MycoNet: A Python Framework for Mycorrhizal Network Biophysics — Algorithms, Simulation, and Validation of the Freiman–Villani Efficiency Bounds
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| Natura: | Recurso digital |
| Lingua: | inglese |
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2026
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| author | Mercier des Rochettes, Bertrand |
| author_facet | Mercier des Rochettes, Bertrand |
| contents | <p>MycoNet is an open-source Python package for simulating mycorrhizal network biophysics within the Freiman-Villani thermodynamic framework. The package implements four core algorithms: (1) the local Freiman index via k-nearest-neighbour sampling and hex-integer FFT Minkowski sum, recovering K_hex = 19/7 exactly on the hexagonal lattice; (2) stochastic hyphal growth with Fokker-Planck nutrient transport; (3) Wasserstein W2 distance via log-domain Sinkhorn (POT); and (4) metabolic dissipation via Fisher information. Under simulated drought stress, sigma_r rises from 3.1 to 4.6 and dissipation increases by factor ~24, consistent with the Theorem 6.1 lower bound Psi >= C* D eps^{-2} (sigma_r - K_hex)^2 with C_sim = 20.9 vs C* = 21.8 (4% agreement). The companion theory paper is submitted to the Journal of Mathematical Biology.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20342304 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | MycoNet: A Python Framework for Mycorrhizal Network Biophysics — Algorithms, Simulation, and Validation of the Freiman–Villani Efficiency Bounds Mercier des Rochettes, Bertrand mycorrhizal networks Freiman index optimal transport Wasserstein distance Fokker-Planck mathematical biology Python <p>MycoNet is an open-source Python package for simulating mycorrhizal network biophysics within the Freiman-Villani thermodynamic framework. The package implements four core algorithms: (1) the local Freiman index via k-nearest-neighbour sampling and hex-integer FFT Minkowski sum, recovering K_hex = 19/7 exactly on the hexagonal lattice; (2) stochastic hyphal growth with Fokker-Planck nutrient transport; (3) Wasserstein W2 distance via log-domain Sinkhorn (POT); and (4) metabolic dissipation via Fisher information. Under simulated drought stress, sigma_r rises from 3.1 to 4.6 and dissipation increases by factor ~24, consistent with the Theorem 6.1 lower bound Psi >= C* D eps^{-2} (sigma_r - K_hex)^2 with C_sim = 20.9 vs C* = 21.8 (4% agreement). The companion theory paper is submitted to the Journal of Mathematical Biology.</p> |
| title | MycoNet: A Python Framework for Mycorrhizal Network Biophysics — Algorithms, Simulation, and Validation of the Freiman–Villani Efficiency Bounds |
| topic | mycorrhizal networks Freiman index optimal transport Wasserstein distance Fokker-Planck mathematical biology Python |
| url | https://doi.org/10.5281/zenodo.20342304 |