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

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Remote optimization of an ultracold atoms experiment by experts and citizen scientists. / Heck, Robert; Vuculescu, Oana; Sorensen, Jens Jakob; Zoller, Jonathan; Andreasen, Morten G.; Bason, Mark G.; Ejlertsen, Poul; Eliasson, Otto; Haikka, Pinja; Laustsen, Jens S.; Nielsen, Laerke L.; Mao, Andrew; Mueller, Romain; Napolitano, Mario; Pedersen, Mads K.; Thorsen, Aske R.; Bergenholtz, Carsten; Calarco, Tommaso; Montangero, Simone; Sherson, Jacob F.

In: Proceedings of the National Academy of Sciences of the United States of America, Vol. 115, No. 48, 27.11.2018, p. E11231-E11237.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Harvard

Heck, R, Vuculescu, O, Sorensen, JJ, Zoller, J, Andreasen, MG, Bason, MG, Ejlertsen, P, Eliasson, O, Haikka, P, Laustsen, JS, Nielsen, LL, Mao, A, Mueller, R, Napolitano, M, Pedersen, MK, Thorsen, AR, Bergenholtz, C, Calarco, T, Montangero, S & Sherson, JF 2018, 'Remote optimization of an ultracold atoms experiment by experts and citizen scientists', Proceedings of the National Academy of Sciences of the United States of America, vol. 115, no. 48, pp. E11231-E11237. https://doi.org/10.1073/pnas.1716869115

APA

Heck, R., Vuculescu, O., Sorensen, J. J., Zoller, J., Andreasen, M. G., Bason, M. G., ... Sherson, J. F. (2018). Remote optimization of an ultracold atoms experiment by experts and citizen scientists. Proceedings of the National Academy of Sciences of the United States of America, 115(48), E11231-E11237. https://doi.org/10.1073/pnas.1716869115

CBE

Heck R, Vuculescu O, Sorensen JJ, Zoller J, Andreasen MG, Bason MG, Ejlertsen P, Eliasson O, Haikka P, Laustsen JS, Nielsen LL, Mao A, Mueller R, Napolitano M, Pedersen MK, Thorsen AR, Bergenholtz C, Calarco T, Montangero S, Sherson JF. 2018. Remote optimization of an ultracold atoms experiment by experts and citizen scientists. Proceedings of the National Academy of Sciences of the United States of America. 115(48):E11231-E11237. https://doi.org/10.1073/pnas.1716869115

MLA

Heck, Robert et al. "Remote optimization of an ultracold atoms experiment by experts and citizen scientists". Proceedings of the National Academy of Sciences of the United States of America. 2018, 115(48). E11231-E11237. https://doi.org/10.1073/pnas.1716869115

Vancouver

Heck R, Vuculescu O, Sorensen JJ, Zoller J, Andreasen MG, Bason MG et al. Remote optimization of an ultracold atoms experiment by experts and citizen scientists. Proceedings of the National Academy of Sciences of the United States of America. 2018 Nov 27;115(48):E11231-E11237. https://doi.org/10.1073/pnas.1716869115

Author

Heck, Robert ; Vuculescu, Oana ; Sorensen, Jens Jakob ; Zoller, Jonathan ; Andreasen, Morten G. ; Bason, Mark G. ; Ejlertsen, Poul ; Eliasson, Otto ; Haikka, Pinja ; Laustsen, Jens S. ; Nielsen, Laerke L. ; Mao, Andrew ; Mueller, Romain ; Napolitano, Mario ; Pedersen, Mads K. ; Thorsen, Aske R. ; Bergenholtz, Carsten ; Calarco, Tommaso ; Montangero, Simone ; Sherson, Jacob F. / Remote optimization of an ultracold atoms experiment by experts and citizen scientists. In: Proceedings of the National Academy of Sciences of the United States of America. 2018 ; Vol. 115, No. 48. pp. E11231-E11237.

Bibtex

@article{607493c3775640b8a6527e13511bc14d,
title = "Remote optimization of an ultracold atoms experiment by experts and citizen scientists",
abstract = "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.",
keywords = "citizen science, optimal control, ultracold atoms, human problem solving, closed-loop optimization, QUANTUM, ADAPTATION",
author = "Robert Heck and Oana Vuculescu and Sorensen, {Jens Jakob} and Jonathan Zoller and Andreasen, {Morten G.} and Bason, {Mark G.} and Poul Ejlertsen and Otto Eliasson and Pinja Haikka and Laustsen, {Jens S.} and Nielsen, {Laerke L.} and Andrew Mao and Romain Mueller and Mario Napolitano and Pedersen, {Mads K.} and Thorsen, {Aske R.} and Carsten Bergenholtz and Tommaso Calarco and Simone Montangero and Sherson, {Jacob F.}",
year = "2018",
month = "11",
day = "27",
doi = "10.1073/pnas.1716869115",
language = "English",
volume = "115",
pages = "E11231--E11237",
journal = "Proceedings of the National Academy of Sciences of the United States of America",
issn = "0027-8424",
publisher = "The National Academy of Sciences of the United States of America",
number = "48",

}

RIS

TY - JOUR

T1 - Remote optimization of an ultracold atoms experiment by experts and citizen scientists

AU - Heck, Robert

AU - Vuculescu, Oana

AU - Sorensen, Jens Jakob

AU - Zoller, Jonathan

AU - Andreasen, Morten G.

AU - Bason, Mark G.

AU - Ejlertsen, Poul

AU - Eliasson, Otto

AU - Haikka, Pinja

AU - Laustsen, Jens S.

AU - Nielsen, Laerke L.

AU - Mao, Andrew

AU - Mueller, Romain

AU - Napolitano, Mario

AU - Pedersen, Mads K.

AU - Thorsen, Aske R.

AU - Bergenholtz, Carsten

AU - Calarco, Tommaso

AU - Montangero, Simone

AU - Sherson, Jacob F.

PY - 2018/11/27

Y1 - 2018/11/27

N2 - 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.

AB - 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.

KW - citizen science

KW - optimal control

KW - ultracold atoms

KW - human problem solving

KW - closed-loop optimization

KW - QUANTUM

KW - ADAPTATION

U2 - 10.1073/pnas.1716869115

DO - 10.1073/pnas.1716869115

M3 - Journal article

VL - 115

SP - E11231-E11237

JO - Proceedings of the National Academy of Sciences of the United States of America

JF - Proceedings of the National Academy of Sciences of the United States of America

SN - 0027-8424

IS - 48

ER -