Extraction and identification of noise patterns for ultracold atoms in an optical lattice
arXiv:1807.04532 · doi:10.1364/OE.27.012710
Abstract
To extract useful information about quantum effects in cold atom experiments, one central task is to identify the intrinsic quantum fluctuation from extrinsic system noises of various kinds. As a data processing method, principal component analysis can decompose fluctuations in experimental data into eigen modes, and give a chance to separate noises originated from different physical sources. In this paper, we demonstrate for Bose-Einstein condensates in one-dimensional optical lattices that the principal component analysis can be applied to time-of-flight images to successfully separate and identify noises from different origins of leading contribution, and can help to reduce or even eliminate noises via corresponding data processing procedures. The attribution of noise modes to their physical origins is also confirmed by numerical analysis within a mean-field theory.
arXiv comment7 pages, 7 figures
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- Implementation of a double-path multimode interferometer using a spinor Bose-Einstein condensate
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- Beam Profiling with Noise Reduction From Computer Vision and Principal Component Analysis for the MAGIS-100 Experiment