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Terrorist Group Cooperation and Longevity

Why do some terrorist groups survive considerably longer than others? The literature is just beginning to address this important question in a systematic manner. Additionally, and as with most studies of terrorism, longevity studies have ignored the possibility of interactions between terrorist groups. This article attempts to address these two gaps in the literature: the incomplete understanding of terrorist group survival and the tendency to assume that terrorist groups act independently. In spite of risks associated with cooperation, I argue that it should help involved terrorist groups mitigate mobilization concerns. More importantly, the impact of cooperation is conditioned by attributes of the country in which a terrorist group operates. Using new global data on terrorist groups between 1987 and 2005, I show that cooperation has the strongest effect on longevity in states where groups should have a harder time operating—more capable states and less democratic states. Interestingly, a group's number of relationships is more important than to whom the group is connected.


Phillips, Brian J. "Terrorist Group Cooperation and Longevity." International Studies Quarterly (2013).

http://dx.doi.org/10.1111/isqu.12073

Paras Pandya's curator insight, July 7, 2015 8:14 AM

Interesting perspective and example of scientific approach and usage of global data. We will see more and more real world evidences and observational data being used in international relations and politics studies and research.

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Emergence in artificial life

Carlos Gershenson
Concepts similar to emergence have been used since antiquity, but we lack an agreed definition of emergence. Still, emergence has been identified as one of the features of complex systems. Most would agree on the statement "life is complex". Thus, understanding emergence and complexity should benefit the study of living systems. It can be said that life emerges from the interactions of complex molecules. But how useful is this to understand living systems? Artificial life (ALife) has been developed in recent decades to study life using a synthetic approach: build it to understand it. ALife systems are not so complex, be them soft (simulations), hard (robots), or wet (protocells). Then, we can aim at first understanding emergence in ALife, for then using this knowledge in biology. I argue that to understand emergence and life, it becomes useful to use information as a framework. In a general sense, emergence can be defined as information that is not present at one scale but is present at another scale. This perspective avoids problems of studying emergence from a materialistic framework, and can be useful to study self-organization and complexity.

Read the full article at: arxiv.org

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Network medicine framework for identifying drug-repurposing opportunities for COVID-19 | PNAS

Deisy Morselli Gysi, Ítalo do Valle, Marinka Zitnik, Asher Ameli, Xiao Gan, Onur Varol, Susan Dina Ghiassian, J. J. Patten, Robert A. Davey, Joseph Loscalzo, and Albert-László Barabási

PNAS May 11, 2021 118 (19) e2025581118;

The COVID-19 pandemic has highlighted the importance of prioritizing approved drugs to treat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Here, we deployed algorithms relying on artificial intelligence, network diffusion, and network proximity to rank 6,340 drugs for their expected efficacy against SARS-CoV-2. We experimentally screened 918 drugs, allowing us to evaluate the performance of the existing drug-repurposing methodologies, and used a consensus algorithm to increase the accuracy of the predictions. Finally, we screened in human cells the top-ranked drugs, identifying six drugs that reduced viral infection, four of which could be repurposed to treat COVID-19. The developed strategy has significance beyond COVID-19, allowing us to identify drug-repurposing candidates for neglected diseases.

Read the full article at: www.pnas.org

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Suzanne Simard interview: How I uncovered the hidden language of trees

First she discovered the wood wide web. Now Suzanne Simard has found that underground connections in a forest are like a brain that allows trees to form societies – and look out for their kin

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Distributions of historic market data: relaxation and correlations

M. Dashti Moghaddam, Zhiyuan Liu & R. A. Serota 
The European Physical Journal B volume 94, Article number: 83 (2021)

We investigate relaxation and correlations in a class of mean-reverting models for stochastic variances. We derive closed-form expressions for the correlation functions and leverage for a general form of the stochastic term. We also discuss correlation functions and leverage for three specific models— multiplicative, Heston (Cox-Ingersoll-Ross) and combined multiplicative-Heston—whose steady-state probability density functions are Gamma, Inverse Gamma and Beta Prime respectively, the latter two exhibiting “fat” tails. For the Heston model, we apply the eigenvalue analysis of the Fokker-Planck equation to derive the correlation function—in agreement with the general analysis— and to identify a series of time scales, which are observable in relaxation of cumulants on approach to the steady state. We test our findings on a very large set of historic financial markets data.

