feat: Major update - Physics docs, Zernike OPD, insights, NX journals, tools

Documentation:
- Add docs/06_PHYSICS/ with Zernike fundamentals and OPD method docs
- Add docs/guides/CMA-ES_EXPLAINED.md optimization guide
- Update CLAUDE.md and ATOMIZER_CONTEXT.md with current architecture
- Update OP_01_CREATE_STUDY protocol

Planning:
- Add DYNAMIC_RESPONSE plans for random vibration/PSD support
- Add OPTIMIZATION_ENGINE_MIGRATION_PLAN for code reorganization

Insights System:
- Update design_space, modal_analysis, stress_field, thermal_field insights
- Improve error handling and data validation

NX Journals:
- Add analyze_wfe_zernike.py for Zernike WFE analysis
- Add capture_study_images.py for automated screenshots
- Add extract_expressions.py and introspect_part.py utilities
- Add user_generated_journals/journal_top_view_image_taking.py

Tests & Tools:
- Add comprehensive Zernike OPD test suite
- Add audit_v10 tests for WFE validation
- Add tools for Pareto graphs and mirror data extraction
- Add migrate_studies_to_topics.py utility

Knowledge Base:
- Initialize LAC (Learning Atomizer Core) with failure/success patterns

Dashboard:
- Update Setup.tsx and launch_dashboard.py
- Add restart-dev.bat helper script

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

atomizer-dashboard/frontend/src/pages/Setup.tsx

@@ -155,9 +155,9 @@ export default function Setup() {
         })),
         algorithm: {
           name: rawConfig.optimizer?.name || rawConfig.algorithm?.name || 'Optuna',
-          sampler: rawConfig.optimization_settings?.sampler || rawConfig.algorithm?.sampler || 'TPESampler',
+          sampler: rawConfig.optimization?.algorithm || rawConfig.optimization_settings?.sampler || rawConfig.algorithm?.sampler || 'TPESampler',
           pruner: rawConfig.optimization_settings?.pruner || rawConfig.algorithm?.pruner,
-          n_trials: rawConfig.optimization_settings?.n_trials || rawConfig.trials?.n_trials || selectedStudy.progress.total,
+          n_trials: rawConfig.optimization?.n_trials || rawConfig.optimization_settings?.n_trials || rawConfig.trials?.n_trials || selectedStudy.progress.total,
           timeout: rawConfig.optimization_settings?.timeout
         },
         fea_model: rawConfig.fea_model || rawConfig.solver ? {