scispace - formally typeset
Search or ask a question

Showing papers by "Santa Fe Institute published in 2018"


Journal ArticleDOI
29 Jun 2018-Science
TL;DR: In this paper, the authors examine barriers and opportunities associated with these difficult-to-decarbonize services and processes, including possible technological solutions and research and development priorities, and examine the use of existing technologies to meet future demands for these services without net addition of CO2 to the atmosphere.
Abstract: Some energy services and industrial processes-such as long-distance freight transport, air travel, highly reliable electricity, and steel and cement manufacturing-are particularly difficult to provide without adding carbon dioxide (CO2) to the atmosphere. Rapidly growing demand for these services, combined with long lead times for technology development and long lifetimes of energy infrastructure, make decarbonization of these services both essential and urgent. We examine barriers and opportunities associated with these difficult-to-decarbonize services and processes, including possible technological solutions and research and development priorities. A range of existing technologies could meet future demands for these services and processes without net addition of CO2 to the atmosphere, but their use may depend on a combination of cost reductions via research and innovation, as well as coordinated deployment and integration of operations across currently discrete energy industries.

951 citations


Book ChapterDOI
TL;DR: In this paper, the authors propose a theory of asset pricing based on heterogeneous agents who continually adapt their expectations to the market that these expectations aggregatively create, and explore the implications of this theory computationally using Santa Fe artificial stock market.
Abstract: This chapter proposes a theory of asset pricing based on heterogeneous agents who continually adapt their expectations to the market that these expectations aggregatively create. It explores the implications of this theory computationally using Santa Fe artificial stock market. Computer experiments with this endogenous-expectations market explain one of the more striking puzzles in finance: that market traders often believe in such concepts as technical trading, "market psychology," and bandwagon effects, while academic theorists believe in market efficiency and a lack of speculative opportunities. Academic theorists and market traders tend to view financial markets in strikingly different ways. Standard (efficient-market) financial theory assumes identical investors who share rational expectations of an asset's future price, and who instantaneously and rationally discount all market information into this price. While a few academics would be willing to assert that the market has a personality or experiences moods, the standard economic view has in recent years begun to change.

