Quantum Sensing with HeRALD: Analyzing Vibrational Parasitic Power Coupling in Transition Edge Sensors for Direct Detection of Dark Matter
POSTER
Abstract
Astronomical observations have consistently suggested that dark matter constitutes a substantial portion of our universe. Despite this strong evidence, detecting dark matter directly remains a formidable challenge. This difficulty arises primarily from the very weak interactions of dark matter with ordinary matter. Consequently, the quest for direct detection continues to push the boundaries of current experimental techniques.
The Helium Roton Apparatus for Light Dark Matter (HeRALD) experiment is part of the TESSERACT Collaboration ( Transition Edge Sensors with Sub-EV Resolution and Cryogenic Targets). The HeRALD experiment employs superfluid helium-4 as the target material with transition edge sensors (TES) for readout.
I will describe recent efforts to calibrate the HeRALD testbed at Lawrence Berkeley National Laboratory using photons from a calcium fluoride scintillator. This study aims to analyze different sources of noise and vibrational parasitic power coupling in our transition edge sensor channels. Through this, the optimal bandwidth for HeRALD signals is assessed, which is crucial to design the necessary filters and reduce noise for future experiments.
The Helium Roton Apparatus for Light Dark Matter (HeRALD) experiment is part of the TESSERACT Collaboration ( Transition Edge Sensors with Sub-EV Resolution and Cryogenic Targets). The HeRALD experiment employs superfluid helium-4 as the target material with transition edge sensors (TES) for readout.
I will describe recent efforts to calibrate the HeRALD testbed at Lawrence Berkeley National Laboratory using photons from a calcium fluoride scintillator. This study aims to analyze different sources of noise and vibrational parasitic power coupling in our transition edge sensor channels. Through this, the optimal bandwidth for HeRALD signals is assessed, which is crucial to design the necessary filters and reduce noise for future experiments.
Presenters
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Bahareh Adami Ardestani
Sonoma State University
Authors
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Bahareh Adami Ardestani
Sonoma State University
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Vetri Velan
Lawrence Berkeley National Laboratory
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Xinran Li
Lawrence Berkeley National Laboratory
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Junsong Lin
University of California, Berkeley
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William Joseph Matava
University of California at Berkeley
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Michael Williams
University of Michigan
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Yue Wang
University of California, Berkeley
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Peter Sorensen
Lawrence Berkeley National Laboratory