Dark counts in optical superconducting transition-edge sensors for rare-event searches

TL;DR

This paper characterizes background events in optical superconducting transition-edge sensors, introduces automated classification methods, and reports a record-low dark-count rate crucial for dark matter detection.

Contribution

It provides the first experimental verification and simulation of high-energy event sources and isolates photonlike dark counts in TESs for dark matter searches.

Findings

Identified three types of background events in TESs.

Developed automated event classification methods.

Achieved a record-low photonlike dark-count rate of 3.6e-4 Hz.

Abstract

Superconducting transition-edge sensors (TESs) are a type of quantum sensor known for its high single-photon detection efficiency and low background. This makes them ideal for particle physics experiments searching for rare events. In this work, we present a comprehensive characterization of the background in optical TESs, distinguishing three types of events: electrical-noise, high-energy, and photonlike events. We introduce computational methods to automate the classification of events. For the first time, we experimentally verify and simulate the source of the high-energy events. We also isolate the photonlike events, the expected signal in dielectric haloscopes searching for dark matter dark photons, and achieve a record-low photonlike dark-count rate of $3.6 \times 10^{-4}$ Hz in the 0.8-3.2 eV energy range.