929 citations


Journal ArticleDOI
Anne D. Bjorkman1, Anne D. Bjorkman2, Isla H. Myers-Smith2, Sarah C. Elmendorf3, Sarah C. Elmendorf4, Sarah C. Elmendorf5, Signe Normand1, Nadja Rüger6, Pieter S. A. Beck, Anne Blach-Overgaard1, Daan Blok7, J. Hans C. Cornelissen8, Bruce C. Forbes9, Damien Georges2, Scott J. Goetz10, Kevin C. Guay11, Gregory H. R. Henry12, Janneke HilleRisLambers13, Robert D. Hollister14, Dirk Nikolaus Karger15, Jens Kattge16, Peter Manning, Janet S. Prevéy, Christian Rixen, Gabriela Schaepman-Strub17, Haydn J.D. Thomas2, Mark Vellend18, Martin Wilmking19, Sonja Wipf, Michele Carbognani20, Luise Hermanutz21, Esther Lévesque22, Ulf Molau23, Alessandro Petraglia20, Nadejda A. Soudzilovskaia24, Marko J. Spasojevic25, Marcello Tomaselli20, Tage Vowles23, Juha M. Alatalo26, Heather D. Alexander27, Alba Anadon-Rosell28, Alba Anadon-Rosell19, Sandra Angers-Blondin2, Mariska te Beest29, Mariska te Beest30, Logan T. Berner10, Robert G. Björk23, Agata Buchwal31, Agata Buchwal32, Allan Buras33, Katherine S. Christie34, Elisabeth J. Cooper35, Stefan Dullinger36, Bo Elberling37, Anu Eskelinen38, Anu Eskelinen39, Esther R. Frei12, Esther R. Frei15, Oriol Grau40, Paul Grogan41, Martin Hallinger, Karen A. Harper42, Monique M. P. D. Heijmans33, James I. Hudson, Karl Hülber36, Maitane Iturrate-Garcia17, Colleen M. Iversen43, Francesca Jaroszynska44, Jill F. Johnstone45, Rasmus Halfdan Jørgensen37, Elina Kaarlejärvi29, Elina Kaarlejärvi46, Rebecca A Klady12, Sara Kuleza45, Aino Kulonen, Laurent J. Lamarque22, Trevor C. Lantz47, Chelsea J. Little48, Chelsea J. Little17, James D. M. Speed49, Anders Michelsen37, Ann Milbau50, Jacob Nabe-Nielsen1, Sigrid Schøler Nielsen1, Josep M. Ninot28, Steven F. Oberbauer51, Johan Olofsson29, Vladimir G. Onipchenko52, Sabine B. Rumpf36, Philipp R. Semenchuk35, Philipp R. Semenchuk36, Rohan Shetti19, Laura Siegwart Collier21, Lorna E. Street2, Katharine N. Suding5, Ken D. Tape53, Andrew J. Trant21, Andrew J. Trant54, Urs A. Treier1, Jean-Pierre Tremblay55, Maxime Tremblay22, Susanna Venn56, Stef Weijers57, Tara Zamin41, Noémie Boulanger-Lapointe12, William A. Gould58, David S. Hik59, Annika Hofgaard, Ingibjörg S. Jónsdóttir60, Ingibjörg S. Jónsdóttir61, Janet C. Jorgenson62, Julia A. Klein63, Borgthor Magnusson, Craig E. Tweedie64, Philip A. Wookey65, Michael Bahn66, Benjamin Blonder67, Benjamin Blonder68, Peter M. van Bodegom24, Benjamin Bond-Lamberty69, Giandiego Campetella70, Bruno Enrico Leone Cerabolini71, F. Stuart Chapin53, William K. Cornwell72, Joseph M. Craine, Matteo Dainese, Franciska T. de Vries73, Sandra Díaz74, Brian J. Enquist75, Brian J. Enquist76, Walton A. Green77, Rubén Milla78, Ülo Niinemets79, Yusuke Onoda80, Jenny C. Ordoñez81, Wim A. Ozinga33, Wim A. Ozinga82, Josep Peñuelas40, Hendrik Poorter83, Hendrik Poorter84, Peter Poschlod85, Peter B. Reich86, Peter B. Reich87, Brody Sandel88, Brandon S. Schamp89, Serge N. Sheremetev90, Evan Weiher91 
Aarhus University1, University of Edinburgh2, National Ecological Observatory Network3, Institute of Arctic and Alpine Research4, University of Colorado Boulder5, Smithsonian Institution6, Lund University7, VU University Amsterdam8, University of Lapland9, Northern Arizona University10, Bigelow Laboratory For Ocean Sciences11, University of British Columbia12, University of Washington13, Grand Valley State University14, Swiss Federal Institute for Forest, Snow and Landscape Research15, Max Planck Society16, University of Zurich17, Université de Sherbrooke18, University of Greifswald19, University of Parma20, Memorial University of Newfoundland21, Université du Québec à Trois-Rivières22, University of Gothenburg23, Leiden University24, University of California, Riverside25, Qatar University26, Mississippi State University27, University of Barcelona28, Umeå University29, Utrecht University30, University of Alaska Anchorage31, Adam Mickiewicz University in Poznań32, Wageningen University and Research Centre33, Alaska Department of Fish and Game34, University of Tromsø35, University of Vienna36, University of Copenhagen37, Helmholtz Centre for Environmental Research - UFZ38, University of Oulu39, Spanish National Research Council40, Queen's University41, Saint Mary's University42, Oak Ridge National Laboratory43, University of Aberdeen44, University of Saskatchewan45, Vrije Universiteit Brussel46, University of Victoria47, Swiss Federal Institute of Aquatic Science and Technology48, Norwegian University of Science and Technology49, Research Institute for Nature and Forest50, Florida International University51, Moscow State University52, University of Alaska Fairbanks53, University of Waterloo54, Laval University55, Deakin University56, University of Bonn57, United States Forest Service58, Simon Fraser University59, University Centre in Svalbard60, University of Iceland61, United States Fish and Wildlife Service62, Colorado State University63, University of Texas at El Paso64, University of Stirling65, University of Innsbruck66, University of Oxford67, Rocky Mountain Biological Laboratory68, Pacific Northwest National Laboratory69, University of Camerino70, University of Insubria71, University of New South Wales72, University of Manchester73, National University of Cordoba74, Santa Fe Institute75, University of Arizona76, Harvard University77, King Juan Carlos University78, Estonian University of Life Sciences79, Kyoto University80, World Agroforestry Centre81, Radboud University Nijmegen82, Forschungszentrum Jülich83, Macquarie University84, University of Regensburg85, University of Sydney86, University of Minnesota87, Santa Clara University88, Algoma University89, Komarov Botanical Institute90, University of Wisconsin–Eau Claire91
04 Oct 2018-Nature
TL;DR: Biome-wide relationships between temperature, moisture and seven key plant functional traits across the tundra and over time show that community height increased with warming across all sites, whereas other traits lagged behind predicted rates of change.
Abstract: The tundra is warming more rapidly than any other biome on Earth, and the potential ramifications are far-reaching because of global feedback effects between vegetation and climate. A better understanding of how environmental factors shape plant structure and function is crucial for predicting the consequences of environmental change for ecosystem functioning. Here we explore the biome-wide relationships between temperature, moisture and seven key plant functional traits both across space and over three decades of warming at 117 tundra locations. Spatial temperature-trait relationships were generally strong but soil moisture had a marked influence on the strength and direction of these relationships, highlighting the potentially important influence of changes in water availability on future trait shifts in tundra plant communities. Community height increased with warming across all sites over the past three decades, but other traits lagged far behind predicted rates of change. Our findings highlight the challenge of using space-for-time substitution to predict the functional consequences of future warming and suggest that functions that are tied closely to plant height will experience the most rapid change. They also reveal the strength with which environmental factors shape biotic communities at the coldest extremes of the planet and will help to improve projections of functional changes in tundra ecosystems with climate warming.

