Atomizer

Antoine/Atomizer

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Author	SHA1	Message	Date
Anto01	cb6b130908	feat(config): Add AtomizerSpec v2.0 schema and migrate all studies Added JSON Schema: - optimization_engine/schemas/atomizer_spec_v2.json Migrated 28 studies to AtomizerSpec v2.0 format: - Drone_Gimbal studies (1) - M1_Mirror studies (21) - M2_Mirror studies (2) - SheetMetal_Bracket studies (4) Each atomizer_spec.json is the unified configuration containing: - Design variables with bounds and expressions - Extractors (standard and custom) - Objectives and constraints - Optimization algorithm settings - Canvas layout information	2026-01-20 13:11:23 -05:00
Anto01	73a7b9d9f1	feat: Add dashboard chat integration and MCP server Major changes: - Dashboard: WebSocket-based chat with session management - Dashboard: New chat components (ChatPane, ChatInput, ModeToggle) - Dashboard: Enhanced UI with parallel coordinates chart - MCP Server: New atomizer-tools server for Claude integration - Extractors: Enhanced Zernike OPD extractor - Reports: Improved report generator New studies (configs and scripts only): - M1 Mirror: Cost reduction campaign studies - Simple Beam, Simple Bracket, UAV Arm studies Note: Large iteration data (2_iterations/, best_design_archive/) excluded via .gitignore - kept on local Gitea only. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>	2026-01-13 15:53:55 -05:00
Anto01	faa7779a43	feat: Add L-BFGS gradient optimizer for surrogate polish phase Implements gradient-based optimization exploiting MLP surrogate differentiability. Achieves 100-1000x faster convergence than derivative-free methods (TPE, CMA-ES). New files: - optimization_engine/gradient_optimizer.py: GradientOptimizer class with L-BFGS/Adam/SGD - studies/M1_Mirror/m1_mirror_adaptive_V14/run_lbfgs_polish.py: Per-study runner Updated docs: - SYS_14_NEURAL_ACCELERATION.md: Full L-BFGS section (v2.4) - 01_CHEATSHEET.md: Quick reference for L-BFGS usage - atomizer_fast_solver_technologies.md: Architecture context Usage: python -m optimization_engine.gradient_optimizer studies/my_study --n-starts 20 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>	2025-12-28 16:36:18 -05:00

Author

SHA1

Message

Date

Anto01

cb6b130908

feat(config): Add AtomizerSpec v2.0 schema and migrate all studies

Added JSON Schema:
- optimization_engine/schemas/atomizer_spec_v2.json

Migrated 28 studies to AtomizerSpec v2.0 format:
- Drone_Gimbal studies (1)
- M1_Mirror studies (21)
- M2_Mirror studies (2)
- SheetMetal_Bracket studies (4)

Each atomizer_spec.json is the unified configuration containing:
- Design variables with bounds and expressions
- Extractors (standard and custom)
- Objectives and constraints
- Optimization algorithm settings
- Canvas layout information

2026-01-20 13:11:23 -05:00

Anto01

73a7b9d9f1

feat: Add dashboard chat integration and MCP server

Major changes:
- Dashboard: WebSocket-based chat with session management
- Dashboard: New chat components (ChatPane, ChatInput, ModeToggle)
- Dashboard: Enhanced UI with parallel coordinates chart
- MCP Server: New atomizer-tools server for Claude integration
- Extractors: Enhanced Zernike OPD extractor
- Reports: Improved report generator

New studies (configs and scripts only):
- M1 Mirror: Cost reduction campaign studies
- Simple Beam, Simple Bracket, UAV Arm studies

Note: Large iteration data (2_iterations/, best_design_archive/)
excluded via .gitignore - kept on local Gitea only.

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

2026-01-13 15:53:55 -05:00

Anto01

faa7779a43

feat: Add L-BFGS gradient optimizer for surrogate polish phase

Implements gradient-based optimization exploiting MLP surrogate differentiability.
Achieves 100-1000x faster convergence than derivative-free methods (TPE, CMA-ES).

New files:
- optimization_engine/gradient_optimizer.py: GradientOptimizer class with L-BFGS/Adam/SGD
- studies/M1_Mirror/m1_mirror_adaptive_V14/run_lbfgs_polish.py: Per-study runner

Updated docs:
- SYS_14_NEURAL_ACCELERATION.md: Full L-BFGS section (v2.4)
- 01_CHEATSHEET.md: Quick reference for L-BFGS usage
- atomizer_fast_solver_technologies.md: Architecture context

Usage: python -m optimization_engine.gradient_optimizer studies/my_study --n-starts 20

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

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

2025-12-28 16:36:18 -05:00

3 Commits