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PreprintCC BY 4.0arXiv

Extended Onsager's variational principle for nonlinear chemical reaction kinetics in active matter

Abstract

Onsager's variational principle (OVP) constructs dissipative dynamics from free energy, dissipation, and input power, but deterministic rate laws alone do not identify fluctuations or chemical fuel consumption. We examine these distinctions for nonlinear reaction kinetics in active matter. Comparing Gaussian diffusion and Poisson reaction events clarifies when statistical fluctuations match a physical Rayleighian: the reaction dissipation potential must be consistent with counting statistics, local detailed balance links rate bias to chemical affinity, and kinetic scales remain constitutive inputs. Under these conditions, the normalized Rayleighian excess gives the leading rate-fluctuation cost in the frozen-state, many-event regime. Three models illustrate the consequences. Spatially uniform reactions exhibit protocol-dependent nonreciprocal response compatible with fixed-state OVP; different Rayleighian representations can select the same rate without specifying the same fluctuations. In an active emulsion, a finite fuel pool accounts for free-energy transfer and dissolution of a chemically maintained domain after replenishment stops. In a membrane-cytosol model, distinct reaction-channel realizations yield identical protein-density trajectories but different chemical input power. Under a separate kinetic assumption, an exact total-density equation still requires an initial rate and does not determine chemical work or fluctuations. These results clarify the physical and statistical inputs required for constructing reaction-transport models and interpreting their fluctuations.

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BibTeX
@misc{xu2026extended,
  title = {{Extended Onsager's variational principle for nonlinear chemical reaction kinetics in active matter}},
  author = {Xinpeng Xu and Changhao Li and Zhongqiang Xiong and Bin Zheng and Kento Yasuda and Shigeyuki Komura},
  howpublished = {arXiv},
  year = {2026},
  month = nov,
  doi = {10.48550/arxiv.2611.01131},
  eprint = {2611.01131},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2611.01131},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Extended Onsager's variational principle for nonlinear chemical reaction kinetics in active matter
AU  - Xinpeng Xu
AU  - Changhao Li
AU  - Zhongqiang Xiong
AU  - Bin Zheng
AU  - Kento Yasuda
AU  - Shigeyuki Komura
PY  - 2026
DA  - 2026/11/01
PB  - arXiv
DO  - 10.48550/arxiv.2611.01131
UR  - https://arxiv.org/abs/2611.01131
AB  - Onsager's variational principle (OVP) constructs dissipative dynamics from free energy, dissipation, and input power, but deterministic rate laws alone do not identify fluctuations or chemical fuel consumption. We examine these distinctions for nonlinear reaction kinetics in active matter. Comparing Gaussian diffusion and Poisson reaction events clarifies when statistical fluctuations match a physical Rayleighian: the reaction dissipation potential must be consistent with counting statistics, local detailed balance links rate bias to chemical affinity, and kinetic scales remain constitutive inputs. Under these conditions, the normalized Rayleighian excess gives the leading rate-fluctuation cost in the frozen-state, many-event regime. Three models illustrate the consequences. Spatially uniform reactions exhibit protocol-dependent nonreciprocal response compatible with fixed-state OVP; different Rayleighian representations can select the same rate without specifying the same fluctuations. In an active emulsion, a finite fuel pool accounts for free-energy transfer and dissolution of a chemically maintained domain after replenishment stops. In a membrane-cytosol model, distinct reaction-channel realizations yield identical protein-density trajectories but different chemical input power. Under a separate kinetic assumption, an exact total-density equation still requires an initial rate and does not determine chemical work or fluctuations. These results clarify the physical and statistical inputs required for constructing reaction-transport models and interpreting their fluctuations.
ER  -