Heston stochastic-volatility PDE after MOL (S x v tensor grid)
DISADVANTAGES2 · dim 741A baseline wins. At the comparison noise level, the best baseline beats SolvSRK by at least 10 percentage points of survival, or by at least 0.05 balanced score when survival is tied. Use the winning baseline named on the problem page - not SolvSRK. All verdicts →
741D MOL discretisation of the Heston backward PDE on a 41x21 log-S x v tensor grid. Per-node coefficients depend on v but are constant in tau -- LRDE row-1 GREEN.
Problem definition
Heston 1993
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.
Show canonical RHS excerpt
def rhs(t: float, y: np.ndarray) -> np.ndarray:
return A_csr @ y + g_arr- Parameters
- A_csr = sparse_matrix(shape=(741, 741), nnz=6105)
- g_arr = repeat(0, 741) [shape=(741,)]
- Initial condition
- y(0) = [0, 0, 0, 0, 0, 0, …] [shape=(741,), min=0, max=353.414865059]
- Horizon
- t ∈ [0, 0.5]
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: none
Recommendation snapshot
Clean best: SolvSRK
Noisy best: SciPy RK45
Coverage
14 solver arms · clean + 5 noise levels
Ranked on survival, precision, and speed
Versions & freeze
Methodology →- Freeze
- 2026-08-13
- libsolvsrk
- 2.3.0
- SciPy
- 1.14
- SUNDIALS
- CVODE (bundled backend)
20 seeds/cell default · 14 arms · TRL 4–5 · simulation-lab validated · this page: Heston stochastic-volatility PDE after MOL (S x v tensor grid) (heston-stochastic-volatility-pde-after-mol-s-x-v-tensor-grid)
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
Results matrix
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% | 11.0 | 10,301 | 1.46 s | 0.880 |
| 2 | SciPy RadauSciPy | 100% | 10.7 | 3,103 | 503 ms | 0.874 |
| 3 | SciPy DOP853SciPy | 100% | 10.0 | 302 | 3 ms | 0.858 |
| 4 | SciPy LSODASciPy | 100% | 8.6 | 1,827 | 22 ms | 0.824 |
| 5 | SciPy RK45SciPy | 100% | 8.6 | 344 | 3 ms | 0.823 |
| 6 | CVODE Adamsexternal | 100% | 8.1 | 3,224 | 150 ms | 0.811 |
| 7 | Tsit5external | 100% | 8.1 | 312 | 659 ms | 0.811 |
| 8 | CVODE BDFexternal | 100% | 7.8 | 3,174 | 96 ms | 0.806 |
| 9 | SciPy BDFSciPy | 100% | 7.7 | 1,803 | 201 ms | 0.802 |
| 10 | SciPy RK23SciPy | 100% | 7.6 | 1,046 | 11 ms | 0.800 |
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 →
Cite this page
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_heston_stochastic_volatility_pde_after_mol_s_x_v_tensor_grid_2026,
title = {Resonix Evidence Portal: Heston stochastic-volatility PDE after MOL (S x v tensor grid)},
author = {{Resonix Labs (Canada) Inc.}},
year = {2026},
howpublished = {\url{https://resonixusa.com/evidence/problems/heston-stochastic-volatility-pde-after-mol-s-x-v-tensor-grid}},
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.}
}Related
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