Decoherence and decay of quantum systems arise from interactions with their environment that can be highly complex. Despite this complexity, bounds on the decay rate are found that are asymptotically ...

Homophily, the overrepresentation of interactions among similar individuals, and heterophily, the elevated prevalence of interactions among dissimilar ones, are frequently observed mixing patterns in ...

We investigate the geometric structure of evolving infectious-disease networks using a notion of node curvature, which is based on the heat-kernel expansion that naturally extends to edges. Applying t...

In networks that grow by isotropic redirection (IR), a new node selects an initial target node uniformly at random and attaches to a randomly chosen neighbor of the target. The emerging networks exhib...

Many scientists use artificial intelligence in their work, but agents are increasingly soliciting researchers for collaborations.

We study how retweet interactions in large-scale Twitter debates are organized beyond direct links alone. Focusing on Twitter debate in Italy during the first phase of the COVID-19 pandemic, we combin...

In network science, one often wants to say that a given real-world network appears to come from a particular network model. In statistical physics, the corresponding problem is about how typical a giv...

Capability and efficiency are two key dimensions of reasoning in large language models (LLMs). Capability refers to the ability to solve a given problem correctly, whereas efficiency refers to the abi...

Public health measures at mass gatherings work only if people follow them, and adherence depends both on how instructions are communicated and what others do. We link these behavioural factors to path...

Reconstructing the state of a large networked system from measurements at only a few nodes is a challenge for monitoring, prediction, and intervention. Here we ask whether such reconstruction is possi...

The stochastic block model is a paradigmatic model of networks with community structure. Yet percolation in the model has been studied primarily in cases with a fixed block structure, even though in r...

Author summary Why do people cooperate even when selfish behavior looks rewarding? Network models show that who interacts with whom matters, but most assume the same kind of dilemma in every social se...

An analysis of UK banking data reveals that people who reported being victim-survivors of financial abuse experience worse financial outcomes compared with a control group.

Emerging infectious disease outbreak risks are ubiquitous worldwide, and highest in landscapes where people, livestock and fragmented natural ecosystems coexist, but detection and data ...

As generative AI agents are deployed at scale, safety will depend not only on technical safeguards and individual model design, but also on collective equilibria that determine how agent populations p...

The debate over pairwise and higher-order models is often cast as a contest of expressive power, but this framing is misleading. A graph with arbitrary multivariate node functions can emulate the node...

Manman Chen, Wanzhou Wang and colleagues examined how infectious disease epidemics were associated with changes in the health workforce across 194 countries and territories from 1990 to 2019. Their fi...

Global trade is more than a single network of aggregate flows. Beneath the observable exchange of products among economies lies a complex multilayer structure, formed by thousands of product-specific ...

Residential and social sorting along political lines structure Americans' daily interactions, often limiting encounters with opposing viewpoints. Here, we combine high-resolution anonymized mobility d...

Large language models can potentially serve as human proxies across various roles, enabling nuanced simulations of behavior. This Review categorizes their applications, stressing distinct evaluation m...

Group interactions are widespread, and higher-order extensions of familiar models display collective phenomena absent from their pairwise baselines, which are routinely offered as evidence of a distin...

The current debate on higher-order interactions raises a fundamental question: when can systems organized through group interactions be faithfully represented within a graph-based formalism? Recent re...

Large-scale experiments now underpin much of modern social science. This Perspective highlights six emerging challenges and suggests directions for future research.

Environmental systems are characterized by complex spatial interactions that cannot be fully described through pairwise relationships or local uncertainty measures. We propose a unified framework comb...

How to best allocate resources to combat the threat of pathogen emergence remains an important open question. Using archetypes that characterize the link from genotype to fitness in both zoonotic rese...

Characterizing temporal interactions in social systems is challenging because social behavior can be bursty and non-stationary, violating the stationarity assumptions of many methods used to measure t...

Inferring network structure from dynamical observations is a fundamental inverse problem in complex systems. Existing approaches have largely focused on single-layer or pairwise interaction networks, ...

Green economic complexity provides a generalizable framework for examining countries' productive capabilities in a defined product set. We apply this framework to AI-enabling goods within the full pro...

Paper2Agent converts research papers into interactive artificial intelligence agents by turning manuscripts, code and data into model context protocol-based tool-invoking systems that reproduce origin...

Music is widely utilized to support recovery from stress, yet the precise neural mechanisms driving this therapeutic effect remain poorly understoo...

Boger and Firestone show that humans possess a domain-general, cross-modal representation of complexity.

Social networks shape how individuals make decisions and how opportunities are distributed. However, the mechanisms that generate these networks often reflect pre-existing inequalities, and technologi...

Achieving universal health coverage, as set out in Sustainable Development Goal 3.8, requires closing persistent geographic and socioeconomic gaps in healthcare access, especially in under-resourced s...

Network motifs, recurrent local patterns of interactions in graphs, provide fundamental insights on the interplay between structure and functionality in complex systems. Many real-world systems are no...

Urban street networks are modeled as spatial graphs whose geometry reflects planning, history, and physical constraints. Global orientation measures describe the overall order of a city but do not rev...

Cities are commonly characterized through population density, infrastructure, and mobility flows. These quantities describe where people are and how they move, but movement does not uniquely determine...

Nature asked eight leaders in higher education what they thought about the state of UK institutions. Here’s how they answered.

Multilevel sociality, in which large communities emerge from interconnected subgroups, is a hallmark of primate societies and a central focus of the social brain hypothesis. We investigate whether suc...

Author summary A wide range of respiratory viruses (influenza viruses, coronaviruses, respiratory syncytial virus, ...) circulate in the same communities and can infect the same individuals. Yet, the ...

In a deterministic, non-chaotic system, the initial state fixes the future completely, yet that future may be impossible to forecast from it. Using a cellular automaton of communicating cells, this st...

This study investigates the robustness of shallow graph embedding methods for community detection in the face of network perturbations, specifically node deletions. Graph embedding techniques, which r...

We present a comprehensive description of the network of Italian Business-to-Business commercial relationships, based on the universe of electronic invoices collected by the Italian Tax Office. The fi...

Temporal-network models attribute memory in contact data to either node self-excitation (branching ratio n_node) or tie reinforcement (kappa), carrying major consequences for epidemic spreading. We pr...

Social systems, when considered on an appropriately coarse-grained scale, display phenomena reminiscent of the behavior of physical many-body systems and can be studied using the methods of statistica...

Complex networked systems are prevalent in biology, engineering, and the social sciences, yet their high-dimensional, nonlinear dynamics pose major challenges for analysis and prediction. A mathematic...

Infodemics represent a significant threat to public health, arising from complex interactions between online and offline phenomena. The continuous feedback loops between digital information ecosystems...

From protein complexes to electronic circuits, many natural and engineered systems function only if assembled in an exact, reproducible fashion. The structure of each of these systems can be understoo...

Author summary When diseases spread, people change their behavior—avoiding crowds, wearing masks, washing hands more frequently. Yet many mathematical models used to predict epidemics assume people be...

Amid a shortage of human reviewers, tests indicate AI can assist—but is not a savior

Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans...