Automated Vector-Scanning Spectroscopy for Large-Scale Characterization of Single Quantum Emitters

Abstract

The inherent spatial randomness and broad spectral heterogeneity of epitaxial quantum dots (QDs) -- one of the most mature classes of solid-state quantum emitters -- remains a major obstacle to their scalable deployment in integrated photonic quantum technologies. Overcoming this challenge requires deterministic fabrication strategies capable of precisely aligning nanophotonic structures with high-quality emitters, which in turn demands efficient and automated single-QD characterization. Despite substantial progress in optical measurement techniques, a platform capable of autonomous, data-efficient, and sufficiently versatile characterization of single quantum dots at the chip scale remains lacking. Here, we introduce an automated cryogenic measurement platform that combines wide-field photoluminescence imaging with vector-stage-scanning confocal spectroscopy to enable high-throughput, chip-scale targeted optical characterization of individual QDs. Using this platform, we automatically acquire photoluminescence data from thousands of GaAs/AlGaAs QDs on a single chip. We demonstrate how this extensive dataset enables identification of high-performance emitters for future deterministic device fabrication, while simultaneously revealing statistical trends across the QD ensemble. By uniting data-efficient targeted measurements with scalable automation, our platform establishes a foundation for large-scale quantum photonic integration and the high throughput characterization framework needed to accelerate materials optimization.