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 →
The classic chaotic three-state system. Terminal accuracy is intrinsically capped by sensitive dependence, so low SCD here is expected — this is a parity case, not a failure.
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 _lorenz_rhs(t, y, sigma=10.0, rho=28.0, beta=8.0/3.0):
x, z, w = y
return np.array([sigma * (z - x), x * (rho - w) - z, x * z - beta * w])
def rhs(t, y):
return _lorenz_rhs(t, y)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: low
Default noise: clean
Recommendation snapshot
Clean best: Vern9 (precision)
Noisy best: parity
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: Lorenz attractor (lorenz)
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 | Vern9external | 100% | 5.1 | 9,618 | 4.01 s | 0.740 |
| 2 | SciPy RadauSciPy | 100% | 4.3 | 53,508 | 978 ms | 0.722 |
| 3 | Vern7external | 100% | 4.2 | 11,592 | 4.11 s | 0.719 |
| 4 | SolvSRK | 100% | 4.0 | 28,944 | 75 ms | 0.715 |
| 5 | SciPy DOP853SciPy | 100% | 2.7 | 8,186 | 48 ms | 0.683 |
| 6 | Tsit5external | 100% | 2.4 | 13,152 | 1.76 s | 0.676 |
| 7 | SciPy LSODASciPy | 100% | 1.7 | 6,281 | 25 ms | 0.660 |
| 8 | SciPy RK45SciPy | 100% | 1.7 | 13,436 | 88 ms | 0.659 |
| 9 | SciPy BDFSciPy | 100% | 1.6 | 15,024 | 464 ms | 0.657 |
| 10 | CVODE Adamsexternal | 100% | 1.3 | 4,206 | 37 ms | 0.649 |
| 11 | FBDFexternal | 100% | 0.9 | 11,323 | 5.19 s | 0.641 |
| 12 | TRBDF2external | 100% | 0.7 | 46,137 | 5.69 s | 0.636 |
| 13 | SciPy RK23SciPy | 100% | 0.6 | 78,866 | 654 ms | 0.633 |
| 14 | CVODE BDFexternal | 100% | 0.0 | 6,335 | 53 ms | 0.619 |
At Clean, best balanced arm is Vern9 · SolvSRK survival 100%, SCD 4.0.
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_lorenz_2026,
title = {Resonix Evidence Portal: Lorenz attractor},
author = {{Resonix Labs (Canada) Inc.}},
year = {2026},
howpublished = {\url{https://resonix.tech/evidence/problems/lorenz}},
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