Clément Vidal

2papers

2 Papers

SRJan 5
Emergent Complexity in Nuclear Reaction Networks: A Study of Stellar Nucleosynthesis through Chemical Organization Theory

Pedro Maldonado-Lang, Clément Vidal

We explore the emergence of complex structures within reaction networks, focusing on nuclear reaction networks relevant to stellar nucleosynthesis. The work presents a theoretical framework rooted in Chemical Organization Theory (COT) to characterize how stable, self-sustaining structures arise from the interactions of basic components. Key theoretical contributions include the formalization of atom sets as fundamental reactive units and the concept of synergy to describe the emergence of new reactions and species from the interaction of these units. The property of separability is defined to distinguish dynamically coupled systems from those that can be decomposed. This framework is then applied to the STARLIB nuclear reaction network database, analyzing how network structure, particularly the formation and properties of atom sets and semi-self-maintaining sets, changes as a function of temperature. Results indicate that increasing temperature generally enhances network cohesion, leading to fewer, larger atom sets. Critical temperatures are identified where significant structural reorganizations occur, such as the merging of distinct clusters of atom sets and the disappearance of small, isolated reactive units. The analysis reveals core clusters - large (containing more that 1000 reactions), semi-self-maintaining structures that appear to form the core of all potentially stable nucleosynthetic configurations at various temperatures. Overall, the paper provides insights into the structural underpinnings of stability and emergence in complex reaction networks, with specific implications for understanding stellar evolution and nucleosynthesis.

AINov 18, 2025
Project Rachel: Can an AI Become a Scholarly Author?

Martin Monperrus, Benoit Baudry, Clément Vidal

This paper documents Project Rachel, an action research study that created and tracked a complete AI academic identity named Rachel So. Through careful publication of AI-generated research papers, we investigate how the scholarly ecosystem responds to AI authorship. Rachel So published 10+ papers between March and October 2025, was cited, and received a peer review invitation. We discuss the implications of AI authorship on publishers, researchers, and the scientific system at large. This work contributes empirical action research data to the necessary debate about the future of scholarly communication with super human, hyper capable AI systems.