Remote optimization of an ultracold atoms experiment by experts and citizen scientists

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  • E11231.full

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  • Robert Heck
  • Oana Vuculescu
  • Jens Jakob Sorensen
  • ,
  • Jonathan Zoller, Ulm Univ, Ulm University, Ctr Integrated Quantum Sci & Technol
  • ,
  • Morten G. Andreasen
  • ,
  • Mark G. Bason, Univ Sussex, University of Sussex, Dept Phys & Astron
  • ,
  • Poul Ejlertsen
  • ,
  • Otto Eliasson
  • ,
  • Pinja Haikka
  • ,
  • Jens S. Laustsen
  • ,
  • Laerke L. Nielsen
  • ,
  • Andrew Mao
  • ,
  • Romain Mueller
  • ,
  • Mario Napolitano
  • ,
  • Mads K. Pedersen
  • Aske R. Thorsen
  • ,
  • Carsten Bergenholtz
  • Tommaso Calarco, Forschungszentrum Julich, Helmholtz Association, Research Center Julich, Peter Grunberg Inst, Quantum Control
  • ,
  • Simone Montangero, Univ Padua, University of Padua, Dipartimento Fis & Astron Galileo Galilei
  • ,
  • Jacob F. Sherson

We introduce a remote interface to control and optimize the experimental production of Bose-Einstein condensates (BECs) and find improved solutions using two distinct implementations. First, a team of theoreticians used a remote version of their dressed chopped random basis optimization algorithm (RedCRAB), and second, a gamified interface allowed 600 citizen scientists from around the world to participate in real-time optimization. Quantitative studies of player search behavior demonstrated that they collectively engage in a combination of local and global searches. This form of multiagent adaptive search prevents premature convergence by the explorative behavior of low-performing players while high-performing players locally refine their solutions. In addition, many successful citizen science games have relied on a problem representation that directly engaged the visual or experiential intuition of the players. Here we demonstrate that citizen scientists can also be successful in an entirely abstract problem visualization. This is encouraging because a much wider range of challenges could potentially be opened to gamification in the future.

Original languageEnglish
JournalProceedings of the National Academy of Sciences of the United States of America
Pages (from-to)E11231-E11237
Number of pages7
Publication statusPublished - 27 Nov 2018

    Research areas

  • citizen science, optimal control, ultracold atoms, human problem solving, closed-loop optimization, QUANTUM, ADAPTATION

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