2405.03861
Homeostasis in Input-Output Networks: Structure, Classification and Applications
Fernando Antoneli, Martin Golubitsky, Jiaxin Jin, Ian Stewart
correctmedium confidence
- Category
- Not specified
- Journal tier
- Strong Field
- Processed
- Sep 28, 2025, 12:56 AM
- arXiv Links
- Abstract ↗PDF ↗
Audit review
The paper’s Theorem 4.12 classifies 3‑node input = output core networks into Family 1 (appendage ρ ⇌ σ) with det(H) = f_{σ,x_σ} f_{ρ,x_ρ} − f_{σ,x_ρ} f_{ρ,x_σ}, and Family 2 (two appendage path components) with det(H) = f_{σ,x_σ} f_{ρ,x_ρ}, concluding that homeostasis arises by null‑degradation in Family 2 and either by null‑degradation or 2‑node appendage cancellation in Family 1. This matches the candidate’s derivation exactly, including the use of the derivative criterion x′ ∝ det(H) under f_{ι,ℑ} ≠ 0 and det(J) ≠ 0. See the input‑output derivative formula and homeostasis criterion (2.21) and the input=output specialization of the homeostasis matrix, together with Theorem 4.12 and Example 4.4.
Referee report (LaTeX)
\textbf{Recommendation:} minor revisions \textbf{Journal Tier:} strong field \textbf{Justification:} The paper presents a correct, clean, and useful classification of infinitesimal homeostasis mechanisms in input-output networks, with transparent determinant-based criteria tied directly to network topology. The 3-node input = output classification (Family 1 vs Family 2) is especially crisp and matches independent reasoning. A few small clarifications (e.g., an explicit input = output derivative formula and a compact summary table) would further improve accessibility.