feat: Add Zernike GNN surrogate module and M1 mirror V12/V13 studies
This commit introduces the GNN-based surrogate for Zernike mirror optimization and the M1 mirror study progression from V12 (GNN validation) to V13 (pure NSGA-II). ## GNN Surrogate Module (optimization_engine/gnn/) New module for Graph Neural Network surrogate prediction of mirror deformations: - `polar_graph.py`: PolarMirrorGraph - fixed 3000-node polar grid structure - `zernike_gnn.py`: ZernikeGNN with design-conditioned message passing - `differentiable_zernike.py`: GPU-accelerated Zernike fitting and objectives - `train_zernike_gnn.py`: ZernikeGNNTrainer with multi-task loss - `gnn_optimizer.py`: ZernikeGNNOptimizer for turbo mode (~900k trials/hour) - `extract_displacement_field.py`: OP2 to HDF5 field extraction - `backfill_field_data.py`: Extract fields from existing FEA trials Key innovation: Design-conditioned convolutions that modulate message passing based on structural design parameters, enabling accurate field prediction. ## M1 Mirror Studies ### V12: GNN Field Prediction + FEA Validation - Zernike GNN trained on V10/V11 FEA data (238 samples) - Turbo mode: 5000 GNN predictions → top candidates → FEA validation - Calibration workflow for GNN-to-FEA error correction - Scripts: run_gnn_turbo.py, validate_gnn_best.py, compute_full_calibration.py ### V13: Pure NSGA-II FEA (Ground Truth) - Seeds 217 FEA trials from V11+V12 - Pure multi-objective NSGA-II without any surrogate - Establishes ground-truth Pareto front for GNN accuracy evaluation - Narrowed blank_backface_angle range to [4.0, 5.0] ## Documentation Updates - SYS_14: Added Zernike GNN section with architecture diagrams - CLAUDE.md: Added GNN module reference and quick start - V13 README: Study documentation with seeding strategy 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
Antoine
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studies/m1_mirror_adaptive_V13/1_setup/optimization_config.json
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studies/m1_mirror_adaptive_V13/1_setup/optimization_config.json
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{
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"$schema": "Atomizer M1 Mirror NSGA-II Pure FEA Optimization V13",
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"study_name": "m1_mirror_adaptive_V13",
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"description": "V13 - Pure NSGA-II multi-objective optimization with FEA only. No surrogate. Seeds from V11+V12 FEA data.",
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"source_studies": {
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"v11": {
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"database": "../m1_mirror_adaptive_V11/3_results/study.db",
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"description": "V11 FEA trials (107 from V10 + V11)"
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},
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"v12": {
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"database": "../m1_mirror_adaptive_V12/3_results/study.db",
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"description": "V12 FEA trials from GNN validation"
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}
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},
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"design_variables": [
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{
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"name": "lateral_inner_angle",
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"expression_name": "lateral_inner_angle",
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"min": 25.0,
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"max": 28.5,
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"baseline": 26.79,
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"units": "degrees",
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"enabled": true
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},
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{
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"name": "lateral_outer_angle",
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"expression_name": "lateral_outer_angle",
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"min": 13.0,
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"max": 17.0,
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"baseline": 14.64,
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"units": "degrees",
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"enabled": true
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},
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{
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"name": "lateral_outer_pivot",
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"expression_name": "lateral_outer_pivot",
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"min": 9.0,
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"max": 12.0,
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"baseline": 10.40,
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"units": "mm",
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"enabled": true
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},
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{
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"name": "lateral_inner_pivot",
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"expression_name": "lateral_inner_pivot",
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"min": 9.0,
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"max": 12.0,
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"baseline": 10.07,
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"units": "mm",
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"enabled": true
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},
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{
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"name": "lateral_middle_pivot",
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"expression_name": "lateral_middle_pivot",
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"min": 18.0,
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"max": 23.0,
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"baseline": 20.73,
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"units": "mm",
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"enabled": true
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},
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{
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"name": "lateral_closeness",
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"expression_name": "lateral_closeness",
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"min": 9.5,
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"max": 12.5,
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"baseline": 11.02,
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"units": "mm",
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"enabled": true
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},
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{
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"name": "whiffle_min",
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"expression_name": "whiffle_min",
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"min": 35.0,
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"max": 55.0,
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"baseline": 40.55,
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"units": "mm",
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"enabled": true
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},
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{
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"name": "whiffle_outer_to_vertical",
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"expression_name": "whiffle_outer_to_vertical",
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"min": 68.0,
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"max": 80.0,
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"baseline": 75.67,
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"units": "degrees",
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"enabled": true
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},
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{
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"name": "whiffle_triangle_closeness",
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"expression_name": "whiffle_triangle_closeness",
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"min": 50.0,
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"max": 65.0,
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"baseline": 60.00,
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"units": "mm",
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"enabled": true
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},
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{
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"name": "blank_backface_angle",
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"expression_name": "blank_backface_angle",
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"min": 4,
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"max": 5.0,
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"baseline": 4.23,
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"units": "degrees",
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"enabled": true
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},
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{
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"name": "inner_circular_rib_dia",
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"expression_name": "inner_circular_rib_dia",
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"min": 480.0,
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"max": 620.0,
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"baseline": 534.00,
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"units": "mm",
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"enabled": true
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}
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],
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"objectives": [
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{
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"name": "rel_filtered_rms_40_vs_20",
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"description": "Filtered RMS WFE at 40 deg relative to 20 deg reference (operational tracking)",
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"direction": "minimize",
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"weight": 5.0,
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"target": 4.0,
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"units": "nm",
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"extractor_config": {
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"target_subcase": "3",
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"reference_subcase": "2",
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"metric": "relative_filtered_rms_nm"
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}
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},
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{
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"name": "rel_filtered_rms_60_vs_20",
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"description": "Filtered RMS WFE at 60 deg relative to 20 deg reference (operational tracking)",
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"direction": "minimize",
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"weight": 5.0,
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"target": 10.0,
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"units": "nm",
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"extractor_config": {
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"target_subcase": "4",
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"reference_subcase": "2",
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"metric": "relative_filtered_rms_nm"
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}
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},
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{
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"name": "mfg_90_optician_workload",
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"description": "Manufacturing deformation at 90 deg polishing (J1-J3 filtered RMS)",
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"direction": "minimize",
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"weight": 1.0,
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"target": 20.0,
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"units": "nm",
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"extractor_config": {
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"target_subcase": "1",
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"reference_subcase": "2",
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"metric": "relative_rms_filter_j1to3"
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}
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}
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],
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"zernike_settings": {
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"n_modes": 50,
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"filter_low_orders": 4,
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"displacement_unit": "mm",
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"subcases": ["1", "2", "3", "4"],
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"subcase_labels": {"1": "90deg", "2": "20deg", "3": "40deg", "4": "60deg"},
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"reference_subcase": "2"
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},
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"nsga2_settings": {
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"population_size": 20,
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"n_generations": 50,
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"crossover_prob": 0.9,
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"mutation_prob": 0.1,
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"seed_from_prior": true
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},
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"nx_settings": {
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"nx_install_path": "C:\\Program Files\\Siemens\\NX2506",
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"sim_file": "ASSY_M1_assyfem1_sim1.sim",
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"solution_name": "Solution 1",
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"op2_pattern": "*-solution_1.op2",
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"simulation_timeout_s": 600,
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"journal_timeout_s": 120,
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"op2_timeout_s": 1800,
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"auto_start_nx": true
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},
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"dashboard_settings": {
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"trial_source_tag": true,
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"fea_marker": "circle",
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"fea_color": "#4CAF50"
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}
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}
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