Jiazhen Liu, Tamang Kunal, Dashun Wang, Chaoming Song

Science progresses by building upon previous discoveries. It is commonly believed that the impact of scientific papers, as measured by citations, is positively correlated with the impact of past discoveries built upon. However, analyzing over 30 million papers and nearly a billion citations across multiple disciplines, we find that there is a long-term positive citation correlation, but a negative short-term correlation. We demonstrate that the key to resolving this paradox lies in a new concept, called “capacity”, which captures the amount of originality remaining for a paper. We find there is an intimate link between capacity and impact dynamics that appears universal across the diverse fields we studied. The uncovered capacity measure not only explains the correlated impact dynamics across the sciences but also improves our understanding and predictions of high-impact discoveries.

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FRANK SCHWEITZER, GEORGES ANDRES, GIONA CASIRAGHI, CHRISTOPH GOTE, RAMONA ROLLER, INGO SCHOLTES, GIACOMO VACCARIO, and CHRISTIAN ZINGG

Advances in Complex SystemsVol. 25, No. 08, 2250014

Resilience denotes the capacity of a system to withstand shocks and its ability to recover from them. We develop a framework to quantify the resilience of highly volatile, non-equilibrium social organizations, such as collectives or collaborating teams. It consists of four steps: (i) delimitation, i.e. narrowing down the target systems, (ii) conceptualization, i.e. identifying how to approach social organizations, (iii) formal representation using a combination of agent-based and network models, (iv) operationalization, i.e. specifying measures and demonstrating how they enter the calculation of resilience. Our framework quantifies two dimensions of resilience, the robustness of social organizations and their adaptivity, and combines them in a novel resilience measure. It allows monitoring resilience instantaneously using longitudinal data instead of an ex-post evaluation.

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Jordi Piñero, Ricard Solé, Artemy Kolchinsky

Many molecular systems operate by harvesting and storing energy from their environments. However, the maintenance of a nonequilibrium state necessary to support energy harvesting itself carries thermodynamic costs. We consider the optimal tradeoff between costs and benefits of energy harvesting in a nonequilibrium steady state, for a system that may be in contact with a fluctuating environment. We find a universal bound on this tradeoff, which leads to closed-form expressions for optimal power output and optimal steady-state distributions for three physically meaningful regimes. Our results are illustrated using a model of a unicyclic network, which is inspired by the logic of biomolecular cycles.

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