Read the full article at: link.springer.com

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SARS-CoV-2 elimination, not mitigation, creates best outcomes for health, the economy, and civil liberties

Miquel Oliu-Barton, Bary S R Pradelski, Philippe Aghion, Patrick Artus, Ilona Kickbusch, Jeffrey V Lazarus, Devi Sridhar, Samantha Vanderslott

The Lancet

The trade-off between different objectives is at the heart of political decision making. Public health, economic growth, democratic solidarity, and civil liberties are important factors when evaluating pandemic responses. There is mounting evidence that these objectives do not need to be in conflict in the COVID-19 response. Countries that consistently aim for elimination—ie, maximum action to control SARS-CoV-2 and stop community transmission as quickly as possible—have generally fared better than countries that opt for mitigation—ie, action increased in a stepwise, targeted way to reduce cases so as not to overwhelm health-care systems.

Read the full article at: www.sciencedirect.com

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Identifying tax evasion in Mexico with tools from network science and machine learning

Martin Zumaya, Rita Guerrero, Eduardo Islas, Omar Pineda, Carlos Gershenson, Gerardo Iñiguez, Carlos Pineda

Mexico has kept electronic records of all taxable transactions since 2014. Anonymized data collected by the Mexican federal government comprises more than 80 million contributors (individuals and companies) and almost 7 billion monthly-aggregations of invoices among contributors between January 2015 and December 2018. This data includes a list of almost ten thousand contributors already identified as tax evaders, due to their activities fabricating invoices for non-existing products or services so that recipients can evade taxes. Harnessing this extensive dataset, we build monthly and yearly temporal networks where nodes are contributors and directed links are invoices produced in a given time slice. Exploring the properties of the network neighborhoods around tax evaders, we show that their interaction patterns differ from those of the majority of contributors. In particular, invoicing loops between tax evaders and their clients are over-represented. With this insight, we use two machine-learning methods to classify other contributors as suspects of tax evasion: deep neural networks and random forests. We train each method with a portion of the tax evader list and test it with the rest, obtaining more than 0.9 accuracy with both methods. By using the complete dataset of contributors, each method classifies more than 100 thousand suspects of tax evasion, with more than 40 thousand suspects classified by both methods. We further reduce the number of suspects by focusing on those with a short network distance from known tax evaders. We thus obtain a list of highly suspicious contributors sorted by the amount of evaded tax, valuable information for the authorities to further investigate illegal tax activity in Mexico. With our methods, we estimate previously undetected tax evasion in the order of $10 billion USD per year by about 10 thousand contributors.

Read the full article at: arxiv.org

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Misinformation about science in the public sphere

Misinformation about science in the public sphere | Papers | Scoop.it

Dietram A. Scheufele, Andrew J. Hoffman, Liz Neeley, and Czerne M. Reid

PNAS April 13, 2021 118 (15) e2104068118

The misinformation crisis exemplified and intensified by the COVID-19 pandemic lays a gauntlet at the door of all science communicators. Scholars, experts, educators, activists, organizers, public servants, and philanthropists share an obligation to engage in “difficult, broad-based negotiation of moral, financial, and other societal trade-offs alongside a collective investigation of scientific potential” (18). In the end, it is our hope that this colloquium issue will stimulate deeper explorations of the causes and cures for misinformation, conducted in closer collaborations among researchers and practitioners.

Read the full article at: www.pnas.org

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How Maxwell’s Demon Continues to Startle Scientists

How Maxwell’s Demon Continues to Startle Scientists | Papers | Scoop.it

The thorny thought experiment has been turned into a real experiment — one that physicists use to probe the physics of information.

