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 & Complex network. The organization has 558 authors who have published 4558 publications receiving 396015 citations. The organization is also known as: SFI.

Grand challenges for archaeology

Abstract: Archaeology is a source of essential data regarding the fundamental nature of human societies. Researchers across the behavioral and social sciences use archeological data in framing foundational arguments. Archaeological evidence frequently undergirds debate on contemporary issues. We propose here to answer “What are archaeology’s most important scientific challenges?” The question arose as we sought to develop recommendations for investments in computational infrastructure that would enable the discipline to address its most compelling questions. Absent a list of these questions, we undertook to develop our own.

A comprehensive classification of complex statistical systems and an axiomatic derivation of their entropy and distribution functions

Abstract: Motivated by the hope that the thermodynamical framework might be extended to strongly interacting statistical systems —complex systems in particular— a number of generalized entropies has been proposed in the past. So far the understanding of their fundamental origin has remained unclear. Here we address this question from first principles. We start by observing that many statistical systems fulfill a set of three general conditions (Shannon-Khinchin axioms, K1–K3). A fourth condition (separability) holds for non-interacting, uncorrelated or Markovian systems only (Shannon-Khinchin axiom, K4). If all four axioms hold the Shannon theorem provides a unique entropy, , i.e. Boltzmann-Gibbs entropy. Here we ask about the consequences of violating the 4th axiom while assuming the first three to hold. By a simple scaling argument we prove that under these conditions each statistical system is characterized by a unique pair of scaling exponents (c, d) in the large size limit. These exponents define equivalence classes for all interacting and non-interacting systems and parametrize a unique entropy, , where Γ(a,b) is the incomplete Gamma function. It covers all systems respecting K1–K3. A series of known entropies can be classified in terms of these equivalence classes. Corresponding distribution functions are special forms of Lambert- exponentials containing —as special cases— Boltzmann, stretched exponential and Tsallis distributions (power laws) —all widely abundant in Nature. In the derivation we assume , with g some function, however more general entropic forms can be classified along the same lines. This is to our knowledge the first ab initio justification for generalized entropies. We discuss a physical example displaying two sets of scaling exponents depending on the external parameters.

Testing the metabolic theory of ecology

Abstract: The metabolic theory of ecology (MTE) predicts the effects of body size and temperature on metabolism through considerations of vascular distribution networks and biochemical kinetics. MTE has also been extended to characterise processes from cellular to global levels. MTE has generated both enthusiasm and controversy across a broad range of research areas. However, most efforts that claim to validate or invalidate MTE have focused on testing predictions. We argue that critical evaluation of MTE also requires strong tests of both its theoretical foundations and simplifying assumptions. To this end, we synthesise available information and find that MTE's original derivations require additional assumptions to obtain the full scope of attendant predictions. Moreover, although some of MTE's simplifying assumptions are well supported by data, others are inconsistent with empirical tests and even more remain untested. Further, although many predictions are empirically supported on average, work remains to explain the often large variability in data. We suggest that greater effort be focused on evaluating MTE's underlying theory and simplifying assumptions to help delineate the scope of MTE, generate new theory and shed light on fundamental aspects of biological form and function.

Three Brief Proofs of Arrow's Impossibility Theorem

Abstract: Arrow's original proof of his impossibility theorem proceeded in two steps: showing the existence of a decisive voter, and then showing that a decisive voter is a dictator. Barbera replaced the decisive voter with the weaker notion of a pivotal voter, thereby shortening the first step, but complicating the second step. I give three brief proofs, all of which turn on replacing the decisive/pivotal voter with an extremely pivotal voter (a voter who by unilaterally changing his vote can move some alternative from the bottom of the social ranking to the top), thereby simplifying both steps in Arrow's proof. My first proof is the most straightforward, and the second uses Condorcet preferences (which are transformed into each other by moving the bottom alternative to the top). The third (and shortest) proof proceeds by reinterpreting Step 1 of the first proof as saying that all social decisions are made the same way (neutrality).

The Fittest versus the Flattest: Experimental Confirmation of the Quasispecies Effect with Subviral Pathogens

Abstract: The “survival of the fittest” is the paradigm of Darwinian evolution in which the best-adapted replicators are favored by natural selection. However, at high mutation rates, the fittest organisms are not necessarily the fastest replicators but rather are those that show the greatest robustness against deleterious mutational effects, even at the cost of a low replication rate. This scenario, dubbed the “survival of the flattest”, has so far only been shown to operate in digital organisms. We show that “survival of the flattest” can also occur in biological entities by analyzing the outcome of competition between two viroid species coinfecting the same plant. Under optimal growth conditions, a viroid species characterized by fast population growth and genetic homogeneity outcompeted a viroid species with slow population growth and a high degree of variation. In contrast, the slow-growth species was able to outcompete the fast species when the mutation rate was increased. These experimental results were supported by an in silico model of competing viroid quasispecies.