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Complexity Global School | Santa Fe Institute

Mon, 02/26/2024 - 16:52

Application for the second Complexity Global School – to be hosted simultaneously at Universidad de los Andes, Colombia, and Santa Fe Institute, USA from July 21 to August 3 – is now open. Applicants based in Latin America and the Caribbean are eligible for the Colombia location, and applicants based in USA, Canada, and western Europe are eligible for the USA location. Supported by the Omidyar Network, the school is free for all admitted students, inclusive of tuition, room, board, and travel stipend.

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APS/ICTP-SAIFR Satellite March Meeting, Session on Complex Systems

Tue, 02/20/2024 - 16:10

To extend the reach and diversity of its annual meetings, the American Physical Society has developed a pilot program of APS Satellite Meetings with the participation of ICTP-SAIFR in Latin America. As part of the APS March Meeting from March 3-8, 2024, ICTP-SAIFR is organizing on March 5 (Tuesday) a 2-hour Satellite Session on Complex Systems that will be broadcast live to all participants of the APS March Meeting, as well as a session on Complex Systems for student/postdoc presentations.

Graduate students and postdocs can apply until February 10, 2024 to give oral presentations or posters at the student-postdoc session on complex systems.

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Faster is Slower effect for evacuation processes: a granular standpoint

Tue, 02/20/2024 - 14:03

F. Al Reda, S. Faure, B. Maury, E. Pinsard

Journal of Computational Physics

• Numerical investigation of the Faster is Slower effect based on a parameter free model.

• Integration of an inhibition tendency of polite pedestrians.

• Numerical evidence of the fluidizing role of an obstacle upstream the exit during evacuation.

• Numerical recovering of an experimental power law for time lapses.

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Call for organization: Conference Complex Systems (CCS 2025)

Mon, 02/19/2024 - 07:37

The Complex Systems Society (CSS) organizes every year a main conference (CCS) – the most important annual meeting for the complex systems research community.

The Complex Systems Society invites bids to host the edition for 2025.

The conference is generally held in September/October of each year.

Interested potential organizers should send a short document (6 pages max.) detailing the proposal to the Society account (please add and in cc).

The last edition was in Salvador, Brasil (CCS2023). The next one will be in Exeter/London, UK (CCS2024).

The CCS series in recent years alternates between Europe, Asia and the Americas. In the edition 2025, preference will be given to bids from outside Europe in this edition even though bids from other locations will be also considered.

The deadline for proposals submission is April 30, 2024

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Self-organization as a mechanism of resilience in dryland ecosystems

Sun, 02/11/2024 - 15:41

Sonia Kéfi, Alexandre Génin, Angeles Garcia-Mayor, Emilio Guirado, Juliano S. Cabral, Miguel Berdugo, Josquin Guerber, Ricard Solé, and Fernando T. Maestre

The spatial structure of vegetation in dryland ecosystems has long fascinated scientists due to its striking appearance. Through a combination of global field surveys, mathematical models, and remote sensing, we show that the mechanisms responsible for these patterns enable healthy dryland ecosystems to adapt to changing environmental conditions, including water shortages, by adjusting their spatial structure. Conversely, degraded ecosystems do not have this ability. Our findings underscore the critical role of spatial pattern formation in promoting resilience in dryland ecosystems. Moreover, these spatial patterns could serve as valuable indicators of ecosystem health under a changing climate, opening important perspectives for future research in this field.

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SARS-CoV-2 and COVID-19: From Crisis to Solution

Sat, 02/10/2024 - 13:54

Špela Šalamon Andrew Ewing Greta Fox Stephane Bilodeau Carlos Gershenson Matti TJ Heino Yaneer Bar-Yam

WHN Science Communications 2024; 5 (1): 1-1.

The global impact of the COVID-19 pandemic persists, causing significant harm. Extensive evidence indicates that even mild infections and reinfections can result in symptomatic and subclinical health damage, disability, and persistent infection. Vascular impacts, neurotropism, and immune dysregulation lead to impaired organ function, increased morbidity and mortality, compromised work productivity, and a decline in overall health and quality of life. The uncontrolled spread of the virus is accelerating its evolution, outpacing the effectiveness of vaccines, treatments, and immune system adaptation. This preventable disease and others magnified by immune dysfunction are driving staff shortages, supply chain disruptions, and overwhelming healthcare systems. Despite the dire nature of the current conditions, knowledge and means are present to solve these problems. We present a science-based strategy for confronting the ongoing pandemic, including reducing airborne transmission through clean indoor air programs comparable with historical clean water programs. Public and professional education on the implications of repeated SARS-CoV-2 infections and utilizing known preventive measures can dramatically reduce transmission, which in turn reduces the rate of new variant introduction and strengthens the effectiveness of vaccines and treatments. It is essential to restore the prioritization of health and safety in healthcare and society.

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Self-Reproduction and Evolution in Cellular Automata: 25 Years after Evoloops

Fri, 02/09/2024 - 15:39

Hiroki Sayama, Chrystopher L. Nehaniv

The year of 2024 marks the 25th anniversary of the publication of evoloops, an evolutionary variant of Chris Langton’s self-reproducing loops which proved that Darwinian evolution of self-reproducing organisms by variation and natural selection is possible within deterministic cellular automata. Over the last few decades, this line of Artificial Life research has since undergone several important developments. Although it experienced a relative dormancy of activities for a while, the recent rise of interest in open-ended evolution and the success of continuous cellular automata models have brought researchers’ attention back to how to make spatio-temporal patterns self-reproduce and evolve within spatially distributed computational media. This article provides a review of the relevant literature on this topic over the past 25 years and highlights the major accomplishments made so far, the challenges being faced, and promising future research directions.

