Effective statistical fringe removal algorithm for high-sensitivity imaging of ultracold atoms

Abstract

High-sensitivity imaging of ultracold atoms is often challenging when interference patterns are imprinted on the imaging light. Such image noises result in low signal-to-noise ratio and limit the capability to extract subtle physical quantities. Here we demonstrate an advanced fringe removal algorithm for absorption imaging of ultracold atoms, which efficiently suppresses unwanted fringe patterns using a small number of sample images without taking additional reference images. The protocol is based on an image decomposition and projection method with an extended image basis. We apply this scheme to raw absorption images of degenerate Fermi gases for the measurement of atomic density fluctuations and temperatures. The quantitative analysis shows that image noises can be efficiently removed with only tens of reference images, which manifests the efficiency of our protocol. Our algorithm would be of particular interest for the quantum emulation experiments in which several physical parameters need to be scanned within a limited time duration.

arXiv comment6 pages, 5 figures, supplementary materials

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• Atom Number Fluctuations in Bose Gases -- Statistical analysis of parameter estimation
• On the fluctuations of the number of atoms in the condensate
• CNN-Based Vortex Detection in Atomic 2D Bose Gases in the Presence of a Phononic Background
• Fast Single-shot Imaging of Individual Ions via Homodyne Detection of Rydberg-Blockade-Induced Absorption
• Heuristic machinery for thermodynamic studies of SU(N) fermions with neural networks