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Trapped Ion Quantum Computing
Imaging the collective excitations of an ultracold gas using statistical correlations
arXiv
Authors: Romain Dubessy, Camilla De Rossi, Thomas Badr, Laurent Longchambon, Hélène Perrin
Year
2014
Paper ID
47112
Status
Preprint
Abstract Read
~2 min
Abstract Words
102
Citations
N/A
Abstract
Advanced data analysis techniques have proved to be crucial for extracting information from noisy images. Here we show that principal component analysis can be successfully applied to ultracold gases to unveil their collective excitations. By analyzing the correlations in a series of images we are able to identify the collective modes which are excited, determine their population, image their eigenfunction, and measure their frequency. Our method allows to discriminate the relevant modes from other noise components and is robust with respect to the data sampling procedure. It can be extended to other dynamical systems including cavity polariton quantum gases or trapped ions.
Why This Paper Matters
- This paper contributes to the Trapped-Ion Quantum Computing research area in the Quantum Articles archive.
- It adds a 2014 reference point for readers tracking recent quantum research.
- Advanced data analysis techniques have proved to be crucial for extracting information from noisy images.
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