NetScience

Strongly clustered random graphs via triadic closure: Degree correlations and clustering spectrum Real-world networks often exhibit strong transitivity with nontrivial local clustering spectra and degree correlations. Such features are not easily modelled in tractable network models, creating an o...

Strongly clustered random graphs via triadic closure: Degree correlations and clustering spectrum arxiv.org/abs/2603.04669

Quantifying the spatiotemporal dynamics of the first two epidemic waves of SARS-CoV-2 infections in the United States Author summary In this work, we developed a set of tools and methods designed to produce high-resolution visualizations, as well as to quantify the complex and intricate patterns associated with the s...

Quantifying the spatiotemporal dynamics of the first two epidemic waves of SARS-CoV-2 infections in the United States journals.plos.org/ploscompbiol...

Harder, shorter, sharper, forward: A comparison of women's and men's elite football gameplay (2020-2025) Elite football is believed to have evolved in recent years, yet systematic evidence for the pace and form of that change remains sparse. Drawing on event-level records for 13,018 matches across ten to...

Harder, shorter, sharper, forward: A comparison of women's and men's elite football gameplay (2020-2025) arxiv.org/abs/2506.22119

Women in Science: Measuring Participation in Europe Across Disciplines, Generations and Over Time In this research, we quantify an inflow of women into science in the past three decades. Structured Big Data allow us to estimate the contribution of women scientists to the growth of science by disci...

Women in Science: Measuring Participation in Europe Across Disciplines, Generations and Over Time arxiv.org/abs/2411.00008

Higher-order interactions at scientific conferences influence team formation Cooperation enables teams to solve complex problems that one individual alone cannot address. In science, collaborative teams have become the predominant way through which progress is achieved. These ...

Higher-order interactions at scientific conferences influence team formation arxiv.org/abs/2603.02571

Projective limits of probabilistic symmetries and their applications to random graph limits We couple projective limits of probability measures to direct limits of their symmetry groups. We show that the direct limit group is the group of symmetries of the projective limit probability measur...

Projective limits of probabilistic symmetries and their applications to random graph limits arxiv.org/abs/2512.02208

To trace or not to trace: analytical insights from network-based contact-tracing models Contact tracing is one of the most important control measures deployed during epidemics. Relying on the identification of contacts of known infected individuals, it necessitates a network perspective....

To trace or not to trace: analytical insights from network-based contact-tracing models arxiv.org/abs/2603.04059

The SIS Competition Model for Conflicting Rumors We propose an SIS competition model describing the propagation of conflicting rumors, such as fake news and its corrections. This simple model captures the interaction between rumor propagation and op...

The SIS Competition Model for Conflicting Rumors arxiv.org/abs/2603.03949

See raining iguanas and coral from the inside out — February’s best science images The month’s sharpest science shots, selected by Nature’s photo team.

See raining iguanas and coral from the inside out — February’s best science images idp.nature.com/authorize?re...

Fast degree-preserving rewiring of complex networks In this paper we introduce a new, fast, degree-preserving rewiring algorithm for altering the assortativity of complex networks, which we call \textit{Fast total link (FTL) rewiring} algorithm. Common...

Fast degree-preserving rewiring of complex networks arxiv.org/abs/2401.12047

Consensus and fragmentation in academic publication preferences Academic publishing requires solving a collective coordination problem: among thousands of possible publication venues, which deserve a community's attention? A clear consensus helps scholars allocate...

Consensus and fragmentation in academic publication preferences arxiv.org/abs/2603.00807

Diversification of global food trade partners increased inequalities in the exposure to shock risks Recent global food trade disruptions have evidenced how local shocks can cascade into global security threats. While the capacity of food systems to absorb spillovers depends heavily on its underlying...

Diversification of global food trade partners increased inequalities in the exposure to shock risks arxiv.org/abs/2603.01740

$Q$-learning-based community detection algorithm link.aps.org/doi/10.1103/...

Self-Organized Criticality in Atmospheric Rivers A statistical-physics-based analysis of the full life cycle of atmospheric rivers finds universal signatures of self-organized criticality.

Self-Organized Criticality in Atmospheric Rivers link.aps.org/doi/10.1103/...

Unifying non-Markovian dynamics and agent heterogeneity in scalable stochastic networks idp.nature.com/authorize?re...

Cross-order induced behaviors in contagion dynamics on higher-order networks Recent studies have shown that novel collective behaviors emerge in complex systems due to higher-order interactions. However, the way in which the structural correlations of these interactions shape ...