425 citations


Proceedings Article
15 Feb 2018
TL;DR: This article showed that the information plane trajectory is predominantly a function of the neural nonlinearity employed: double-sided saturating nonlinearities such as tanh yield a compression phase as neural activations enter the saturation regime, but linear activation functions and single-sided saturated non-linearities like ReLU in fact do not.
Abstract: The practical successes of deep neural networks have not been matched by theoretical progress that satisfyingly explains their behavior. In this work, we study the information bottleneck (IB) theory of deep learning, which makes three specific claims: first, that deep networks undergo two distinct phases consisting of an initial fitting phase and a subsequent compression phase; second, that the compression phase is causally related to the excellent generalization performance of deep networks; and third, that the compression phase occurs due to the diffusion-like behavior of stochastic gradient descent. Here we show that none of these claims hold true in the general case. Through a combination of analytical results and simulation, we demonstrate that the information plane trajectory is predominantly a function of the neural nonlinearity employed: double-sided saturating nonlinearities like tanh yield a compression phase as neural activations enter the saturation regime, but linear activation functions and single-sided saturating nonlinearities like the widely used ReLU in fact do not. Moreover, we find that there is no evident causal connection between compression and generalization: networks that do not compress are still capable of generalization, and vice versa. Next, we show that the compression phase, when it exists, does not arise from stochasticity in training by demonstrating that we can replicate the IB findings using full batch gradient descent rather than stochastic gradient descent. Finally, we show that when an input domain consists of a subset of task-relevant and task-irrelevant information, hidden representations do compress the task-irrelevant information, although the overall information about the input may monotonically increase with training time, and that this compression happens concurrently with the fitting process rather than during a subsequent compression period.

387 citations


Journal ArticleDOI
TL;DR: In this paper, a conceptual framework and quantitative method for quantifying the causes of cost changes in a technology, and apply it to PV modules, is presented, which can be adapted to retrospectively or prospectively study many technologies, and performance metrics besides cost.

229 citations


Journal ArticleDOI
TL;DR: Random graph null models have found widespread application in diverse research communities analyzing network datasets, including social, information, and economic networks, as well as food webs, pr....
Abstract: Random graph null models have found widespread application in diverse research communities analyzing network datasets, including social, information, and economic networks, as well as food webs, pr...

172 citations


Journal ArticleDOI
TL;DR: Track single cell volume over the cell cycle and generate a mathematical framework to compare size homeostasis in datasets ranging from bacteria to mammalian cells reveal that a near-adder behavior is the most common type of size control and highlights the importance of growth rate modulation to size control in mammalian cells.
Abstract: Despite decades of research, how mammalian cell size is controlled remains unclear because of the difficulty of directly measuring growth at the single-cell level. Here we report direct measurements of single-cell volumes over entire cell cycles on various mammalian cell lines and primary human cells. We find that, in a majority of cell types, the volume added across the cell cycle shows little or no correlation to cell birth size, a homeostatic behavior called "adder". This behavior involves modulation of G1 or S-G2 duration and modulation of growth rate. The precise combination of these mechanisms depends on the cell type and the growth condition. We have developed a mathematical framework to compare size homeostasis in datasets ranging from bacteria to mammalian cells. This reveals that a near-adder behavior is the most common type of size control and highlights the importance of growth rate modulation to size control in mammalian cells.

167 citations


01 Dec 2018
TL;DR: A conceptual framework and quantitative method for quantifying the causes of cost changes in a technology, and it is found that increased module efficiency was the leading low-level cause of cost reduction in 1980–2012, contributing almost 25% of the decline.
Abstract: Photovoltaic (PV) module costs have declined rapidly over forty years but the reasons remain elusive. Here we advance a conceptual framework and quantitative method for quantifying the causes of cost changes in a technology, and apply it to PV modules. Our method begins with a cost model that breaks down cost into variables that changed over time. Cost change equations are then derived to quantify each variable's contribution. We distinguish between changes observed in variables of the cost model – which we term low-level mechanisms of cost reduction – and research and development, learning-by-doing, and scale economies, which we refer to as high-level mechanisms. We find that increased module efficiency was the leading low-level cause of cost reduction in 1980–2012, contributing almost 25% of the decline. Government-funded and private R&D was the most important high-level mechanism over this period. After 2001, however, scale economies became a more significant cause of cost reduction, approaching R&D in importance. Policies that stimulate market growth have played a key role in enabling PV's cost reduction, through privately-funded R&D and scale economies, and to a lesser extent learning-by-doing. The method presented here can be adapted to retrospectively or prospectively study many technologies, and performance metrics besides cost.

142 citations


Journal ArticleDOI
TL;DR: An overview of the potential mechanisms underlying collective navigation is provided, how both social and collective learning during group navigation could lead to the accumulation of knowledge at the population level, resulting in the emergence of migratory culture is explored.
Abstract: Animals often travel in groups, and their navigational decisions can be influenced by social interactions. Both theory and empirical observations suggest that such collective navigation can result ...

132 citations


Journal ArticleDOI
TL;DR: A database of historical and archaeological information from 30 regions around the world over the last 10,000 years revealed that characteristics, such as social scale, economy, features of governance, and information systems, show strong evolutionary relationships with each other and that complexity of a society across different world regions can be meaningfully measured using a single principal component of variation.
Abstract: Do human societies from around the world exhibit similarities in the way that they are structured, and show commonalities in the ways that they have evolved? These are long-standing questions that have proven difficult to answer. To test between competing hypotheses, we constructed a massive repository of historical and archaeological information known as “Seshat: Global History Databank.” We systematically coded data on 414 societies from 30 regions around the world spanning the last 10,000 years. We were able to capture information on 51 variables reflecting nine characteristics of human societies, such as social scale, economy, features of governance, and information systems. Our analyses revealed that these different characteristics show strong relationships with each other and that a single principal component captures around three-quarters of the observed variation. Furthermore, we found that different characteristics of social complexity are highly predictable across different world regions. These results suggest that key aspects of social organization are functionally related and do indeed coevolve in predictable ways. Our findings highlight the power of the sciences and humanities working together to rigorously test hypotheses about general rules that may have shaped human history.

