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Complex Systems Studies

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Post #6050 1.1K
Complex Systems Studies What if birds of a feather flock together, but only at specific group sizes? https://nature.com/articles/s41467-025-66415-2 This is the focus of our new paper, Homophily within and across groups, now published in Nature Communications. Here, we introduce…
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Homophily within and across groups
https://nature.com/articles/s41467-025-66415-2
Post #6049 2.6K
What if birds of a feather flock together, but only at specific group sizes?
https://nature.com/articles/s41467-025-66415-2

This is the focus of our new paper, Homophily within and across groups, now published in Nature Communications. Here, we introduce a maximum-entropy random graph model that moves beyond these limits, capturing homophily across all social scales in the network, with parameters for each group size. The framework decomposes homophily into within- and across-group contributions, recovering the stochastic block model as a special case. As an exponential-family model, it fits empirical data and enables inference of group-level variation of homophily that aggregate metrics miss. The group-dependence of homophily substantially impacts network percolation thresholds, altering predictions for epidemic spread, information diffusion, and the effectiveness of interventions. Ignoring such heterogeneity risks systematically misjudging connectivity and dynamics in complex systems.
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Post #6046 1.44K
Statistical Physics Analysis of Graph Neural Networks: Approaching Optimality in the Contextual Stochastic Block Model

https://journals.aps.org/prx/abstract/10.1103/lfxj-hbsk
Physical Review X Statistical Physics Analysis of Graph Neural Networks: Approaching Optimality in the Contextual Stochastic Block Model An asymptotic analysis of graph convolutional networks shows that deeper architectures can boost performance when designed with residual connections, offering the first precise theory for infinitely deep graph neural networks.
Post #6044 1.24K

Forwarded from Sitpor.org سیتپـــــور

منظور از پدیدارگی در سیستم‌های پیچیده چیست؟
عباس ریزی

معروف است که سیستم‌های پیچیده در مقیاس ریز، اجزایشان برهم‌کنش‌های موضعی دارند ولی در مقیاس درشت، رفتارهای «پدیداره» از خود نشان می‌دهند که شبیه به رفتار اجزا در مقیاس ریز نیستند. اما به راستی این پدیدارگی چیست؟ آیا درک ویژگی‌ها یا رفتارهای پدیداره نیاز به چیزهای دیگری دارد؟ در این سخنرانی که بر اساس مقاله مروری زیر است، به این مسئله می‌پردازیم.

What is emergence, after all?
🎞 ویدیو در یوتیوب
🔗 اسلایدها
🎧 فایل صوتی
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@sitpor | sitpor.org
instagram.com/sitpor_media
#سیتپـــــور به خاطر روایتگری در علم
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Post #6043 999

Forwarded from Anahid Kiani

🔷 جلسات سمینار هفتگی فیزیک اماری و سامانه های پیچیده

📜 موضوع ارائه: پدیدارگی در سیستم های پیچیده چیست؟

👨🏻‍💻 ارائه دهنده: عباس کریمی ریزی

🕒 زمان: دوشنبه ۱۰ آذر، ساعت ۱۵

📍مکان: سالن سمینار، طبقه سوم دانشکده فیزیک

💻 لینک گوگل میت:

https://meet.google.com/wgd-aesr-yuk
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🌐http://ccnsd.ir
🌐 https://complexity.sbu.ac.ir/

🆔 @Complexity_SBU
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Post #6040 940
Sociophysics models inspired by the Ising model
https://arxiv.org/abs/2506.23837

