Support jump rate laws in the CLE#1436
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isaacsas merged 7 commits intoSciML:masterfrom Mar 19, 2026
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Add `use_jump_ratelaws=false` kwarg to `sde_model`, `hybrid_model`, `SDEProblem`, and `HybridProblem`. When true, CLE noise (diffusion) coefficients use jump rate laws (binomials) instead of ODE rate laws (powers) inside sqrt(|ratelaw|), giving more mathematically correct noise intensity for integer populations. Only affects noise terms, not drift. First-order reactions are identical under both settings. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Directly evaluate Catalyst-generated drift and diffusion functions at multiple state values and compare against hand-coded formulas for both ODE and jump rate law noise. This is deterministic and avoids flaky statistical sampling. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The CLE derived from the CME uses the same stochastic propensity a_j(X) in both drift and diffusion terms. The previous implementation only switched diffusion; this makes the kwarg affect drift too for physical consistency. Also removes the drift_scales hack by widening the assemble_oderhs filter to accept both ODE and SDE scale reactions, adds the kwarg to ode_model/ODEProblem, and adds a statistical test comparing Catalyst output against a hand-coded reference SDE. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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