Skip to Main content Skip to Navigation

Imaging the collective excitations of an ultracold gas using statistical correlations

Romain Dubessy 1 Camilla de Rossi 1 Thomas Badr 1 Laurent Longchambon 1 Hélène Perrin 1
LPL - Laboratoire de Physique des Lasers
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.
Complete list of metadatas
Contributor : Romain Dubessy <>
Submitted on : Tuesday, October 7, 2014 - 10:24:27 AM
Last modification on : Tuesday, February 11, 2020 - 2:07:45 PM
Document(s) archivé(s) le : Thursday, January 8, 2015 - 10:36:05 AM


Files produced by the author(s)


  • HAL Id : hal-01071947, version 1
  • ARXIV : 1410.1675


Romain Dubessy, Camilla de Rossi, Thomas Badr, Laurent Longchambon, Hélène Perrin. Imaging the collective excitations of an ultracold gas using statistical correlations. 2014. ⟨hal-01071947v1⟩



Record views


Files downloads