Self-Bayesian aberration removal via constraints for ultracold atom microscopy

8Citations
Citations of this article
19Readers
Mendeley users who have this article in their library.

Abstract

High-resolution imaging of ultracold atoms typically requires custom high numerical aperture (NA) optics, as is the case for quantum gas microscopy. These high NA objectives involve many optical elements, each of which contributes to loss and light scattering, making them unsuitable for quantum backaction limited "weak"measurements. We employ a low-cost high NA aspheric lens as an objective for a practical and economical - although aberrated - high-resolution microscope to image Rb87 Bose-Einstein condensates. Here, we present a methodology for digitally eliminating the resulting aberrations that is applicable to a wide range of imaging strategies and requires no additional hardware. We recover nearly the full NA of our objective, thereby demonstrating a simple and powerful digital aberration correction method for achieving optimal microscopy of quantum objects. This reconstruction relies on a high-quality measure of our imaging system's even-order aberrations from density-density correlations measured with differing degrees of defocus. We demonstrate our aberration compensation technique using phase-contrast imaging, a dispersive imaging technique directly applicable to quantum backaction limited measurements. Furthermore, we show that our digital correction technique reduces the contribution of photon shot noise to density-density correlation measurements which would otherwise contaminate the desired quantum projection noise signal in weak measurements.

Cite

CITATION STYLE

APA

Altuntaş, E., & Spielman, I. B. (2021). Self-Bayesian aberration removal via constraints for ultracold atom microscopy. Physical Review Research, 3(4). https://doi.org/10.1103/PhysRevResearch.3.043087

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free