No clear winner. The survival gap is under 10 percentage points and the balanced-score gap is under 0.05, so neither SolvSRK nor the best baseline clears the win threshold. Either works — choose on cost, licensing, or integration effort. All verdicts →
100-node coupled FHN on Erdős-Rényi graph; dim=200; synchrony and population dynamics
Canonical benchmark implementation
Canonical RHS excerpt from the registered callable used for this benchmark cell. Expand it to verify the state equations; it is not a standalone runnable fixture.
def rhs(t: float, y: np.ndarray) -> np.ndarray:
v = y[0::2]
w = y[1::2]
dy = np.empty(dim)
# Coupling term: mean-field diffusive coupling
coupling = coupling_strength * adj.dot(v)
dv = v - v**3 / 3.0 - w + I_ext + coupling
dw = (v + a - b * w) / tau
dy[0::2] = dv
dy[1::2] = dw
return dyCanonical RHS excerpt captured from the same registered callable used for the published benchmark. Frozen closure values are summarized below; helper imports and solver settings are intentionally omitted.
Fingerprint
Spread: high
Default noise: none
Recommendation snapshot
Clean best: SolvSRK
Noisy best: SciPy BDF
Coverage
14 solver arms · clean + 5 noise levels
Ranked on survival, precision, and speed
20 seeds/cell default · 14 arms · TRL 4–5 · simulation-lab validated · this page: FitzHugh-Nagumo network (N=100) (fitzhugh-nagumo-network-n-100)
Governed SolvTune benchmark freeze; per-arm medians only. RHS definitions and raw trial rows are not published.
Self-reported by Resonix Labs · not independently verified
Pick an objective and a noise level to rank all arms on survival, median SCD, median nfev, and median wall time. Medians across seeds.
Objective
Best overall trade-off of survival, precision, and speed.
Noise level
| # | Solver | Survival | SCD | nfev | Wall | Score |
|---|---|---|---|---|---|---|
| 1 | SolvSRK | 100% | 12.2 | 16,491 | 790 ms | 0.909 |
| 2 | Vern7external | 100% | 9.6 | 3,642 | 3.46 s | 0.848 |
| 3 | SciPy RadauSciPy | 100% | 9.6 | 24,177 | 456 ms | 0.847 |
| 4 | Vern9external | 100% | 9.4 | 5,154 | 3.75 s | 0.843 |
| 5 | SciPy LSODASciPy | 100% | 8.5 | 3,681 | 65 ms | 0.822 |
| 6 | CVODE Adamsexternal | 100% | 8.4 | 4,239 | 105 ms | 0.819 |
| 7 | SciPy BDFSciPy | 100% | 8.1 | 4,605 | 138 ms | 0.811 |
| 8 | FBDFexternal | 100% | 7.9 | 2,464 | 4.08 s | 0.808 |
| 9 | TRBDF2external | 100% | 7.8 | 9,749 | 5.50 s | 0.805 |
| 10 | CVODE BDFexternal | 100% | 7.7 | 3,963 | 97 ms | 0.803 |
| 11 | Tsit5external | 100% | 7.3 | 3,012 | 731 ms | 0.792 |
| 12 | SciPy RK45SciPy | 100% | 7.1 | 3,308 | 62 ms | 0.788 |
| 13 | SciPy DOP853SciPy | 100% | 7.1 | 2,882 | 53 ms | 0.787 |
| 14 | SciPy RK23SciPy | 100% | 7.0 | 7,130 | 135 ms | 0.785 |
At Clean, best balanced arm is SolvSRK.
Values are medians across seeds, measured by Resonix Labs on Resonix hardware and not independently verified; nfev and wall are on reference lab hardware (indicative). Under injected noise only SolvSRK and the SciPy arms are run. How we measure accuracy → · Verification status →
SolvScout · free
This page shows one published benchmark cell. SolvScout fingerprints your ODE, compares it to the full corpus, and recommends a solver with the same survival / precision / speed ranking you see here — including when a SciPy arm wins.
SolvSRK · 30-day trial
SolvSRK is the stiffness-adaptive integrator behind the SolvSRK column in these tables. Create an account, activate a machine, and take a 30-day trial — same binary you'd ship after purchase.
Replace the access date. Pin the freeze ID and library versions when comparing against a later export. Cite it as what it is — a self-reported vendor benchmark, not an independently verified result. The note field says so; please keep it.
@misc{resonix_evidence_fitzhugh_nagumo_network_n_100_2026,
title = {Resonix Evidence Portal: FitzHugh-Nagumo network (N=100)},
author = {{Resonix Labs (Canada) Inc.}},
year = {2026},
howpublished = {\url{https://resonix.tech/evidence/problems/fitzhugh-nagumo-network-n-100}},
note = {Self-reported vendor benchmark; internally generated by Resonix Labs and not independently verified. Accessed YYYY-MM-DD. Freeze 2026-08-13; libsolvsrk 2.3.0; SciPy 1.14.}
}TRL 4–5 · simulation-lab validated · 398 problems · 14 solver arms · clean + 5 noise levels
Freeze: 2026-08-13 · scipy 1.14 · libsolvsrk 2.3.0 · Methodology
Self-reported by Resonix Labs · not independently verified · Verification status