Read the full article at: www.quantamagazine.org

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Time to regulate AI that interprets human emotions

Time to regulate AI that interprets human emotions | Papers | Scoop.it

The pandemic is being used as a pretext to push unproven artificial-intelligence tools into workplaces and schools.

Read the full article at: www.nature.com

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Modeling COVID-19 for Lifting Non-Pharmaceutical Interventions

Modeling COVID-19 for Lifting Non-Pharmaceutical Interventions | Papers | Scoop.it

Matthew Koehler, David M Slater, Garry Jacyna and James R Thompson

Journal of Artificial Societies and Social Simulation 24 (2) 9

As a result of the COVID-19 worldwide pandemic, the United States instituted various non-pharmaceutical interventions (NPIs) in an effort to slow the spread of the disease. Although necessary for public safety, these NPIs can also have deleterious effects on the economy of a nation. State and federal leaders need tools that provide insight into which combination of NPIs will have the greatest impact on slowing the disease and at what point in time it is reasonably safe to start lifting these restrictions to everyday life. In the present work, we outline a modeling process that incorporates the parameters of the disease, the effects of NPIs, and the characteristics of individual communities to offer insight into when and to what degree certain NPIs should be instituted or lifted based on the progression of a given outbreak of COVID-19. We apply the model to the 24 county-equivalents of Maryland and illustrate that different NPI strategies can be employed in different parts of the state. Our objective is to outline a modeling process that combines the critical disease factors and factors relevant to decision-makers who must balance the health of the population with the health of the economy.

Read the full article at: jasss.soc.surrey.ac.uk

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Avoiding the bullies: The resilience of cooperation among unequals

Avoiding the bullies: The resilience of cooperation among unequals | Papers | Scoop.it

Foley M, Smead R, Forber P, Riedl C (2021) Avoiding the bullies: The resilience of cooperation among unequals. PLoS Comput Biol 17(4): e1008847.

Individuals often differ in their ability to resolve conflicts in their favor, and this can lead to the emergence of hierarchies and dominant alphas. Such social structures present a serious risk of destabilizing cooperative social interactions or norms. Why work together to find food when a more aggressive or stronger individual can take all of it? In this paper we use game theory and agent-based modeling to investigate how cooperative behavior evolves in the presence of powerful bullies who have no incentive to cooperate. We show that when individuals can choose their interaction partners, bullies do not always destabilize cooperation. Instead, cooperative norms survive as individuals learn to avoid dominant individuals who become isolated in the population. When competitive ability itself depends dynamically on past success, complex cycles of coupled network-strategy-rank changes emerge: effective collaborators gain popularity and thus power, adopt aggressive behavior, get isolated, then lose power. Our results have important implications: in our modeled scenario the rich do not always get richer, the dominance of bullies can be broken, and inequality in accrued resources can be eliminated. Thus, our work provides new insight into potential sources of, and strategies for avoiding, resource inequality.

Read the full article at: journals.plos.org

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Emergence of Polarized Ideological Opinions in Multidimensional Topic Spaces

Emergence of Polarized Ideological Opinions in Multidimensional Topic Spaces | Papers | Scoop.it

Fabian Baumann, Philipp Lorenz-Spreen, Igor M. Sokolov, and Michele Starnini
Phys. Rev. X 11, 011012 (2021)

By embedding opinions in a nonorthogonal topic space, a new model shows that a reinforcement mechanism driven by homophilic social interactions reproduces extreme and correlated opinion states found in surveys.

Read the full article at: link.aps.org

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The global network of ports supporting high seas fishing | Science Advances

The global network of ports supporting high seas fishing | Science Advances | Papers | Scoop.it

Jorge P. Rodríguez, Juan Fernández-Gracia, Carlos M. Duarte, Xabier Irigoien, and Víctor M. Eguíluz

Science Advances 26 Feb 2021:
Vol. 7, no. 9, eabe3470

Fisheries in waters beyond national jurisdiction (“high seas”) are difficult to monitor and manage. Their regulation for sustainability requires critical information on how fishing effort is distributed across fishing and landing areas, including possible border effects at the exclusive economic zone (EEZ) limits. We infer the global network linking harbors supporting fishing vessels to fishing areas in high seas from automatic identification system tracking data in 2014, observing a modular structure, with vessels departing from a given harbor fishing mostly in a single province. The top 16% of these harbors support 84% of fishing effort in high seas, with harbors in low- and middle-income countries ranked among the top supporters. Fishing effort concentrates along narrow strips attached to the boundaries of EEZs with productive fisheries, identifying a free-riding behavior that jeopardizes efforts by nations to sustainably manage their fisheries, perpetuating the tragedy of the commons affecting global fishery resources.