The Ising model, originally developed for understanding magnetic phase transitions, has become a cornerstone in the study of collective phenomena across diverse disciplines. In this review, we explore how Ising and Ising-like models have been successfully adapted to sociophysical systems, where binary-state agents mimic human decisions or opinions. By focusing on key areas such as opinion dynamics, financial markets, social segregation, game theory, language evolution, and epidemic spreading, we demonstrate how the models describing these phenomena, inspired by the Ising model, capture essential features of collective behavior, including phase transitions, consensus formation, criticality, and metastability. In particular, we emphasize the role of the dynamical rules of evolution in the different models that often converge back to Ising-like universality. We end by outlining the future directions in sociphysics research, highlighting the continued relevance of the Ising model in the analysis of complex social systems.
arXiv.org Sociophysics models inspired by the Ising model The Ising model, originally developed for understanding magnetic phase transitions, has become a cornerstone in the study of collective phenomena across diverse disciplines. In this review, we...
Post #6039 933
Round table: Ruminations on the Ising Model: Past, Present, Future

with:
Jürg Fröhlich (ETH Zürich)
Tom Spencer (IAS)
Arthur Jaffe (Harvard University)
Geoffrey Grimmett (University of Cambridge)
Joel Lebowitz (Rutgers University)

https://youtu.be/YvS0j2pj_xY
YouTube Round table: Ruminations on the Ising Model: Past, Present, Future round table moderated by Geoffrey GRIMMETT with: Jürg Fröhlich (ETH Zürich) Tom Spencer (IAS) Arthur Jaffe (Harvard University) Geoffrey Grimmett (University of Cambridge) Joel Lebowitz (Rutgers University)
Post #6038 764
The Unreasonable Effectiveness of Spectral Graph Theory: A Confluence of Algorithms, Geometry, and Physics

https://youtu.be/8XJes6XFjxM
YouTube The Unreasonable Effectiveness of Spectral Graph Theory: A Confluence of Algorithms, Geometry & ... James R. Lee, University of Washington Simons Institute Open Lectures http://simons.berkeley.edu/events/openlectures2014-fall-4 Full title: The Unreasonable Effectiveness of Spectral Graph Theory: A Confluence of Algorithms, Geometry, and Physics
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Post #6035 1.04K
Epistorm-Mix provides privacy-preserving contact data and contact patterns characterization relevant for the spread of respiratory infectious diseases within the US population.

Built on a probability-based sample, Epistorm-Mix delivers population-level contact matrices and mixing indicators that reflect real-world heterogeneity across age, sex, race/ethnicity, income, and settings. These data enable epidemic models to better capture differential infection risks and to test targeted interventions in silico—offering actionable insight for seasonal preparedness and pandemic response.
The Repository

https://www.epistorm.org/data/epistorm-mix
www.epistorm.org Epistorm-Mix: Mapping Social Contact Patterns in the Post-Pandemic United States Epistorm-Mix provides individual-level contact data and contacts patterns characterization relevant for the spread of respiratory infectious diseases within the US population.
Post #6033 1.17K
Zoo of Centralities: Encyclopedia of Node Metrics in Complex Networks

Centrality is a fundamental concept in network science, providing critical insights into the structure and dynamics of complex systems such as social, transportation, biological and financial networks. Despite its extensive use, there is no universally accepted definition of centrality, leading to the development of a large variety of distinct centrality measures. These measures have grown so numerous that they resemble a 'zoo', each representing a unique approach to capturing node importance within a network. However, the increasing number of metrics being developed has led to several challenges, including issues of discoverability, redundancy, naming conflicts, validation and accessibility. This work aims to address these challenges by providing a comprehensive catalog of over 400 centrality measures, along with clear descriptions and references to original sources. While not exhaustive, this compilation represents the most extensive and systematic effort to date in organizing and presenting centrality measures. We also encourage readers to explore and contribute to the Centrality Zoo website at this https URL, which provides an interactive platform for discovering and comparing centrality measures.

https://arxiv.org/abs/2511.05122
arXiv.org Zoo of Centralities: Encyclopedia of Node Metrics in Complex Networks Centrality is a fundamental concept in network science, providing critical insights into the structure and dynamics of complex systems such as social, transportation, biological and financial...
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Post #6032 952
ertekezes.pdf4.3 MB
Deep Learning Techniques for the Analysis of Soccer Matches

Pegah Rahimian

Postdoctoral position at Department of Information Technology; Division of Systems and Control
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