector below the cathode. White circles represent PMTs that were nonfunctional in SR1.

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    • Figure 14
      Figure 14

      Evolution of the acceptance of S1 and S2 signals from physical interactions by incremental application of the three categories of selection criteria described in the text as a function of uncorrected S1 and S2 signal sizes. The total acceptance is also shown after considering the reconstruction efficiencies introduced in Sec. 3.

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    • Figure 15
      Figure 15

      Spatial distribution of modeled background rates (color scale) from ER (top left), radiogenic neutrons (top right), surface events (bottom left) and total background (bottom right) considering the cS1-cS2b region in which a 50 GeV WIMP signal is expected to have the highest significance compared to the total background. Note that the rate axis is not the same for all panels. Red solid lines mark the result of the FV optimization (1.3t) and red dashed lines the inner core mass (0.65t).

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    • Figure 16
      Figure 16

      Rn220 (upper panel) and neutron generator (lower panel) calibration data in ER/NR discrimination space for events within the inner 1t cylindrical volume (black) and outside the 1t volume but within the 1.3t volume (green). The models extracted from the calibration data for ER (blue) and a 200  GeV/c2 WIMP (red) are shaded and additionally drawn as 10%-50%-90% (dotted-solid-dotted) contour lines. The energy axes for ER (top) and NR (bottom) are drawn as gray contours. More details on background and signal modeling are given in Ref. [10].

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