130 citations


Journal ArticleDOI
TL;DR: In this article, a hybrid quantum algorithm employing a restricted Boltzmann machine to obtain accurate molecular potential energy surfaces was presented, which achieved high accuracy for the ground state energy for H2, LiH, H2O.
Abstract: Considering recent advancements and successes in the development of efficient quantum algorithms for electronic structure calculations—alongside impressive results using machine learning techniques for computation—hybridizing quantum computing with machine learning for the intent of performing electronic structure calculations is a natural progression. Here we report a hybrid quantum algorithm employing a restricted Boltzmann machine to obtain accurate molecular potential energy surfaces. By exploiting a quantum algorithm to help optimize the underlying objective function, we obtained an efficient procedure for the calculation of the electronic ground state energy for a small molecule system. Our approach achieves high accuracy for the ground state energy for H2, LiH, H2O at a specific location on its potential energy surface with a finite basis set. With the future availability of larger-scale quantum computers, quantum machine learning techniques are set to become powerful tools to obtain accurate values for electronic structures. With the rapid development of quantum computers, quantum machine learning approaches are emerging as powerful tools to perform electronic structure calculations. Here, the authors develop a quantum machine learning algorithm, which demonstrates significant improvements in solving quantum many-body problems.

Journal ArticleDOI
03 Apr 2018
TL;DR: In this paper, the authors highlight the numerous factors that limit understanding of the risk of space radiation for human crews and identify ways in which these limitations could be addressed for improved understanding and appropriate risk posture regarding future human spaceflight.
Abstract: Despite years of research, understanding of the space radiation environment and the risk it poses to long-duration astronauts remains limited. There is a disparity between research results and observed empirical effects seen in human astronaut crews, likely due to the numerous factors that limit terrestrial simulation of the complex space environment and extrapolation of human clinical consequences from varied animal models. Given the intended future of human spaceflight, with efforts now to rapidly expand capabilities for human missions to the moon and Mars, there is a pressing need to improve upon the understanding of the space radiation risk, predict likely clinical outcomes of interplanetary radiation exposure, and develop appropriate and effective mitigation strategies for future missions. To achieve this goal, the space radiation and aerospace community must recognize the historical limitations of radiation research and how such limitations could be addressed in future research endeavors. We have sought to highlight the numerous factors that limit understanding of the risk of space radiation for human crews and to identify ways in which these limitations could be addressed for improved understanding and appropriate risk posture regarding future human spaceflight.

Journal ArticleDOI
TL;DR: In this article, the exact probability distribution of a run-and-tumble particle with and without diffusion on the infinite line, as well as in a finite interval, was investigated.
Abstract: We investigate the motion of a run-and-tumble particle (RTP) in one dimension. We find the exact probability distribution of the particle with and without diffusion on the infinite line, as well as in a finite interval. In the infinite domain, this probability distribution approaches a Gaussian form in the long-time limit, as in the case of a regular Brownian particle. At intermediate times, this distribution exhibits unexpected multi-modal forms. In a finite domain, the probability distribution reaches a steady state form with peaks at the boundaries, in contrast to a Brownian particle. We also study the relaxation to the steady state analytically. Finally we compute the survival probability of the RTP in a semi-infinite domain. In the finite interval, we compute the exit probability and the associated exit times. We provide numerical verifications of our analytical results.

Journal ArticleDOI
TL;DR: This paper defines semantic information as the syntactic information that a physical system has about its environment which is causally necessary for the system to maintain its own existence, and uses recent results in non-equilibrium statistical physics to analyse semantic information from a thermodynamic point of view.
Abstract: Shannon information theory provides various measures of so-called syntactic information, which reflect the amount of statistical correlation between systems. By contrast, the concept of ‘semantic i...

