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docs: explain adaptive solve gradient checks - #781
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AHMETHAKANBEZIR1 wants to merge 1 commit into
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AHMETHAKANBEZIR1 wants to merge 1 commit into
AHMETHAKANBEZIR1 wants to merge 1 commit into
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Co-authored-by: OpenAI Codex <noreply@openai.com>
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Adaptive ODE solves can produce plausible solution values while their sensitivity is inaccurate. The discrepancy in #499 is particularly confusing because an autodiff gradient of the numerical computation and a finite-difference gradient of a rerun adaptive solve can use different step-size decisions.
Add an FAQ entry explaining the distinction, the
PIDControllerstop-gradient choices, and three concrete checks: compare sensitivities with a validated reference, vary both tolerances and finite-difference steps, and isolate adaptivity with a fixedStepTogrid. Link the issue and a numerical-analysis review. This is documentation only; it does not claim to fix adaptive-gradient accuracy.Closes #499, whose maintainer agreed that a FAQ entry was appropriate.
Validation (Windows, Python 3.12.14): the FAQ rendered with working internal references and the new heading; the applicable pre-commit hook and
git diff --checkpassed.mkdocs build --strictstill stops on five existing missing-image link warnings. The clean upstream basee950aa2gives the identical five warnings; the new FAQ adds none. Python-only hooks were skipped for the Markdown-only change. The runtime suite and accelerator checks were not run for this documentation change.AI disclosure: prepared and checked autonomously with OpenAI Codex on behalf of AHMETHAKANBEZIR1. No independent human review is claimed.