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Challenging local realism with human choices

Overview of attention for article published in Nature, May 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

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Title
Challenging local realism with human choices
Published in
Nature, May 2018
DOI 10.1038/s41586-018-0085-3
Pubmed ID
Authors

The BIG Bell Test Collaboration

Abstract

A Bell test is a randomized trial that compares experimental observations against the philosophical worldview of local realism 1 , in which the properties of the physical world are independent of our observation of them and no signal travels faster than light. A Bell test requires spatially distributed entanglement, fast and high-efficiency detection and unpredictable measurement settings2,3. Although technology can satisfy the first two of these requirements4-7, the use of physical devices to choose settings in a Bell test involves making assumptions about the physics that one aims to test. Bell himself noted this weakness in using physical setting choices and argued that human 'free will' could be used rigorously to ensure unpredictability in Bell tests 8 . Here we report a set of local-realism tests using human choices, which avoids assumptions about predictability in physics. We recruited about 100,000 human participants to play an online video game that incentivizes fast, sustained input of unpredictable selections and illustrates Bell-test methodology 9 . The participants generated 97,347,490 binary choices, which were directed via a scalable web platform to 12 laboratories on five continents, where 13 experiments tested local realism using photons5,6, single atoms 7 , atomic ensembles 10 and superconducting devices 11 . Over a 12-hour period on 30 November 2016, participants worldwide provided a sustained data flow of over 1,000 bits per second to the experiments, which used different human-generated data to choose each measurement setting. The observed correlations strongly contradict local realism and other realistic positions in bipartite and tripartite 12 scenarios. Project outcomes include closing the 'freedom-of-choice loophole' (the possibility that the setting choices are influenced by 'hidden variables' to correlate with the particle properties 13 ), the utilization of video-game methods 14 for rapid collection of human-generated randomness, and the use of networking techniques for global participation in experimental science.

X Demographics

X Demographics

The data shown below were collected from the profiles of 279 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 284 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 284 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 62 22%
Researcher 50 18%
Student > Master 26 9%
Professor 22 8%
Student > Bachelor 16 6%
Other 37 13%
Unknown 71 25%
Readers by discipline Count As %
Physics and Astronomy 116 41%
Engineering 19 7%
Agricultural and Biological Sciences 10 4%
Computer Science 7 2%
Social Sciences 7 2%
Other 50 18%
Unknown 75 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 565. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 March 2024.
All research outputs
#42,867
of 25,756,911 outputs
Outputs from Nature
#3,671
of 98,672 outputs
Outputs of similar age
#950
of 342,123 outputs
Outputs of similar age from Nature
#89
of 889 outputs
Altmetric has tracked 25,756,911 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 98,672 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 102.7. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 342,123 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 889 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.