Santa Fe Institute

About: Santa Fe Institute is a nonprofit organization based out in Santa Fe, New Mexico, United States. It is known for research contribution in the topics: Population & Context (language use). The organization has 558 authors who have published 4558 publications receiving 396015 citations. The organization is also known as: SFI.

Computational Mechanics: Pattern and Prediction, Structure and Simplicity

Abstract: Computational mechanics, an approach to structural complexity, defines a process's causal states and gives a procedure for finding them. We show that the causal-state representation—an ∈-machine—is the minimal one consistent with accurate prediction. We establish several results on ∈-machine optimality and uniqueness and on how ∈-machines compare to alternative representations. Further results relate measures of randomness and structural complexity obtained from ∈-machines to those from ergodic and information theories.

The Quark and the Jaguar: Adventures in the Simple and the Complex

Abstract: This book is about how the wonderful diversity of the universe can arise out of a set of fairly simple basic laws. It is written by an expert in both the fundamental laws and the complex structures that they can produce.' Stephen Hawking's acclaim of Murray Gell-Mann's literary debut is typical of the reception the book received on first publication in 1994. From one of the twentieth century's greatest scientists comes this unique, highly personal vision of the connections between the basic laws of physics and the complexity and diversity of the natural world. THE QUARK AND THE JAGUAR - the simple and the complex - is an irresistibly engaging and rewarding introduction to the life's work of physicist, polymath and Nobel Laureate Murray Gell-Mann.

The n‐dimensional hypervolume

Abstract: Aim The Hutchinsonian hypervolume is the conceptual foundation for many lines of ecological and evolutionary inquiry, including functional morphology, comparative biology, community ecology and niche theory. However, extant methods to sample from hypervolumes or measure their geometry perform poorly on high-dimensional or holey datasets. Innovation We first highlight the conceptual and computational issues that have prevented a more direct approach to measuring hypervolumes. Next, we present a new multivariate kernel density estimation method that resolves many of these problems in an arbitrary number of dimensions. Main conclusions We show that our method (implemented as the ‘hypervolume’ R package) can match several extant methods for hypervolume geometry and species distribution modelling. Tools to quantify high-dimensional ecological hypervolumes will enable a wide range of fundamental descriptive, inferential and comparative questions to be addressed.

Urban Scaling and Its Deviations: Revealing the Structure of Wealth, Innovation and Crime across Cities

Abstract: With urban population increasing dramatically worldwide, cities are playing an increasingly critical role in human societies and the sustainability of the planet. An obstacle to effective policy is the lack of meaningful urban metrics based on a quantitative understanding of cities. Typically, linear per capita indicators are used to characterize and rank cities. However, these implicitly ignore the fundamental role of nonlinear agglomeration integral to the life history of cities. As such, per capita indicators conflate general nonlinear effects, common to all cities, with local dynamics, specific to each city, failing to provide direct measures of the impact of local events and policy. Agglomeration nonlinearities are explicitly manifested by the superlinear power law scaling of most urban socioeconomic indicators with population size, all with similar exponents (*1.15). As a result larger cities are disproportionally the centers of innovation, wealth and crime, all to approximately the same degree. We use these general urban laws to develop new urban metrics that disentangle dynamics at different scales and provide true measures of local urban performance. New rankings of cities and a novel and simpler perspective on urban systems emerge. We find that local urban dynamics display long-term memory, so cities under or outperforming their size expectation maintain such (dis)advantage for decades. Spatiotemporal correlation analyses reveal a novel functional taxonomy of U.S. metropolitan areas that is generally not organized geographically but based instead on common local economic models, innovation strategies and patterns of crime.

Coevolution of dynamical states and interactions in dynamic networks.

Abstract: We explore the coupled dynamics of the internal states of a set of interacting elements and the network of interactions among them. Interactions are modeled by a spatial game and the network of interaction links evolves adapting to the outcome of the game. As an example, we consider a model of cooperation in which the adaptation is shown to facilitate the formation of a hierarchical interaction network that sustains a highly cooperative stationary state. The resulting network has the characteristics of a small world network when a mechanism of local neighbor selection is introduced in the adaptive network dynamics. The highly connected nodes in the hierarchical structure of the network play a leading role in the stability of the network. Perturbations acting on the state of these special nodes trigger global avalanches leading to complete network reorganization.