Forwarded from Sitpor.org سیتپـــــور
سمینارهای هفتگی دانشکدهی فیزیک دانشگاه صنعتی خواجه نصیرالدّین طوسی:
پیچیدگی چیست؟
عباس ریزی
دوشنبه ۲۶ آبانماه، ساعت ۱۲:۱۵ تا ۱۳:۳۰
سالن سفیر، پردیس شهید رضایینژاد
https://meet.google.com/aec-wjdx-pqi
----------------------------------------------
@sitpor | sitpor.org
instagram.com/sitpor_media
#سیتپـــــور به خاطر روایتگری در علم
پیچیدگی چیست؟
عباس ریزی
دوشنبه ۲۶ آبانماه، ساعت ۱۲:۱۵ تا ۱۳:۳۰
سالن سفیر، پردیس شهید رضایینژاد
https://meet.google.com/aec-wjdx-pqi
----------------------------------------------
@sitpor | sitpor.org
instagram.com/sitpor_media
#سیتپـــــور به خاطر روایتگری در علم
👍4
Chris Kempes, The Easy Part of Biology | Natural Philosophy Symposium 2025
https://youtu.be/riKfuUiGOjk
https://youtu.be/riKfuUiGOjk
YouTube
Chris Kempes, The Easy Part of Biology | Natural Philosophy Symposium 2025
The inaugural Natural Philosophy Symposium was held in Baltimore on May 29-31, 2025. It was sponsored by the Natural Philosophy Forum at Johns Hopkins (https://www.naturalphilosophyhopkins.org/), covering all aspects of natural philosophy, featuring talks…
Bloomberg is pleased to announce the 2026-2027 edition of the Bloomberg Data Science #PhD Fellowship Program (https://www.techatbloomberg.com/bloomberg-data-science-ph-d-fellowship/), a premier initiative supporting outstanding Ph.D. students advancing the frontiers of data science, AI and their applications
Bloomberg L.P.
Data Science Ph.D. Fellowship | Bloomberg LP
Apply now for the Bloomberg Data Science Ph.D. Fellowship program. Applications are due by April 28, 2023 for the 2023-2024 academic year.
👍1
پستداک در دانشگاه کردستان
https://sbna.uok.ac.ir/postdoctoral-opportunity-in-network-analysis-at-sbna-lab.html
https://sbna.uok.ac.ir/postdoctoral-opportunity-in-network-analysis-at-sbna-lab.html
SBNA (Social & Biological Network Analysis) Lab.
Postdoctoral Opportunity in Network Analysis at SBNA Lab
The Social & Biological Network Analysis (SBNA) Laboratory at the University of Kurdistan is pleased to announce an opening for…
#postdoc Researcher positions | Statistical Physics and Active Matter
https://www.mpg.de/25427964/postdoctoral-researcher-positions-mpids-w088
https://www.mpg.de/25427964/postdoctoral-researcher-positions-mpids-w088
Max-Planck-Gesellschaft
Postdoctoral Researcher positions | Statistical Physics and Active Matter
Postdoctoral Researcher positions on Statistical Physics and Active Matter at the Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
👎1
ertekezes.pdf
4.3 MB
Deep Learning Techniques for the Analysis of Soccer Matches
Pegah Rahimian
Postdoctoral position at Department of Information Technology; Division of Systems and Control
Pegah Rahimian
Postdoctoral position at Department of Information Technology; Division of Systems and Control
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
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...
👍4
epydemix is an open-source Python package designed for flexible, modular, and data-driven epidemic modeling.
https://www.epydemix.org/
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1013735
https://www.epydemix.org/
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1013735
www.epydemix.org
epydemix: The ABC of epidemics
epydemix is a Python package for epidemic modeling. It provides tools to create, calibrate, and analyze epidemic models, allowing users to simulate the spread of infectious diseases using different compartmental models, contact layers, and calibration techniques.…
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
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.
Forwarded from Theoretical_Physics
Information theory for complex systems scientists.pdf
1.5 MB
Information theory for complex systems scientists: What, why, and how
Physics Reports, Volume 1148, 8 December 2025, Pages 1-55
Physics Reports, Volume 1148, 8 December 2025, Pages 1-55
👍2
Roland Bauerschmidt - Perspectives on the renormalisation group approach
https://youtu.be/l1iZbsEiO6c
https://youtu.be/l1iZbsEiO6c
YouTube
Roland Bauerschmidt - Perspectives on the renormalisation group approach
The goal of this talk is to review some of the successes but also the outstanding challenges of the renormalisation group approach to the Ising and \varphi^4 models. I will also try to describe a common perspective of the usual approach to the renormalisation…
The Unreasonable Effectiveness of Spectral Graph Theory: A Confluence of Algorithms, Geometry, and Physics
https://youtu.be/8XJes6XFjxM
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
https://simons.berkeley.edu/events/openlectures2014-fall-4
Full title: The Unreasonable Effectiveness of Spectral Graph Theory: A Confluence of Algorithms, Geometry, and Physics
Simons Institute Open Lectures
https://simons.berkeley.edu/events/openlectures2014-fall-4
Full title: The Unreasonable Effectiveness of Spectral Graph Theory: A Confluence of Algorithms, Geometry, and Physics
👍1
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
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)
with:
Jürg Fröhlich (ETH Zürich)
Tom Spencer (IAS)
Arthur Jaffe (Harvard University)
Geoffrey Grimmett (University of Cambridge)
Joel Lebowitz (Rutgers University)
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.
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...
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
-------------------------------------
🌐https://ccnsd.ir
🌐 https://complexity.sbu.ac.ir/
🆔 @Complexity_SBU
📜 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
-------------------------------------
🌐https://ccnsd.ir
🌐 https://complexity.sbu.ac.ir/
🆔 @Complexity_SBU
👍6👎1
Forwarded from Sitpor.org سیتپـــــور
Media is too big
VIEW IN TELEGRAM
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
----------------------------------------------
@sitpor | sitpor.org
instagram.com/sitpor_media
#سیتپـــــور به خاطر روایتگری در علم
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
----------------------------------------------
@sitpor | sitpor.org
instagram.com/sitpor_media
#سیتپـــــور به خاطر روایتگری در علم
👍6
The perplexing “connected cluster axiom” – Inverse Complexity Lab
https://skewed.de/lab/posts/connected-clusters/#fn1
https://skewed.de/lab/posts/connected-clusters/#fn1
skewed.de
The perplexing “connected cluster axiom” – Inverse Complexity Lab
Research group on inverse problems in complex systems and network science.
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
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.