Journal ArticleDOI
Jean Bousquet1, Sylvie Arnavielhe, A. Bedbrook, M. Bewick, Daniel Laune, E. Mathieu-Dupas, Ruth Murray, Gabrielle L. Onorato, Jean-Louis Pépin2, R. Picard, F. Portejoie, Elísio Costa3, João Fonseca3, Olga Lourenço4, M. Morais-Almeida, Ana Todo-Bom5, A. A. Cruz6, J. da Silva7, Faradiba Sarquis Serpa, Maddalena Illario, Enrica Menditto8, Lorenzo Cecchi, Ricardo Pio Monti9, Luigi Napoli, M. T. Ventura10, G. De Feo11, Désirée Larenas-Linnemann, M. Fuentes Perez, Y. R. Huerta Villabolos, Daniela Rivero-Yeverino, Erendira Rodriguez-Zagal, Flore Amat12, Isabella Annesi-Maesano13, Isabelle Bosse, Pascal Demoly, P. Devillier14, J. F. Fontaine, Jocelyne Just12, T. P. Kuna15, B. Samolinski16, A. Valiulis16, A. Valiulis17, R. Emuzyte18, Violeta Kvedariene18, Dermot Ryan19, Aziz Sheikh19, P. Schmidt-Grendelmeier20, Leszek Klimek21, Oliver Pfaar21, K. C. Bergmann22, Ralph Mösges23, Torsten Zuberbier22, Regina Roller-Wirnsberger24, P. V. Tomazic24, W. J. Fokkens25, Niels H. Chavannes26, Sietze Reitsma25, Josep M. Antó, Victoria Cardona, T. Dedeu, J Mullol27, Tari Haahtela, Johanna Salimäki, Sanna Toppila-Salmi, Erkka Valovirta28, B. Gemicioǧlu29, A. Yorgancioglu30, Nikolaos G. Papadopoulos31, Nikolaos G. Papadopoulos32, Emmanuel P. Prokopakis33, Sinthia Bosnic-Anticevich34, Robyn E O'Hehir35, Juan Carlos Ivancevich, H. Neffen36, E. Zernotti37, Inger Kull38, Erik Melén38, Magnus Wickman39, Claus Bachert40, Peter Hellings25, Peter Hellings41, S. Palkonen, Carsten Bindslev-Jensen42, Esben Eller42, Susan Waserman43, Milan Sova, G. De Vries, M. van Eerd, Ioana Agache44, Thomas B. Casale45, Marc Dykewickz46, R. N. Naclerio47, Y. Okamoto48, Dana Wallace49 
TL;DR: An overview of the methods used in MASK and the key results obtained to date include a novel phenotypic characterization of the patients, confirmation of the impact of allergic rhinitis on work productivity and treatment patterns in real life and the potential usefulness of MASK will be further explored.
Abstract: mHealth, such as apps running on consumer smart devices is becoming increasingly popular and has the potential to profoundly affect healthcare and health outcomes. However, it may be disruptive and results achieved are not always reaching the goals. Allergic Rhinitis and its Impact on Asthma (ARIA) has evolved from a guideline using the best evidence-based approach to care pathways suited to real-life using mobile technology in allergic rhinitis (AR) and asthma multimorbidity. Patients largely use over-the-counter medications dispensed in pharmacies. Shared decision making centered around the patient and based on self-management should be the norm. Mobile Airways Sentinel networK (MASK), the Phase 3 ARIA initiative, is based on the freely available MASK app (the Allergy Diary, Android and iOS platforms). MASK is available in 16 languages and deployed in 23 countries. The present paper provides an overview of the methods used in MASK and the key results obtained to date. These include a novel phenotypic characterization of the patients, confirmation of the impact of allergic rhinitis on work productivity and treatment patterns in real life. Most patients appear to self-medicate, are often non-adherent and do not follow guidelines. Moreover, the Allergy Diary is able to distinguish between AR medications. The potential usefulness of MASK will be further explored by POLLAR (Impact of Air Pollution on Asthma and Rhinitis), a new Horizon 2020 project using the Allergy Diary.

Journal ArticleDOI
TL;DR: Using reconstructed transcripts of debates held in the Revolution’s first parliament, a quantitative analysis of how this body managed innovation is presented, using information theory to track the creation, transmission, and destruction of word-use patterns across over 40,000 speeches and a thousand speakers.
Abstract: The French Revolution brought principles of “liberty, equality, fraternity” to bear on the day-to-day challenges of governing what was then the largest country in Europe. Its experiments provided a model for future revolutions and democracies across the globe, but this first modern revolution had no model to follow. Using reconstructed transcripts of debates held in the Revolution’s first parliament, we present a quantitative analysis of how this body managed innovation. We use information theory to track the creation, transmission, and destruction of word-use patterns across over 40,000 speeches and a thousand speakers. The parliament as a whole was biased toward the adoption of new patterns, but speakers’ individual qualities could break these overall trends. Speakers on the left innovated at higher rates, while speakers on the right acted to preserve prior patterns. Key players such as Robespierre (on the left) and Abbe Maury (on the right) played information-processing roles emblematic of their politics. Newly created organizational functions—such as the Assembly president and committee chairs—had significant effects on debate outcomes, and a distinct transition appears midway through the parliament when committees, external to the debate process, gained new powers to “propose and dispose.” Taken together, these quantitative results align with existing qualitative interpretations, but also reveal crucial information-processing dynamics that have hitherto been overlooked. Great orators had the public’s attention, but deputies (mostly on the political left) who mastered the committee system gained new powers to shape revolutionary legislation.

Journal ArticleDOI
TL;DR: It is shown that one can map the molecular Hamiltonian to an Ising-type Hamiltonian which could easily be implemented on currently available quantum hardware and is an early step in developing generalized methods on such devices for chemical physics.
Abstract: Obtaining exact solutions to the Schrodinger equation for atoms, molecules, and extended systems continues to be a “Holy Grail” problem which the fields of theoretical chemistry and physics have been striving to solve since inception. Recent breakthroughs have been made in the development of hardware-efficient quantum optimizers and coherent Ising machines capable of simulating hundreds of interacting spins with an Ising-type Hamiltonian. One of the most vital questions pertaining to these new devices is, “Can these machines be used to perform electronic structure calculations?” Within this work, we review the general procedure used by these devices and prove that there is an exact mapping between the electronic structure Hamiltonian and the Ising Hamiltonian. Additionally, we provide simulation results of the transformed Ising Hamiltonian for H2 , He2 , HeH+, and LiH molecules, which match the exact numerical calculations. This demonstrates that one can map the molecular Hamiltonian to an Ising-type Hami...