Read the full article at: advances.sciencemag.org

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Perverse Downstream Consequences of Debunking: Being Corrected by Another User for Posting False Political News Increases Subsequent Sharing of Low Quality, Partisan, and Toxic Content in a Twitter...

Perverse Downstream Consequences of Debunking: Being Corrected by Another User for Posting False Political News Increases Subsequent Sharing of Low Quality, Partisan, and Toxic Content in a Twitter... | Papers | Scoop.it

Mohsen Mosleh, Cameron Martel, Dean Eckles, David Rand

A prominent approach to combating online misinformation is to debunk false content. Here we investigate downstream consequences of social corrections on users’ subsequent sharing of other content. Being corrected might make users more attentive to accuracy, thus improving their subsequent sharing. Alternatively, corrections might not improve subsequent sharing - or even backfire - by making users feel defensive, or by shifting their attention away from accuracy (e.g., towards various social factors). We identified N=2,000 users who shared false political news on Twitter, and replied to their false tweets with links to fact-checking websites. We find causal evidence that being corrected decreases the quality, and increases the partisan slant and language toxicity, of the users’ subsequent retweets (but has no significant effect on primary tweets). This suggests that being publicly corrected by another user shifts one's attention away from accuracy - presenting an important challenge for social correction approaches.

https://dl.acm.org/doi/10.1145/3411764.3445642

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The Fail West - Uncharted Territories

The Fail West - Uncharted Territories | Papers | Scoop.it

Soon, over 1.5 million people will have died of COVID in Western countries.
1.5 million futile, needless deaths. 1.5 million wasted lives.
Meanwhile, in a block of Asia-Pacific countries with a population over twice as big, they lost 18,000 people. 

(...)

Within 1-2 months, we knew most of the crucial knowledge needed to control the epidemic. Governments must reckon with their incapacity to apply these learnings.


Read the full article at: unchartedterritories.substack.com

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Technology & Society: social, philosophical and ethical implications for the 21st century

Francis Heylighen

This richly illustrated manuscript including an extensive bibliography forms the lecture notes of a course with the same title. This course tries to give the students a deeper insight into what technology is, and how it affects human life on this planet. Given how pervasive and dominant technological systems have become in this 21st century, it is important to understand the dynamics that propel its ever-faster development. It is especially important to understand, on the one hand, the negative effects and dangers of this development, so that we can mitigate or evade those, on the other hand, the benefits and promises, so that we can further promote and enhance them. These issues are reviewed from a systems/cybernetics perspective. The focus is on accelerating evolution, technology as mediator and human-technology symbiosis, leading up to the notion of a global superorganism.

Read the full article at: researchportal.vub.be

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Transformative climate adaptation in the United States: Trends and prospects

Linda Shi and Susanne Moser

Science 29 Apr 2021: eabc8054
As climate change intensifies, civil society is increasingly calling for transformative adaptation that redresses drivers of climate vulnerability. We review trends in how U.S. federal government, private industry and civil society are planning for climate adaptation. We find growing divergence in their approaches and impacts. This incoherence increases maladaptive investment in climate-blind infrastructure, justice-blind reforms in financial and professional sectors, and greater societal vulnerability to climate impacts. If these actors were to proactively and deliberatively engage in transformative adaptation, they would need to address the material, relational and normative factors that hold current systems in place. Drawing on a review of transformation and collective impact literatures, we conclude with directions for research and policy engagement to support more transformative adaptation moving forward.

