What does this research mean for the field?

MOSAIC is a scalable framework that accurately simulates heterogeneous stochastic systems by incorporating agent-specific properties and non-Markovian dynamics. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

The aim is to accurately simulate non-Markovian dynamics in heterogeneous stochastic systems.

March 4, 2026Nature CommunicationsOpen Access

Unifying non-Markovian dynamics and agent heterogeneity in scalable stochastic networks

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Authors

APAurélien PélissierETH Zurich MPMiroslav PhanETH Zurich DBDidier Le BailCentre National de la Recherche Scientifique

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Implication

This research introduces MOSAIC to simulate heterogeneous dynamics in stochastic networks, suggesting improved accuracy over classical methods.

Key Points

The aim is to accurately simulate non-Markovian dynamics in heterogeneous stochastic systems.
Introduced MOSAIC framework for modeling stochastic agents with individual complexity.
Embedded agent-specific properties directly into the stochastic dynamics.
Unified heterogeneous rates and dynamic interaction preferences within one formalism.
Applied framework to various domains including biochemical reactions and social networks.
MOSAIC reproduces empirical features often missed by existing methods.
It captures complex dynamics at a computational cost similar to Gillespie-like algorithms.
Applications show improved simulation of delayed reactions and immune-cell interactions.

Cite This Study

Pélissier et al. (2026) studied this question.

synapsesocial.com/papers/69a7cd2ad48f933b5eed94c0 https://doi.org/10.1038/s41467-026-69817-y

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Implication

This research introduces MOSAIC to simulate heterogeneous dynamics in stochastic networks, suggesting improved accuracy over classical methods.

Unifying non-Markovian dynamics and agent heterogeneity in scalable stochastic networks

Discussion

Member takes

Implication

Key Points

Cite This Study

Unifying non-Markovian dynamics and agent heterogeneity in scalable stochastic networks

Discussion

Member takes

Implication

Key Points

Cite This Study

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