Using data from humans and other mammals, a team of scientists including researchers from the Santa Fe Institute has developed one of the first quantitative models that explains why sleep times across species and during development decrease as brains get bigger. Crucially, the model identifies a sharp transition at around 2.4 years of age, where sleep patterns change in humans as the primary purpose of sleep shifts from reorganization to repair.
SFI External Professor Raissa D’Souza has joined the Board of Reviewing Editors at Science magazine, one of the world’s top peer-reviewed journals.
SFI's Artemy Kolchinsky and David Wolpert present their work exploring the thermodynamics of computation within the context of Turing machines.
Leaders of sustainability organizations report on valuable lessons they’ve distilled from their own experiences about successful leadership.
If voters gravitate toward the center of the political spectrum, why are the parties drifting farther apart? A new model by SFI's Vicky Chuqiao Yang and her collaborators reveals a mechanism for increased polarization in U.S. politics, guided by the idea of "satisficing"-- that people will settle for a candidate who is "good enough."
A new paper by Professor Sid Redner and his collaborators gives a statistical model for optimizing mechanical processes where components wear down and must be reset. It has been chosen as an Editor's Suggestion at the high-profile physics journal, Physical Review Letters.
Leaving money on the table to stay in the game: New paper squares economic choice with evolutionary survival
How biological survival relates to economic choice is the crux of a new paper by SFI's Michael Price and Stanford's James Holland Jones.
Workshops and working groups are among the defining features of science at SFI, but the dividends sometimes follow months or years down the line.
SFI External Professor Ross Hammond and collaborators have developed a new agent-based computer model that helps policy-makers simulate multiple variations for re-opening. It can incorporate critical factors in determining how to contain COVID-19, such as variations in age, contact networks, activity patterns, and likelihood of infection.
Transmission T-035: Amos Golan on info-metrics for modeling and inference with complex and uncertain pandemic information
We must use a modeling approach to COVID-19 data that will yield the least biased inference and prediction.
When thinking about reopening schools, an important factor to consider is the rate of community transmission.
Human cognition and cultural norms have changed the composition of human portraits, according to a new analysis of European paintings from the 15th to the 20th century. The study, led by SFI Omidyar Fellow Helena Miton, examined "bias" in 1831 paintings by 582 unique European painters.
Swing voters, swing stocks, swing users: Scientists develop a general technique for identifying swing components
A new technique could help identify prime candidates for changing election outcomes, or lead to a better understanding of how institutional and environmental factors shape the emergence of social structure.
External Professor Emeritus Constantino Tsallis and his colleague describe a single function that accurately describes all existing available data on active COVID-19 cases and deaths—and aims to predict forthcoming peaks.
On April 15, SFI hosted a flash discussion that focused on human behavior, incentives, and beliefs. The overarching message was that the financial and social fallout of the pandemic, while difficult to predict, will largely depend on actions at individual, community, and institutional levels.