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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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