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Michael te

As seen in: arXiv
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Articles by Michael te

Condensed Matter > Statistical Mechanics

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By Michael te
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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[2501.03235] Neural networks consisting of DNA

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By Michael te
| arXiv
arXiv:2501.03235 (physics) View PDF HTML (experimental) Comments: Subjects: Biological Physics (physics.bio-ph); Soft Condensed Matter (cond-mat.soft); Artificial Intelligence (cs.AI); Neural and Evolutionary Computing (cs.NE); Biomolecules (q-bio.BM); Molecular Networks (q-bio.MN) Cite as: arXiv:2501.03235 [physics.bio-ph] (or arXiv:2501.03235v1 [physics.bio-ph] for this version) https://doi.org/10.48550/arXiv.2501.03235 Submission history From: Michael Te Vrugt [ view email] [v1] Thu, 12...
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[2307.00437] Passive and active field theories for disease spreading

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By Michael te, Raphael Wittkowski, Julian Jeggle
| arXiv
The worldwide COVID-19 pandemic has led to a significant growth of interest in the development of mathematical models that allow to describe effects such as social distancing measures, the development of vaccines, and mutations. Several of these models are based on concepts from soft matter theory.
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[2302.05006] Thermodynamics of an Empty Box

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By Michael te Vrugt, Tore Haug-Warberg, Lodin Ellingsen, Michael te
| arXiv
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