Bulletin of the American Physical Society
APS March Meeting 2021
Volume 66, Number 1
Monday–Friday, March 15–19, 2021; Virtual; Time Zone: Central Daylight Time, USA
Session V18: The Statistical Physics of Real-world NetworksInvited Live Undergrad Friendly
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Sponsoring Units: GSNP Chair: Guido Caldarelli, University of Venice Ca'Foscari |
Thursday, March 18, 2021 3:00PM - 3:36PM Live |
V18.00001: Complex networks with complex nodes Invited Speaker: Raissa D'Souza The statistical physics perspective has provided a wealth of understanding about the structure and function of massive networks including phase transition behaviors, non-trivial network structures such as modularity and heterogeneous degree distributions, and the analysis of the dynamics unfolding on networks. It reveals the massive implications that network structure can have on network function and resilience. Yet, complementary to this perspective of complex networks, simple networks of nonlinear nodes have been studied extensively in fields of dynamical systems and control theory. Real world networks -- from brain networks to social networks to critical infrastructure networks -- lie at the interface of both, with nonlinear nodes and highly non-trivial network structures. We are at a point in time when there is opportunity for these fields to come together. This talk will survey results of a recent project at three different scales on the complex node versus complex network spectrum, from synchronization in nanoscale oscillations to hierarchy and stability in multilayered social systems of macaque monkeys. |
Thursday, March 18, 2021 3:36PM - 4:12PM Live |
V18.00002: Construction, Filtration and Dynamics of Functional Brain Networks Invited Speaker: Tommaso Gili The large extent of our knowledge of brain functioning reaches a deeper insight into its mechanisms if seen through the lens of complex networks. Timeseries of brain activity (neurovascular and electrophysiological) have been extensively used to associate the brain functional segregation with specific behavioral outcomes. A comprehensive description of the cerebral functionality relays on the embedding and filtration of a fully connected network and on the subsequent evaluation of the supported dynamics. |
Thursday, March 18, 2021 4:12PM - 4:48PM Live |
V18.00003: Structure, phase transitions, and message passing in sparse networks Invited Speaker: Mark Newman Most networks and graphs encountered in empirical studies, including technological, social, and biological and ecological networks, are very sparse. Standard spectral and linear algebra methods perform poorly when applied to such networks. Message passing methods, such as belief propagation, offer an alternative which works well in the sparse limit and which can also provide new analytic insights. This talk will introduce the message passing method through a series of examples and illustrate how the method can be used for a wide range of calculations of network structure and function. Among other things, the talk will touch upon the calculation of percolation properties, graph spectra, and community structure, the deep connections between message-passing fixed points and structural phase transitions in networks, and a new solution to the long-standing problem of message passing on networks with a high density of short loops. |
Thursday, March 18, 2021 4:48PM - 5:24PM Live |
V18.00004: Percolation in real interdependent networks Invited Speaker: Filippo Radicchi The function of a real network depends not only on the reliability of its own components, but is affected also by the simultaneous operation of other real networks coupled with it. Robustness of systems composed of interdependent network layers is generally framed and characterized in terms of percolation models. In this talk, I will consider three different variants of percolation models that provide different insights on the robustness of real-world interdependent networks. I will first consider the ordinary percolation model and illustrate a theoretical approach consisting in a system of heuristic equations able to approximate the phase diagram for arbitrary networks. Second, I will introduce and characterize the redundant percolation model, a genuine model for interdependent networks where the addition of new layers boosts system robustness by creating redundant interdependencies among network layers. Third, I will generalize the problem of optimal percolation |
Thursday, March 18, 2021 5:24PM - 6:00PM Live |
V18.00005: Statistical Physics of Twitter users' interactions Invited Speaker: Fabio SARACCO In 1957 Jaynes proposed an Information Theory approach to derive the statistical ensembles of Statistical Mechanics [1]: the maximisation of the Shannon entropy, after constraining the energy of the system returns exactly the probability distributions of the canonical ensemble. Recently, the same approach was extended to the study of complex networks [2-4] and, when applied to the study of the political debate on Online Social Networks (OSN), it permits to infer several non-trivial information, as the political orientation of the users, the effective flow of messages and the presence of (dis)information strategies [5-7]. In the present seminar I will review the definition of such framework and show the details of the various applications on the political debate on Twitter. |
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