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First Dark Photon Search Results from the Dandelion Experiment

I. Ourahou, C. Beaufort, M. Bastero-Gil, A. Catalano, J. Macias-Perez, S. Savorgnano, D. Santos, C. Smith, F. Naraghi, J. Bounmy, D. Tourres, F. Vezzu

Abstract

This paper presents the first results from the Dandelion experiment, a directional detection, which searches for 1 meV dark photon dark matter. We use a spherical mirror to convert dark photons into standard millimeter-wavelength photons that can then be detected with an array of 221 Kinetic Inductance Detectors (KIDs) cooled down to 150 mK within the KISS (KIDs Interferometric Spectral Surveyor) camera and operating between 150 and 350 GHz. We used 1480 minutes of data to search for the signal of dark photons in the KID detectors, which is expected to be modulated due to the Earth's rotation. Our main challenge was to deal with a large background from room temperature and stray-light fluctuations. We used a de-correlation analysis to remove these background fluctuations. Templates of the background fluctuations were constructed from a Principal Component Analysis decomposition of detector measurements outside the expected Field of View trajectory of dark photons. We found that the dark photon signal was consistent with zero, giving a new upper limit on the dark photon's kinetic mixing, $χ$, with masses between 0.6 meV and 1.4 meV. These are the first constraints on dark photons as a dark matter candidate using an array of KIDs at millimeter wavelength.

First Dark Photon Search Results from the Dandelion Experiment

Abstract

This paper presents the first results from the Dandelion experiment, a directional detection, which searches for 1 meV dark photon dark matter. We use a spherical mirror to convert dark photons into standard millimeter-wavelength photons that can then be detected with an array of 221 Kinetic Inductance Detectors (KIDs) cooled down to 150 mK within the KISS (KIDs Interferometric Spectral Surveyor) camera and operating between 150 and 350 GHz. We used 1480 minutes of data to search for the signal of dark photons in the KID detectors, which is expected to be modulated due to the Earth's rotation. Our main challenge was to deal with a large background from room temperature and stray-light fluctuations. We used a de-correlation analysis to remove these background fluctuations. Templates of the background fluctuations were constructed from a Principal Component Analysis decomposition of detector measurements outside the expected Field of View trajectory of dark photons. We found that the dark photon signal was consistent with zero, giving a new upper limit on the dark photon's kinetic mixing, , with masses between 0.6 meV and 1.4 meV. These are the first constraints on dark photons as a dark matter candidate using an array of KIDs at millimeter wavelength.
Paper Structure (12 sections, 11 equations, 10 figures)

This paper contains 12 sections, 11 equations, 10 figures.

Table of Contents

  1. Introduction
  2. Experimental Setup
  3. Signal modeling and reconstruction procedure
  4. Expected Dark Photon Signal
  5. Background contribution
  6. Two-region model
  7. Final analysis
  8. Exclusion Curve
  9. Conclusion
  10. Frequency Bandwidth
  11. Rayleigh-Jeans Approximation
  12. Synchronous Modulation Technique

Figures (10)

  • Figure 1: The figure shows a schematic diagram of the experimental setup Beaufort2024Dandelion
  • Figure 2: Spatial and temporal definition of the signal and background regions for the two-position analysis. The left panel shows the predicted 1480-minute run starting on January 11, 2024 temporal modulation of the signal's X and Y coordinates on the detector, as derived from the model in Bozorgnia2011Modulation. The other two panels project these complete daily trajectories onto the array of operational pixels for the first (frontal) and second (tilted) mirror positions. Based on proximity to these paths, pixels are classified into two critical sets: the 'Signal + Background' region (black dots), which is searched for the dark photon signature, and the 'Background-only' region (red dots).
  • Figure 3: Comparison between the change in intensity of the Fresnel diffraction function Beaufort2024Dandelion and the two-dimensional Gaussian fit as a function of radial distance.
  • Figure 4: The left and middle panels show the raw temperature time series for a subset of 'Signal' pixels and the full set of 'Background' pixels, respectively. Both are dominated by large, correlated thermal fluctuations. To model this common-mode noise, we apply Principal Component Analysis (PCA) to the concatenated background data. The right panel displays the first five (out of 10 used) resulting principal components, which represent the dominant, independent modes of temporal variation. These components are used to construct the noise model for subtraction
  • Figure 5: This figure illustrates the modeled temporal evolution of the Gaussian signal component for pixels in both the Signal and Background regions. Right Panel: The normalized signal templates for pixels located within the Signal + Background region. As the Gaussian signal spot moves along its daily trajectory, each pixel is illuminated at a distinct time, creating the unique temporal signature that is the target of our search. Left Panel: The corresponding signal component for a set of pixels in the Background-only region. The amplitude is three orders of magnitude lower, remaining negligible throughout the observation. This quantitatively justifies their use for a clean extraction of common-mode noise.
  • ...and 5 more figures