Read the full article at: science.sciencemag.org

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Universal dynamics of ranking

Gerardo Iñiguez, Carlos Pineda, Carlos Gershenson, Albert-László Barabási
Virtually anything can be and is ranked; people and animals, universities and countries, words and genes. Rankings reduce the components of highly complex systems into ordered lists, aiming to capture the fitness or ability of each element to perform relevant functions, and are being used from socioeconomic policy to knowledge extraction. A century of research has found regularities in ranking lists across nature and society when data is aggregated over time. Far less is known, however, about ranking dynamics, when the elements change their rank in time. To bridge this gap, here we explore the dynamics of 30 ranking lists in natural, social, economic, and infrastructural systems, comprising millions of elements, whose temporal scales span from minutes to centuries. We find that the flux governing the arrival of new elements into a ranking list reveals systems with identifiable patterns of stability: in high-flux systems only the top of the list is stable, while in low-flux systems the top and bottom are equally stable. We show that two basic mechanisms - displacement and replacement of elements - are sufficient to understand and quantify ranking dynamics. The model uncovers two regimes in the dynamics of ranking lists: a fast regime dominated by long-range rank changes, and a slow regime driven by diffusion. Our results indicate that the balance between robustness and adaptability characterizing the dynamics of complex systems might be governed by random processes irrespective of the details of each system.

Read the full article at: arxiv.org

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Synchronizing Chaos with Imperfections

Yoshiki Sugitani, Yuanzhao Zhang, and Adilson E. Motter
Phys. Rev. Lett. 126, 164101

Previous research on nonlinear oscillator networks has shown that chaos synchronization is attainable for identical oscillators but deteriorates in the presence of parameter mismatches. Here, we identify regimes for which the opposite occurs and show that oscillator heterogeneity can synchronize chaos for conditions under which identical oscillators cannot. This effect is not limited to small mismatches and is observed for random oscillator heterogeneity on both homogeneous and heterogeneous network structures. The results are demonstrated experimentally using networks of Chua’s oscillators and are further supported by numerical simulations and theoretical analysis. In particular, we propose a general mechanism based on heterogeneity-induced mode mixing that provides insights into the observed phenomenon. Since individual differences are ubiquitous and often unavoidable in real systems, it follows that such imperfections can be an unexpected source of synchronization stability.

Read the full article at: link.aps.org

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Growth, death, and resource competition in sessile organisms

Edward D. Lee, Christopher P. Kempes, and Geoffrey B. West

PNAS April 13, 2021 118 (15) e2020424118

Although termite mounds stand out as an example of remarkably regular patterns emerging over long times from local interactions, ecological spatial patterns range from regular to random, and temporal patterns range from transient to stable. We propose a minimal quantitative framework to unify this variety by accounting for how quickly sessile organisms grow and die mediated by competition for fluctuating resources. Building on metabolic scaling theory for forests, we reproduce a wide range of spatial patterns and predict transient features such as population shock waves that align with observations. By connecting diverse ecological dynamics, our work will help apply lessons from model systems more broadly (e.g., by leveraging remote mapping to infer local ecological conditions).

Read the full article at: www.pnas.org

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Phase transitions and assortativity in models of gene regulatory networks evolved under different selection processes

Brandon Alexander , Alexandra Pushkar and Michelle Girvan

Journal of the Royal Society Interface Volume 18 Issue 177

We study a simplified model of gene regulatory network evolution in which links (regulatory interactions) are added via various selection rules that are based on the structural and dynamical features of the network nodes (genes). Similar to well-studied models of ‘explosive’ percolation, in our approach, links are selectively added so as to delay the transition to large-scale damage propagation, i.e. to make the network robust to small perturbations of gene states. We find that when selection depends only on structure, evolved networks are resistant to widespread damage propagation, even without knowledge of individual gene propensities for becoming ‘damaged’. We also observe that networks evolved to avoid damage propagation tend towards disassortativity (i.e. directed links preferentially connect high degree ‘source’ genes to low degree ‘target’ genes and vice versa). We compare our simulations to reconstructed gene regulatory networks for several different species, with genes and links added over evolutionary time, and we find a similar bias towards disassortativity in the reconstructed networks.

