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

William Eshbaugh; Ashish Chanana; Edgar Perez; Junyeob Song; Craig R. Copeland; Sulaiman Al Ghadani; Daniel McBride; Prasiddha Siwakoti; Maria Carolina Volpato; Armando Rastelli; Saimon Filipe Covre da Silva; Ignacio Segovia-Dominguez; Sadhvikas Addamane; Kartik Srinivasan; Edward B. Flagg; Marcelo Davanco

arXiv · 2606.28624

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

William Eshbaugh·Ashish Chanana·Edgar Perez·Junyeob Song·Craig R. Copeland·Sulaiman Al Ghadani·Daniel McBride·Prasiddha Siwakoti·Maria Carolina Volpato·Armando Rastelli·Saimon Filipe Covre da Silva·Ignacio Segovia-Dominguez·Sadhvikas Addamane·Kartik Srinivasan·Edward B. Flagg·Marcelo Davanco

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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.

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William Eshbaugh, Ashish Chanana, Edgar Perez, Junyeob Song, Craig R. Copeland, Sulaiman Al Ghadani, Daniel McBride, Prasiddha Siwakoti, Maria Carolina Volpato, Armando Rastelli, Saimon Filipe Covre da Silva, Ignacio Segovia-Dominguez, Sadhvikas Addamane, Kartik Srinivasan, Edward B. Flagg, Marcelo Davanco. 2026-06-26. Automated Vector-Scanning Spectroscopy for Large-Scale Characterization of Single Quantum Emitters. https://arxiv.org/abs/2606.28624

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