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PhoQuPy: A Python framework for Automation of Quantum Optics experiments

Srivatsa Murali, Anshuman Kumar

TL;DR

PhoQuPy tackles the automation bottleneck in optical characterization of quantum emitters by integrating Python-based control over diverse hardware for confocal PL mapping, $g^{(2)}$ measurements, and life-time analysis in cryogenic environments. The framework coordinates motion, spectroscopy, and single-photon detection, featuring a double-acquisition cosmic-ray suppression method and a modular architecture that supports both room-temperature and cryogenic workflows, including galvo-based fast scanning. It demonstrates spatially resolved PL maps, temperature-dependent spectra, and hyperspectral imaging via a common-path interferometer, with a path toward unified GUIs, database integration, and ML-assisted emitter localization. The approach promises higher reproducibility and throughput for benchmarking single-photon emitters in quantum materials.

Abstract

We present the automation of a confocal photoluminescence (PL) scanning system for the identification and characterization of single-photon emitters (SPEs) in quantum materials. The setup excites the sample with a laser and acquires a spectrum at each spatial coordinate in a raster scan pattern. A double-acquisition method is used to remove cosmic ray artifacts by comparing subsequent measurements at the same spatial coordinate. Once identified, the emitter is further characterized via a HBT setup, thereby measuring lifetime as well as second-order autocorrelation g(2) measurements to confirm singlephoton emission. The system integrates Python-based hardware control for motorized stages, spectrometer acquisition, and post-processing, with a migration to a galvo-mirror scanning approach for using it along with a cryostat for low temperature measurements. Our results demonstrate spatially resolved PL maps and temperature-dependent spectra, highlighting the capability of the setup to efficiently benchmark SPE performance. We further went on to perform automation of other experiments such as a Non-Linear Interferometry setup for Quantum Imaging with Undetected Light and a Fourier Transform Imaging Spectroscopy using a common path birefringence Interferometer to obtain hyperspectral images of our samples.

PhoQuPy: A Python framework for Automation of Quantum Optics experiments

TL;DR

PhoQuPy tackles the automation bottleneck in optical characterization of quantum emitters by integrating Python-based control over diverse hardware for confocal PL mapping, measurements, and life-time analysis in cryogenic environments. The framework coordinates motion, spectroscopy, and single-photon detection, featuring a double-acquisition cosmic-ray suppression method and a modular architecture that supports both room-temperature and cryogenic workflows, including galvo-based fast scanning. It demonstrates spatially resolved PL maps, temperature-dependent spectra, and hyperspectral imaging via a common-path interferometer, with a path toward unified GUIs, database integration, and ML-assisted emitter localization. The approach promises higher reproducibility and throughput for benchmarking single-photon emitters in quantum materials.

Abstract

We present the automation of a confocal photoluminescence (PL) scanning system for the identification and characterization of single-photon emitters (SPEs) in quantum materials. The setup excites the sample with a laser and acquires a spectrum at each spatial coordinate in a raster scan pattern. A double-acquisition method is used to remove cosmic ray artifacts by comparing subsequent measurements at the same spatial coordinate. Once identified, the emitter is further characterized via a HBT setup, thereby measuring lifetime as well as second-order autocorrelation g(2) measurements to confirm singlephoton emission. The system integrates Python-based hardware control for motorized stages, spectrometer acquisition, and post-processing, with a migration to a galvo-mirror scanning approach for using it along with a cryostat for low temperature measurements. Our results demonstrate spatially resolved PL maps and temperature-dependent spectra, highlighting the capability of the setup to efficiently benchmark SPE performance. We further went on to perform automation of other experiments such as a Non-Linear Interferometry setup for Quantum Imaging with Undetected Light and a Fourier Transform Imaging Spectroscopy using a common path birefringence Interferometer to obtain hyperspectral images of our samples.
Paper Structure (12 sections, 2 equations, 9 figures)

This paper contains 12 sections, 2 equations, 9 figures.

Table of Contents

  1. Introduction
  2. System Architecture Overview
  3. Joystick Control and Image Stitching Using Zaber Stage
  4. Confocal Photoluminescence (PL) Mapping Automation
  5. $g^{(2)}$ and Lifetime Measurement via snAPI
  6. Galvo Mirror Implementation for Cryostat PL Mapping
  7. Experiments with Common-Path Birefringent Interferometer
  8. Discussion and Challenges
  9. Future Work
  10. Conclusion
  11. Acknowledgment
  12. Code Availability

Figures (9)

  • Figure 1: System architecture overview. A modular Python layer abstracts all hardware and coordinates experiment workflows.KrammPythonAutomation
  • Figure 2: 20×20 stitched image covering approximately $4\,\mathrm{cm}^{2}$
  • Figure 3: Confocal PL map interface (CdSe quantum dot).
  • Figure 4: Surface plot of PL intensity map for CdSe Quantum Dot
  • Figure 5: Fiber alignment scan showing coupling efficiency distribution.
  • ...and 4 more figures