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๐Ÿ”ฌ GRIN Fixture Auto-Calibration Framework

xPRIMEray / GD_xPRIMEray โ€“ Engineering Study Architecture


๐Ÿง  Purpose

Establish a repeatable, measurable, and automatable framework for:

  • Characterizing GrinFilmCamera behavior
  • Defining valid parameter operating regions
  • Enabling Codex-assisted execution
  • Progressing toward auto-calibration of GRIN ray paths

This document defines the A / B / C execution model and integrates it into the broader xPRIMEray architecture.


๐Ÿงฑ Core Philosophy

We are not just rendering.

We are building a:

Controlled optical laboratory inside the renderer

Where: - Scenes = fixtures - Rays = measurable signals - Parameters = controllable inputs - Logs = instrumentation - Codex = execution + analysis agent


๐Ÿ”บ A / B / C Framework

A โ€” Safe Execution Harness (Operations Layer)

Goal

Enable deterministic, bounded, reproducible test execution.

Requirements

  • Fixed entrypoint script(s)
  • Controlled scenes only
  • Non-destructive commands
  • Predictable output directory
  • Codex-friendly interface

Example Entry Script

/scripts/run_fixture_baseline.sh

Responsibilities

  • Load fixture scene
  • Apply parameter set
  • Run renderer in bounded mode
  • Emit logs to structured location

B โ€” Measurement & Logging Layer (Signal Layer)

Goal

Convert ray behavior into quantifiable engineering metrics

Required Metrics (Initial Set)

  • Hit Success Rate
  • Miss / Divergence Rate
  • Bend Angle Distribution
  • Radial Deviation
  • Final Intercept Error
  • Path Smoothness (oscillation detection)
  • Symmetry Error (if applicable)

Output Format

/output/fixture_runs/{timestamp}/
  โ”œโ”€โ”€ params.json
  โ”œโ”€โ”€ ray_log.txt
  โ”œโ”€โ”€ metrics.json
  โ””โ”€โ”€ summary.txt

Key Principle

If it cannot be measured, it cannot be calibrated.


C โ€” Codex Execution Workflow (Integration Layer)

Goal

Enable Codex to act as a controlled engineering operator

Standard Interaction Pattern

  1. Show command
  2. Confirm non-destructive
  3. Execute
  4. Summarize results

Example Prompt Pattern

Run the GRIN fixture baseline.
Show command first, then execute, then summarize metrics.

Responsibilities

  • Execute harness scripts
  • Parse output artifacts
  • Compare runs
  • Suggest parameter adjustments

๐Ÿงช Fixture-Based Characterization

Definition

A fixture is a controlled scene designed to test specific GRIN behaviors.

Fixture Components

  • Known emitter position
  • Known target surface or region
  • Defined GRIN field
  • Expected ray behavior

Example Fixture Types

  • Radial focusing lens
  • Symmetric field test
  • Wormhole throat proxy
  • Flat-to-curved transition field

๐Ÿ“Š Phase Plan

Phase 1 โ€” Baseline Harness (A)

Deliverables

  • One fixture scene
  • One execution script
  • Basic logging

Success Criteria

  • Codex can run fixture without errors
  • Output artifacts generated consistently

Phase 2 โ€” Metric Instrumentation (B-lite)

Deliverables

  • Core metric extraction
  • Structured metrics.json

Success Criteria

  • Runs produce comparable numeric outputs
  • Basic pass/fail thresholds definable

Phase 3 โ€” Comparative Analysis (B-full)

Deliverables

  • Run-to-run comparison tooling
  • Delta reporting

Success Criteria

  • Detect parameter sensitivity
  • Identify stable vs unstable regions

Phase 4 โ€” Codex Workflow Integration (C)

Deliverables

  • Codex-compatible script interface
  • Standardized prompt templates

Success Criteria

  • Codex can execute + summarize runs reliably

Phase 5 โ€” Parameter Sweep Engine

Deliverables

  • Controlled parameter sweeps
  • Multi-run aggregation

Success Criteria

  • Parameter space begins forming stability maps

Phase 6 โ€” Calibration Engine

Deliverables

  • Optimization loop
  • Objective function (error minimization)

Success Criteria

  • Identify best-fit parameter sets for fixture

Phase 7 โ€” Auto-Calibration

Deliverables

  • Fully automated loop:
  • run โ†’ evaluate โ†’ adjust โ†’ repeat

Success Criteria

  • System converges to valid GRIN configurations autonomously

๐Ÿง  Architectural Integration

This framework connects to:

  • RayBeamRenderer โ†’ ray path generation
  • GrinFilmCamera โ†’ parameter control surface
  • FieldSource3D โ†’ GRIN field definition
  • Future: ResearchModeConfig

๐Ÿ”ฎ Long-Term Vision

A system where:

  • Any fixture can be loaded
  • Codex executes a test suite
  • Metrics are generated automatically
  • Optimal parameters are proposed

Resulting in:

A self-characterizing optical simulation engine


โšก Immediate Next Step

Implement:

  1. First fixture scene
  2. Single execution script
  3. Minimal metrics output

Then validate with Codex execution.


๐Ÿงฌ Tagline

We are not tuning parameters manually.

We are teaching the system how to understand itself.


๐Ÿš€ End of Document