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 →
6D Jansen-Rit single column (normal alpha) with additive noise σ=0.1. Noise regime: extreme (exploratory). Base problem: NMM.2. Runner injects noise via acceptance_criteria.noise_sigma.
Jansen & Rit (1995); Ableidinger et al. (2017)
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 _stable_expit(x):
"""Numerically stable sigmoid 1/(1+exp(-x)), scalar or array."""
x = np.asarray(x, dtype=float)
return np.where(
x >= 0,
1.0 / (1.0 + np.exp(-x)),
np.exp(x) / (1.0 + np.exp(x)),
)
def _jr_sigmoid(v, v_max=5.0, r=0.56, v0=6.0):
"""Jansen-Rit population sigmoid: S(v) = v_max / (1 + exp(r*(v0 - v)))."""
return v_max * _stable_expit(r * (v - v0))
def rhs(t: float, y: np.ndarray) -> np.ndarray:
x0, x1, x2, x3, x4, x5 = y
S_pyr = _jr_sigmoid(x1 - x2)
S_exc = _jr_sigmoid(C1 * x0)
S_inh = _jr_sigmoid(C3 * x0)
return np.array([
x3,
x4,
x5,
A * a * S_pyr - 2.0 * a * x3 - a2 * x0,
A * a * (p + C2 * S_exc) - 2.0 * a * x4 - a2 * x1,
B * b * C4 * S_inh - 2.0 * b * x5 - b2 * x2,
])Canonical 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: medium
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: Jansen-Rit normal alpha — noise σ=0.1 (extreme (exploratory)) (jansen-rit-normal-alpha-noise-0-1-extreme-exploratory)
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% | 8.4 | 23,249 | 235 ms | 0.819 |
| — | SciPy BDFSciPy | 0% | — | — | — | — |
| — | SciPy RadauSciPy | 0% | — | — | — | — |
| — | SciPy RK45SciPy | 0% | — | — | — | — |
| — | SciPy LSODASciPy | 0% | — | — | — | — |
| — | SciPy DOP853SciPy | 0% | — | — | — | — |
| — | SciPy RK23SciPy | 0% | — | — | — | — |
| — | CVODE BDFexternal | 0% | — | — | — | — |
| — | CVODE Adamsexternal | 0% | — | — | — | — |
| — | Tsit5external | 0% | — | — | — | — |
| — | Vern7external | 0% | — | — | — | — |
| — | Vern9external | 0% | — | — | — | — |
| — | TRBDF2external | 0% | — | — | — | — |
| — | FBDFexternal | 0% | — | — | — | — |
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_jansen_rit_normal_alpha_noise_0_1_extreme_exploratory_2026,
title = {Resonix Evidence Portal: Jansen-Rit normal alpha — noise σ=0.1 (extreme (exploratory))},
author = {{Resonix Labs (Canada) Inc.}},
year = {2026},
howpublished = {\url{https://resonix.tech/evidence/problems/jansen-rit-normal-alpha-noise-0-1-extreme-exploratory}},
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