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Landauer Bound and Continuous Phase Transitions

Thu, 02/08/2024 - 15:46

Maria Cristina Diamantini

Entropy 2023, 25(7), 984

In this review, we establish a relation between information erasure and continuous phase transitions. The order parameter, which characterizes these transitions, measures the order of the systems. It varies between 0, when the system is completely disordered, and 1, when the system is completely ordered. This ordering process can be seen as information erasure by resetting a certain number of bits to a standard value. The thermodynamic entropy in the partially ordered phase is given by the information-theoretic expression for the generalized Landauer bound in terms of error probability. We will demonstrate this for the Hopfield neural network model of associative memory, where the Landauer bound sets a lower limit for the work associated with ‘remembering’ rather than ‘forgetting’. Using the relation between the Landauer bound and continuous phase transition, we will be able to extend the bound to analog computing systems. In the case of the erasure of an analog variable, the entropy production per degree of freedom is given by the logarithm of the configurational volume measured in units of its minimal quantum.

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The Fragile Nature of Road Transportation Systems

Thu, 02/08/2024 - 14:08

Linghang Sun, Yifan Zhang, Cristian Axenie, Margherita Grossi, Anastasios Kouvelas, Michail A. Makridis

Major cities worldwide experience problems with the performance of their road transportation systems. The continuous increase in traffic demand presents a substantial challenge to the optimal operation of urban road networks and the efficiency of traffic control strategies. Although robust and resilient transportation systems have been extensively researched over the past decades, their performance under an ever-growing traffic demand can still be questionable. The operation of transportation systems is widely believed to display fragile property, i.e., the loss in performance increases exponentially with the linearly increasing magnitude of disruptions, which undermines their continuous operation. The risk engineering community is now embracing the novel concept of (anti-)fragility, which enables systems to learn from historical disruptions and exhibit improved performance as disruption levels reach unprecedented magnitudes. In this study, we demonstrate the fragile nature of road transportation systems when faced with either demand or supply disruptions. First, we conducted a rigorous mathematical analysis to theoretically establish the fragile nature of the systems. Subsequently, by taking into account real-world stochasticity, we implemented a numerical simulation with realistic network data to bridge the gap between the theoretical proof and the real-world operations, to study the impact of uncertainty on the fragile property of the systems. This work aims to help researchers better comprehend the necessity to explicitly consider antifragile design toward the application of future traffic control strategies, coping with constantly growing traffic demand and subsequent traffic accidents.

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Lessons from Life Itself: Relational Models of Complexity and Self-Organization on

Wed, 02/07/2024 - 16:27

Binghamton Center of Complex Systems (CoCo) Seminar February 7, 2024 Pedro Márquez-Zacarías (Santa Fe Institute) 

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What can physics tell us about ourselves?

Wed, 02/07/2024 - 09:23

Humans can live up to age 100, and not 1000 – why? Are there limits in how much our brains can think and compute? The laws of physics can help explain a lot, both about our own human bodies and how we are connected to life all around us.

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A Random Boolean Network shifted toward a critical point

Tue, 02/06/2024 - 14:47

Tomoko Sakiyama

Physica Scripta

Random Boolean Networks (RBNs) model complex networks with numerous variables, serving as a tool for gene expression and genetic regulation modeling. RBNs exhibit phase transitions, contingent on node degrees. Given the significance of phase transitions in collective behaviors, the study explores the relationship between RBNs and actual living system networks, which also display critical behaviors. Notably, living systems exhibit such behaviors even beyond the predicted critical point in RBNs. This paper introduces a novel RBNs model incorporating a rewiring process for edge connections/disconnections. In contrast to prior studies, our model includes artificial genes occasionally adding self-loops and creating an instant and temporal lookup table. Consequently, our proposed model demonstrates the edge of chaos at higher node degrees. It serves as an abstract RBNs model generating noisy behaviors from internal agent processes without external parameter tuning.

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Calls for the 2024 CSS Emerging Researcher, Junior, and Senior Scientific Awards

Mon, 02/05/2024 - 15:21

The Complex Systems Society announces the ninth edition of the CSS Scientific Awards. 

The Emerging Researcher Award recognizes promising researchers in Complex Systems within 3 years of the PhD defense.

The Junior Scientific Award is aimed at recognizing excellent scientific record of young researchers within 10 years of the PhD defense.

The Senior Scientific Award will recognize outstanding contributions of Complex Systems scholars at whatever stage of their careers.

Deadline: April 30th, 2024.

See for the list of previous awardees.

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Lake Como School on Computational Social Science: Advances, Challenges and Opportunities

Mon, 02/05/2024 - 11:46

May 13-17, 2024 Villa del Grumello, Como, Italy

Over the past decade, computational social science (CSS) has risen as an interdisciplinary field that combines methods and theories from computer science, statistics, and social sciences to study complex social phenomena using computational tools and techniques. 

By leveraging the power of computing and data, computational social scientists aim to uncover patterns and trends in complex social systems that may be difficult or impossible to discern through traditional research methods. 

Topics of interest include social networks, online communities, opinion dynamics, and collective decision-making, among others. Computational social science has become increasingly important as our world becomes more digitised, and its insights have significant implications for fields such as public policy, marketing, and sociology.

The First edition of the school Computational Social Science: Advances, Challenges and Opportunities is designed to provide an intensive and immersive learning experience for graduate students, postdoctoral researchers, and early career faculty interested in utilising computational methods to study social phenomena. 

The school will be open to 45 selected students. Application deadline: February 25th, 2024

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