Read the full article at: royalsocietypublishing.org

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The COVID-19 Infodemic: Twitter versus Facebook

Kai-Cheng Yang, Francesco Pierri, Pik-Mai Hui, David Axelrod, Christopher Torres-Lugo, John Bryden, Filippo Menczer

The global spread of the novel coronavirus is affected by the spread of related misinformation -- the so-called COVID-19 Infodemic -- that makes populations more vulnerable to the disease through resistance to mitigation efforts. Here we analyze the prevalence and diffusion of links to low-credibility content about the pandemic across two major social media platforms, Twitter and Facebook. We characterize cross-platform similarities and differences in popular sources, diffusion patterns, influencers, coordination, and automation. Comparing the two platforms, we find divergence among the prevalence of popular low-credibility sources and suspicious videos. A minority of accounts and pages exert a strong influence on each platform. These misinformation "superspreaders" are often associated with the low-credibility sources and tend to be verified by the platforms. On both platforms, there is evidence of coordinated sharing of Infodemic content. The overt nature of this manipulation points to the need for societal-level rather than in-house mitigation strategies. However, we highlight limits imposed by inconsistent data-access policies on our capability to study harmful manipulations of information ecosystems.

Read the full article at: arxiv.org

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Economics in Nouns and Verbs

W. Brian Arthur

Standard economic theory uses mathematics as its main means of understanding,
and this brings clarity of reasoning and logical power. But there is a
drawback: algebraic mathematics restricts economic modeling to what can be
expressed only in quantitative nouns, and this forces theory to leave out
matters to do with process, formation, adjustment, creation and nonequilibrium.
For these we need a different means of understanding, one that allows verbs as
well as nouns. Algorithmic expression is such a means. It allows verbs
(processes) as well as nouns (objects and quantities). It allows fuller
description in economics, and can include heterogeneity of agents, actions as
well as objects, and realistic models of behavior in ill-defined situations.
The world that algorithms reveal is action-based as well as object-based,
organic, possibly ever-changing, and not fully knowable. But it is strangely
and wonderfully alive.

Read the full article at: arxiv.org

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Cells Form Into ‘Xenobots’ on Their Own

Cells Form Into ‘Xenobots’ on Their Own | Papers | Scoop.it

Embryonic cells can self-assemble into new living forms that don't resemble the bodies they usually generate, challenging old ideas of what defines an organism.

Read the full article at: www.quantamagazine.org

See Also: 

A cellular platform for the development of synthetic living machines
Douglas Blackiston, Emma Lederer, Sam Kriegman, Simon Garnier, Joshua Bongard, Michael Levin

Science Robotics 31 Mar 2021:
Vol. 6, Issue 52, eabf1571

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Random Networks with Quantum Boolean Functions

Random Networks with Quantum Boolean Functions | Papers | Scoop.it

Mario Franco, Octavio Zapata, David A. Rosenblueth,  and Carlos Gershenson

Mathematics 2021, 9(8), 792

We propose quantum Boolean networks, which can be classified as deterministic reversible asynchronous Boolean networks. This model is based on the previously developed concept of quantum Boolean functions. A quantum Boolean network is a Boolean network where the functions associated with the nodes are quantum Boolean functions. We study some properties of this novel model and, using a quantum simulator, we study how the dynamics change in function of connectivity of the network and the set of operators we allow. For some configurations, this model resembles the behavior of reversible Boolean networks, while for other configurations a more complex dynamic can emerge. For example, cycles larger than 2N were observed. Additionally, using a scheme akin to one used previously with random Boolean networks, we computed the average entropy and complexity of the networks. As opposed to classic random Boolean networks, where “complex” dynamics are restricted mainly to a connectivity close to a phase transition, quantum Boolean networks can exhibit stable, complex, and unstable dynamics independently of their connectivity.

Read the full article at: www.mdpi.com

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