Journal ArticleDOI
TL;DR: Trait variations for woody versus herbaceous assemblages appear to reflect alternative strategies and differing environmental constraints, suggesting that a more synthetic framework is needed that addresses how suites of traits within and across broad functional groups respond to climate.
Abstract: AimDespite several recent efforts to map plant traits and to identify their climatic drivers, there are still major gaps. Global trait patterns for major functional groups, in particular, the differences between woody and herbaceous plants, have yet to be identified. Here, we take advantage of big data efforts to compile plant species occurrence and trait data to analyse the spatial patterns of assemblage means and variances of key plant traits. We tested whether these patterns and their climatic drivers are similar for woody and herbaceous plants. LocationNew World (North and South America). MethodsUsing the largest currently available database of plant occurrences, we provide maps of 200 × 200 km grid‐cell trait means and variances for both woody and herbaceous species and identify environmental drivers related to these patterns. We focus on six plant traits: maximum plant height, specific leaf area, seed mass, wood density, leaf nitrogen concentration and leaf phosphorus concentration. ResultsFor woody assemblages, we found a strong climate signal for both means and variances of most of the studied traits, consistent with strong environmental filtering. In contrast, for herbaceous assemblages, spatial patterns of trait means and variances were more variable, the climate signal on trait means was often different and weaker. Main conclusionTrait variations for woody versus herbaceous assemblages appear to reflect alternative strategies and differing environmental constraints. Given that most large‐scale trait studies are based on woody species, the strikingly different biogeographic patterns of herbaceous traits suggest that a more synthetic framework is needed that addresses how suites of traits within and across broad functional groups respond to climate.

Journal ArticleDOI
TL;DR: The fine-scale interaction rules of migrating caribou are revealed and a map of near neighbour influence is constructed that quantifies the nature of information flow in these herds, leading to better predictions of spatial use patterns and responses to changing environmental conditions.
Abstract: Social interactions are a significant factor that influence the decision-making of species ranging from humans to bacteria. In the context of animal migration, social interactions may lead to improved decision-making, greater ability to respond to environmental cues, and the cultural transmission of optimal routes. Despite their significance, the precise nature of social interactions in migrating species remains largely unknown. Here we deploy unmanned aerial systems to collect aerial footage of caribou as they undertake their migration from Victoria Island to mainland Canada. Through a Bayesian analysis of trajectories we reveal the fine-scale interaction rules of migrating caribou and show they are attracted to one another and copy directional choices of neighbours, but do not interact through clearly defined metric or topological interaction ranges. By explicitly considering the role of social information on movement decisions we construct a map of near neighbour influence that quantifies the nature of information flow in these herds. These results will inform more realistic, mechanism-based models of migration in caribou and other social ungulates, leading to better predictions of spatial use patterns and responses to changing environmental conditions. Moreover, we anticipate that the protocol we developed here will be broadly applicable to study social behaviour in a wide range of migratory and non-migratory taxa.This article is part of the theme issue 'Collective movement ecology'.

Journal ArticleDOI
TL;DR: A computational tool is developed to track recombination in patients, identify recombination hot spots, and show contribution of recombination to antibody escape, which provides insight into molecular mechanisms by which viral recombination contributes to HIV-1 persistence and immunopathogenesis.
Abstract: Recombination in HIV-1 is well documented, but its importance in the low-diversity setting of within-host diversification is less understood. Here we develop a novel computational tool (RAPR (Recombination Analysis PRogram)) to enable a detailed view of in vivo viral recombination during early infection, and we apply it to near-full-length HIV-1 genome sequences from longitudinal samples. Recombinant genomes rapidly replace transmitted/founder (T/F) lineages, with a median half-time of 27 days, increasing the genetic complexity of the viral population. We identify recombination hot and cold spots that differ from those observed in inter-subtype recombinants. Furthermore, RAPR analysis of longitudinal samples from an individual with well-characterized neutralizing antibody responses shows that recombination helps carry forward resistance-conferring mutations in the diversifying quasispecies. These findings provide insight into molecular mechanisms by which viral recombination contributes to HIV-1 persistence and immunopathogenesis and have implications for studies of HIV transmission and evolution in vivo.

Journal ArticleDOI
TL;DR: Research is presented that links individual and broad-scale ecological and evolutionary processes to collective movement, and relates these concepts to emerging challenges for the management and conservation of animals on the move in a world that is increasingly impacted by human activity.
Abstract: Recent advances in technology and quantitative methods have led to the emergence of a new field of study that stands to link insights of researchers from two closely related, but often disconnected...

Journal ArticleDOI
TL;DR: The upper bounds show that for each of these problems there is a significant regime where reliable detection is information-theoretically possible but where known algorithms such as PCA fail completely, since the spectrum of the observed matrix is uninformative.
Abstract: We study the problem of detecting a structured, low-rank signal matrix corrupted with additive Gaussian noise. This includes clustering in a Gaussian mixture model, sparse PCA, and submatrix localization. Each of these problems is conjectured to exhibit a sharp information-theoretic threshold, below which the signal is too weak for any algorithm to detect. We derive upper and lower bounds on these thresholds by applying the first and second moment methods to the likelihood ratio between these “planted models” and null models where the signal matrix is zero. For sparse PCA and submatrix localization, we determine this threshold exactly in the limit where the number of blocks is large or the signal matrix is very sparse; for the clustering problem, our bounds differ by a factor of $\sqrt {2}$ when the number of clusters is large. Moreover, our upper bounds show that for each of these problems there is a significant regime where reliable detection is information-theoretically possible but where known algorithms such as PCA fail completely, since the spectrum of the observed matrix is uninformative. This regime is analogous to the conjectured “hard but detectable” regime for community detection in sparse graphs.

