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X-WR-CALDESC:Events for Biomedical Mathematics Group
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TZID:Asia/Seoul
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TZOFFSETFROM:+0900
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DTSTART:20240101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20251024T100000
DTEND;TZID=Asia/Seoul:20251024T120000
DTSTAMP:20260423T013542
CREATED:20250928T144047Z
LAST-MODIFIED:20251023T035250Z
UID:11629-1761300000-1761307200@www.ibs.re.kr
SUMMARY:Dynamical Mean-Field Theory of Complex Systems on Sparse Directed Networks - Gyuyoung Hwang
DESCRIPTION:In this talk\, we discuss the paper “Dynamical Mean-Field Theory of Complex Systems on Sparse Directed Networks” by Fernando L. Metz\, Phys. Rev. Letters\, 2025. \nAbstract \nAlthough real-world complex systems typically interact through sparse and heterogeneous networks\, analytic solutions of their dynamics are limited to models with all-to-all interactions. Here\, we solve the dynamics of a broad range of nonlinear models of complex systems on sparse directed networks with a random structure. By generalizing dynamical mean-field theory to sparse systems\, we derive an exact equation for the path probability describing the effective dynamics of a single degree of freedom. Our general solution applies to key models in the study of neural networks\, ecosystems\, epidemic spreading\, and synchronization. Using the population dynamics algorithm\, we solve the path-probability equation to determine the phase diagram of a seminal neural network model in the sparse regime\, showing that this model undergoes a transition from a fixed-point phase to chaos as a function of the network topology.
URL:https://www.ibs.re.kr/bimag/event/dynamical-mean-field-theory-of-complex-systems-on-sparse-directed-networks-gyuyoung-hwang/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
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