Cross-order induced behaviors in contagion dynamics on higher-order networks arxiv.org/abs/2602.24023

Fluid dynamics meet network science: two cases of temporal network eigendecomposition Temporal networks, defined as sequences of time-aggregated adjacency matrices, sample latent graph dynamics and trace trajectories in graph space. By interpreting each adjacency matrix as a different ...

Fluid dynamics meet network science: two cases of temporal network eigendecomposition arxiv.org/abs/2509.03135

Three AI-agents walk into a bar . . . . `Lord of the Flies' tribalism emerges among smart AI-Agents Near-future infrastructure systems may be controlled by autonomous AI agents that repeatedly request access to limited resources such as energy, bandwidth, or computing power. We study a simplified ve...

Three AI-agents walk into a bar . . . . `Lord of the Flies' tribalism emerges among smart AI-Agents arxiv.org/abs/2602.23093

Renormalization of interacting random graph models link.aps.org/doi/10.1103/...

Modeling financial transactions via random walks on temporal networks We model financial transactions as random walks on activity-driven temporal networks. By enforcing fund conservation, our framework analytically derives heavy-tailed distributions for the stationary b...

Modeling financial transactions via random walks on temporal networks arxiv.org/abs/2602.20713

Selecting representative community partitions under modularity degeneracy: the STAR method Community detection based on modularity maximization is one of the most widely used approaches for uncovering mesoscale structures in complex networks. However, it is well known that the modularity fu...

Selecting representative community partitions under modularity degeneracy: the STAR method arxiv.org/abs/2602.21838

Academic collaborations and movements towards successful careers in physics Collaboration networks evolve throughout academic careers, yet few studies systematically examine how these network dynamics relate to long-term career success and mobility. Analysing 35,708 physicist...

Academic collaborations and movements towards successful careers in physics arxiv.org/abs/2602.22031

A Bayesian approach to out-of-sample network reconstruction Networks underpin systems that range from finance to biology, yet their structure is often only partially observed. Current reconstruction methods typically fit the parameters of a model anew to each ...

A Bayesian approach to out-of-sample network reconstruction arxiv.org/abs/2602.21869

On the equivalence between nonlinear graph-based dynamics and linear dynamics on higher-order networks In network science, collective dynamics of complex systems are typically modelled as (nonlinear, often including many-body) vertex-level update rules evolving over a graph interaction structure. In re...

On the equivalence between nonlinear graph-based dynamics and linear dynamics on higher-order networks arxiv.org/abs/2602.21727

Modeling plant disease spread via high-resolution human mobility networks Human mobility plays a crucial role in the spread of human diseases, but is rarely quantified in plant disease epidemics. To address this gap, we integrate a unique, high-resolution network of human m...

Modeling plant disease spread via high-resolution human mobility networks arxiv.org/abs/2602.21491

Multiplexity amplifies geometry in networks Many real-world network are multilayer, with nontrivial correlations across layers. Here we show that these correlations amplify geometry in networks. We focus on mutual clustering--a measure of the a...

Multiplexity amplifies geometry in networks arxiv.org/abs/2505.17688

Group adaptation drives opinion dynamics in higher-order networks In modern interconnected societies, opinions and beliefs can quickly spread across large populations, giving rise to collective behaviors such as the adoption of social norms or polarization. These ph...

Group adaptation drives opinion dynamics in higher-order networks arxiv.org/abs/2602.19684

Non-Pharmaceutical Interventions Reshape Network Immunization Outcomes Herd immunity is shaped not only by the infection capacity of a spreading epidemic or the contact structure of the hosting population, but also by how and under what circumstances individuals acquire ...

Non-Pharmaceutical Interventions Reshape Network Immunization Outcomes arxiv.org/abs/2602.17360

Beyond the Wisdom of the Crowd: How Network Topology Distorts Collective Perception Cognitive biases are often attributed to heuristics or limited information. Yet the structure of social networks is a key, often-overlooked source of perceptual bias. When information passes through s...

Beyond the Wisdom of the Crowd: How Network Topology Distorts Collective Perception arxiv.org/abs/2602.17146

Graphs are maximally expressive for higher-order interactions We demonstrate that graph-based models are fully capable of representing higher-order interactions, and have a long history of being used for precisely this purpose. This stands in contrast to a commo...

Graphs are maximally expressive for higher-order interactions arxiv.org/abs/2602.16937