Journal ArticleDOI
TL;DR: In this article, the authors present an empirical analysis of heterosexual dating markets in four large U.S. cities using data from a popular, free online dating service, and find that both men and women pursue partners who are on average about 25% more desirable than themselves by their measures and that they use different messaging strategies with partners of different desirability.
Abstract: Romantic courtship is often described as taking place in a dating market where men and women compete for mates, but the detailed structure and dynamics of dating markets have historically been difficult to quantify for lack of suitable data. In recent years, however, the advent and vigorous growth of the online dating industry has provided a rich new source of information on mate pursuit. We present an empirical analysis of heterosexual dating markets in four large U.S. cities using data from a popular, free online dating service. We show that competition for mates creates a pronounced hierarchy of desirability that correlates strongly with user demographics and is remarkably consistent across cities. We find that both men and women pursue partners who are on average about 25% more desirable than themselves by our measures and that they use different messaging strategies with partners of different desirability. We also find that the probability of receiving a response to an advance drops markedly with increasing difference in desirability between the pursuer and the pursued. Strategic behaviors can improve one’s chances of attracting a more desirable mate, although the effects are modest.

Journal ArticleDOI
TL;DR: This work demonstrates that the mutation rate changes the global balance between deleterious and beneficial mutational effects on fitness, and suggests that this tipping point already occurs at the modest mutation rates that are found in the wild.
Abstract: Mutation is fundamental to evolution, because it generates the genetic variation on which selection can act. In nature, genetic changes often increase the mutation rate in systems that range from viruses and bacteria to human tumors. Such an increase promotes the accumulation of frequent deleterious or neutral alleles, but it can also increase the chances that a population acquires rare beneficial alleles. Here, we study how up to 100-fold increases in Escherichia coli’s genomic mutation rate affect adaptive evolution. To do so, we evolved multiple replicate populations of asexual E. coli strains engineered to have four different mutation rates for 3000 generations in the laboratory. We measured the ability of evolved populations to grow in their original environment and in more than 90 novel chemical environments. In addition, we subjected the populations to whole genome population sequencing. Although populations with higher mutation rates accumulated greater genetic diversity, this diversity conveyed benefits only for modestly increased mutation rates, where populations adapted faster and also thrived better than their ancestors in some novel environments. In contrast, some populations at the highest mutation rates showed reduced adaptation during evolution, and failed to thrive in all of the 90 alternative environments. In addition, they experienced a dramatic decrease in mutation rate. Our work demonstrates that the mutation rate changes the global balance between deleterious and beneficial mutational effects on fitness. In contrast to most theoretical models, our experiments suggest that this tipping point already occurs at the modest mutation rates that are found in the wild.

Journal ArticleDOI
TL;DR: It is shown that nestedness and other features of mutualistic webs are spandrels resulting from the creation of diversity through speciation-divergence dynamics, and the agreement between observed and modelled networks suggests that the patterns displayed by real mutualism webs might actually represent evolutionary spand Rels.
Abstract: Mutualistic networks have been shown to involve complex patterns of interactions among animal and plant species, including a widespread presence of nestedness. The nested structure of these webs seems to be positively correlated with higher diversity and resilience. Moreover, these webs exhibit marked measurable structural patterns, including broad distributions of connectivity, strongly asymmetrical interactions and hierarchical organization. Hierarchical organization is an especially interesting property, since it is positively correlated with biodiversity and network resilience, thus suggesting potential selection processes favouring the observed web organization. However, here we show that all these structural quantitative patterns-and nestedness in particular-can be properly explained by means of a very simple dynamical model of speciation and divergence with no selection-driven coevolution of traits. The agreement between observed and modelled networks suggests that the patterns displayed by real mutualistic webs might actually represent evolutionary spandrels.

Journal ArticleDOI
TL;DR: It is shown that it is possible to diagnose systematically the central physical problem of slums using a topological analysis of neighborhood maps and resolved by finding solutions to a sequence of constrained optimization problems.
Abstract: The world is urbanizing quickly with nearly 4 billion people presently living in urban areas, about 1 billion of them in slums. Achieving sustainable development from rapid urbanization relies critically on creating cities without slums. We show that it is possible to diagnose systematically the central physical problem of slums—the lack of spatial accesses and related services—using a topological analysis of neighborhood maps and resolved by finding solutions to a sequence of constrained optimization problems. We set up the problem by showing that the built environment of any city can be decomposed into two types of networked spaces—accesses and places—and prove that these spaces display universal topological characteristics. We then show that while the neighborhoods of developed cities express the same common topology, urban slums fall into a different topological class. We demonstrate that it is always possible to find solutions that grow a street network in existing slums, providing universal accesses at minimal disruption and cost. We then show how elaborations of this procedure that include local preferences and reduce travel distances between places result from additional access construction. These methods are presently taking effect in neighborhoods in Cape Town (South Africa) and Mumbai (India), demonstrating their practical feasibility and emphasizing their role as a platform to enable communities and local governments to combine technical knowledge with local aspirations into contextually appropriate urban sustainable development solutions.

