What question did this study set out to answer?

This research investigates the dynamics of synchronization in FitzHugh-Nagumo networks on scale-free topologies.

May 4, 20260 citationsOpen Access

Sustained Attractor Diversity in Doubt-Modulated FitzHugh--Nagumo Networks: Spectral Dead Zone and Chimera States on Scale-Free Topologies

JCJulien ChauvinCommissariat à l'Énergie Atomique et aux Énergies Alternatives

Key Points

This research investigates the dynamics of synchronization in FitzHugh-Nagumo networks on scale-free topologies.
Systematic adversarial review of results on spectral dead zone and chimera states.
Analyses include logistic regression, correlation assessments, and validation via hardware testing (ngspice).
Implementation of +985% synchrony surge through anti-synchronization filter ablation.
Spectral dead zone identified with λ₂_crit = 2.31, indicating functional/collapsed regimes.
Peripheral forcing achieved +1.20 bits improvement over hub forcing (+0.21 bits).
Chimera states show distinct mechanistic differences from previous models (R=0.141 vs R=0.766).

Abstract

V4. 0. 0 — Audited Stable (2 May 2026) This release formalizes the V4 scientific results following systematic adversarial review. Key findings: Spectral dead zone: λ₂crit = 2. 31 separates functional and collapsed regimes (logistic regression, 100% accuracy, n=36) u = anti-synchronization filter: FROZENU ablation produces +985% synchrony surge (factor ×10. 9) Topological intelligence: hub trajectory complexity correlates with degree (r=−0. 716, p=1. 29e−79) Event-driven phase transition: peripheral forcing outperforms hub forcing (+1. 20 vs +0. 21 bits) Chimera states mechanistically distinct from Abrams-Strogatz 2004 (R=0. 141 vs R=0. 766) Hardware validation: Dead zone confirmed in SPICE (ngspice 46), BA m=5, N=64, 50 seeds — 3. 1× ratio. Test suite: 84 automated tests — 0 failures. Companion document: Results Compendium (COMPENDIUM. pdf) — 4-page typeset brief covering all findings, robustness experiments, and reproduction instructions. GitHub: https: //github. com/cafe-virtuel/Mem4ristor

Ask AI

Helpful

Bookmark

View Full Paper