SFI Community Lecture — 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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Postdocs to give flash talks, get writing tips in complexity conference

The fourth bi-annual Postdocs in Complexity Conference at the Santa Fe Institute provides networking opportunities for early career researchers working on complex systems science, as well as special sessions from SFI faculty and other prominent speakers. This three-day conference will build on the themes of the previous three Postdocs in Complexity meetings, refining the structure to allow additional time to build community and focus on collaborations.

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On time and being Maya

The Maya Working Group meets at SFI to discuss a new theme, “Being Maya,” which will focus on the cultural identity of the lowland Maya civilization.

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Working group to parse words, meaning

The bane of the language-learner is a goldmine for linguists, cultural evolutionists, and computer scientists, a group of whom will meet at SFI Aug. 27–28, 2018. Given the messy state of linguistic affairs, they ask, is it possible to quantitatively encode “meaning” independent of any particular language?

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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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