Journal ArticleDOI
TL;DR: In this article, the role of population abundances on the stability of large communities is investigated. But the authors focus on the spectrum of a large community matrix for arbitrary feasible species abundance distributions.
Abstract: Random matrix theory successfully connects the structure of interactions of large ecological communities to their ability to respond to perturbations. One of the most debated aspects of this approach is that so far studies have neglected the role of population abundances on stability. While species abundances are well studied and empirically accessible, studies on stability have so far failed to incorporate this information. Here we tackle this question by explicitly including population abundances in a random matrix framework. We derive an analytical formula that describes the spectrum of a large community matrix for arbitrary feasible species abundance distributions. The emerging picture is remarkably simple: while population abundances affect the rate to return to equilibrium after a perturbation, the stability of large ecosystems is uniquely determined by the interaction matrix. We confirm this result by showing that the likelihood of having a feasible and unstable solution in the Lotka-Volterra system of equations decreases exponentially with the number of species for stable interaction matrices.

Journal ArticleDOI
TL;DR: The authors' experimental and simulation-based results indicate that dust contains living bacterial taxa that can be inactivated following changes in local abiotic conditions and suggest that the bactericidal potential of ordinary window-filtered sunlight may be similar to ultraviolet wavelengths across dosages that are relevant to real buildings.
Abstract: Microbial communities associated with indoor dust abound in the built environment. The transmission of sunlight through windows is a key building design consideration, but the effects of light exposure on dust communities remain unclear. We report results of an experiment and computational models designed to assess the effects of light exposure and wavelengths on the structure of the dust microbiome. Specifically, we placed household dust in replicate model “rooms” with windows that transmitted visible, ultraviolet, or no light and measured taxonomic compositions, absolute abundances, and viabilities of the resulting bacterial communities. Light exposure per se led to lower abundances of viable bacteria and communities that were compositionally distinct from dark rooms, suggesting preferential inactivation of some microbes over others under daylighting conditions. Differences between communities experiencing visible and ultraviolet light wavelengths were relatively minor, manifesting primarily in abundances of dead human-derived taxa. Daylighting was associated with the loss of a few numerically dominant groups of related microorganisms and apparent increases in the abundances of some rare groups, suggesting that a small number of microorganisms may have exhibited modest population growth under lighting conditions. Although biological processes like population growth on dust could have generated these patterns, we also present an alternate statistical explanation using sampling models from ecology; simulations indicate that artefactual, apparent increases in the abundances of very rare taxa may be a null expectation following the selective inactivation of dominant microorganisms in a community. Our experimental and simulation-based results indicate that dust contains living bacterial taxa that can be inactivated following changes in local abiotic conditions and suggest that the bactericidal potential of ordinary window-filtered sunlight may be similar to ultraviolet wavelengths across dosages that are relevant to real buildings.

Journal ArticleDOI
03 Sep 2018
TL;DR: Higher-order interactions among antibiotics are prevalent and also that there are systematic patterns in how they occur: the frequency of higher- order interactions increases with the number of components, net interactions tend to be more synergistic, and emergent interactions—arising at specific higher-order levels—tend toward antagonism.
Abstract: Interactions and emergent processes are essential for research on complex systems involving many components. Most studies focus solely on pairwise interactions and ignore higher-order interactions among three or more components. To gain deeper insights into higher-order interactions and complex environments, we study antibiotic combinations applied to pathogenic Escherichia coli and obtain unprecedented amounts of detailed data (251 two-drug combinations, 1512 three-drug combinations, 5670 four-drug combinations, and 13608 five-drug combinations). Directly opposite to previous assumptions and reports, we find higher-order interactions increase in frequency with the number of drugs in the bacteria's environment. Specifically, as more drugs are added, we observe an elevated frequency of net synergy (effect greater than expected based on independent individual effects) and also increased instances of emergent antagonism (effect less than expected based on lower-order interaction effects). These findings have implications for the potential efficacy of drug combinations and are crucial for better navigating problems associated with the combinatorial complexity of multi-component systems.

Journal ArticleDOI
TL;DR: In this paper, the authors apply the nowcast approach to the practical development of methods to estimate the current state of risk for dozens of the world's seismically exposed megacities, defined as cities having populations of over 1.
Abstract: Natural Time (“NT”) refers to the concept of using small earthquake counts, for example of M > 3 events, to mark the intervals between large earthquakes, for example M > 6 events. The term was first used by Varotsos et al. (2005) and later by Holliday et al. (2006) in their studies of earthquakes. In this paper, we discuss ideas and applications arising from the use of NT to understand earthquake dynamics, in particular by use of the idea of nowcasting. Nowcasting differs from forecasting, in that the goal of nowcasting is to estimate the current state of the system, rather than the probability of a future event. Rather than focus on an individual earthquake faults, we focus on a defined local geographic region surrounding a particular location. This local region is considered to be embedded in a larger regional setting from which we accumulate the relevant statistics. We apply the nowcasting idea to the practical development of methods to estimate the current state of risk for dozens of the world’s seismically exposed megacities, defined as cities having populations of over 1 million persons. We compute a ranking of these cities based on their current nowcast value, and discuss the advantages and limitations of this approach. We note explicitly that the nowcast method is not a model, in that there are no free parameters to be fit to data. Rather, the method is simply a presentation of statistical data, which the user can interpret. Among other results, we find, for example, that the current nowcast ranking of the Los Angeles region is comparable to its ranking just prior to the January 17, 1994 Northridge earthquake.