Video: Quantum Computers

Sending instantaneous messages across long distances, or quickly computing over ungodly amounts of data are just two possibilities that arise if we can design computers to exploit quantum uncertainty, entanglement, and measurement. In this SFI Community Lecture, scientist Christopher Monroe describes the architecture of a quantum computer based on individual atoms, suspended and isolated with electric fields, and individually addressed with laser beams.

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Social animals have tipping points, too

Quantitative tools developed in math and physics to understand bifurcations in dynamical systems could help ecologists and biologists better understand — and predict — tipping points in animal societies.

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Theory, meet Empiry

It may seem that there isn't much cross-discussion between theoretical and empirical scientists, but a new cross-citation network analysis shows there is more overlap than many believe. 

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Networks, second edition

SFI External Professor Mark Newman has updated his classic textbook on networks. Oxford University Press publishes Networks, second edition, in early September, 2018.

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New external faculty announced for 2018

SFI welcomes ten new professors to our external faculty, a cohort of academics who enrich our networks of interactions, help us push the boundaries of complex systems science, and connect us to over 70 institutions around the globe.

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Broken brains and network structures

Neuroscientists and complexity scientists meet to develop new tools for studying the brain as a complex network. Their working group, titled “Cognitive Regime Shift: When the Brain Breaks,” is part of SFI’s Aging, Adaptation, and the Arrow of Time research theme, funded by the James S. McDonnell Foundation.

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Parakeet pecking orders, basketball match-ups, and the tenure-track: How analyzing winners and losers can reveal rank within networks

In a paper published in Science Advances, researchers from the Santa Fe Institute describe a new algorithm called SpringRank that uses wins and losses to quickly find rankings lurking in large networks. When tested on a wide range of synthetic and real-world datasets, ranging from teams in an NCAA college basketball tournament to the social behavior of animals, SpringRank outperformed other ranking algorithms in predicting outcomes and in efficiency.

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Workshop explores team culture and human performance

This question of how the collective influences individual performance is central to the work of SFI’s investigation into the limits of human performance. In a workshop that takes place June 25-27, experts from a range of disciplines, including physiology, organizational behavior, sports analytics and applied mathematics, explore how the collective affects the individual.

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