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Update notebook defaults and handle damping roundoff - #7
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Publish the selected notebook defaults: neural Hamiltonians, polynomial damping-library selection, and 1,000/100 full/refit updates. The two-mass example now defaults to state-dependent damping with known gain and 20-unit trajectories; the circuit retains constant damping, learned gain and five-unit trajectories. Clear saved execution outputs from the public notebooks.
A successful bounded regression can return a tiny negative damping coefficient due to floating-point roundoff, which previously prevented model construction. Clamp only roundoff-sized negative damping values to zero; reject larger violations and preserve the original solver diagnostics and unsuccessful status.
Validation: the new regression tests fail on the old code and pass with the fix. Full suite: 124 passed, 115 subtests passed, 4 skipped. Ruff passed. Both notebooks completed all cells using the selected model components and complete pruning grids with temporary 0.2-duration and one-update/refit software-check limits. These checks do not assess the full default fitting runs.