Update UQ and VnV TODO files: add new tasks for uncertainty quantification, validation, and mission rehearsal; enhance progress log and technical documentation

Author: arcticoder

UQ-TODO.ndjson

@@ -1,3 +1,6 @@
+{"title":"UQ: metamaterial amplification factor uncertainty","description":"Quantify uncertainty in 10^4× amplification; model dispersion/absorption; propagate to required P_peak and E_total.","type":"analysis","severity":70,"category":"cross_system_coupling","impact":"If lower than expected, energy budget may not close."}
+{"title":"UQ: laser coherence factor validation","description":"Validate assumed ~100× energy reduction via coherence control (injection locking/phase conjugation) under plasma conditions; provide confidence intervals.","type":"validation","severity":60,"category":"coherence_control","impact":"Overestimation increases battery requirement."}
+{"title":"UQ: discharge efficiency vs. power profile","description":"Propagate discharge efficiency model vs C-rate across the 30 s ramps; quantify impact on E_effective and feasibility margins.","type":"analysis","severity":55,"category":"system_performance","impact":"Lower efficiency reduces available energy; may exceed capacity."}
 {"title": "Multi-Objective Optimization Trade-offs", "description": "Trade-offs between energy requirements, stability, and travel speed in warp bubble design are not well characterized. Pareto frontiers need systematic exploration.", "type": "theoretical", "severity": 65, "category": "design_trade_offs", "impact": "May not find optimal balance between competing design requirements"}
 {"title": "Constraint Handling in High-Dimensional Space", "description": "Physical constraints (energy conditions, causality, etc.) create complex boundaries in high-dimensional parameter space that may not be properly handled by optimization algorithms.", "type": "in silico", "severity": 60, "category": "constraint_satisfaction", "impact": "Could produce solutions that violate physical constraints"}
 {"title": "Local Minima Escape Strategies", "description": "Optimization landscape may contain many local minima that trap standard algorithms. Need robust global optimization strategies.", "type": "in silico", "severity": 55, "category": "global_optimization", "impact": "May miss significantly better solutions trapped in local minima"}

VnV-TODO.ndjson

@@ -1,3 +1,12 @@
+{"category":"V&V","task":"HIL: end-to-end power draw within 10% of model","priority":"High","source_file":"src/supraluminal_prototype/power.py","source_snippet":"def compute_smearing_energy","python_snippet":"# Placeholder integration note: compare logged P(t) vs model over ramp/cruise/ramps; compute MAPE and assert <10%"}
+{"category":"V&V","task":"Closed-loop phase stability > 6 dB margin","priority":"High","source_file":"src/supraluminal_prototype/control.py","source_snippet":"def sync_rings","python_snippet":"# Placeholder: derive loop transfer L(jw) and ensure |L| margin > 6 dB at crossover; assert margin_db >= 6"}
+{"category":"V&V","task":"Dry-run mission rehearsal with simulated telemetry","priority":"Medium","source_file":"scripts/mission_rehearsal.py","source_snippet":"def run_rehearsal","python_snippet":"# Placeholder: run dry-run generating synthetic telemetry; assert key event timestamps within planned windows"}
+{"category":"Docs/Process","task":"Traceability: link roadmap items to tests","priority":"High","source_file":"docs/roadmap.ndjson","source_snippet":"associated_tasks","python_snippet":"# Scriptable check: for each associated_tasks title, ensure a matching line exists in VnV-TODO.ndjson/UQ-TODO.ndjson/tests"}
+{"category":"Docs/Process","task":"Finalize requirements spec v1.0","priority":"High","source_file":"docs/requirements.md","source_snippet":"Mission requirements","python_snippet":"# Placeholder: validate document completeness checklist; assert all MUST-level items present"}
+{"category":"Safety","task":"Safety checklist v0.9","priority":"High","source_file":"docs/safety_checklist.md","source_snippet":"Safe ramp abort and quench procedures","python_snippet":"# Placeholder: validate presence of abort criteria, watchdogs, thermal margins"}
+{"category":"V&V","task":"V&V: coil ramp linearity and hysteresis","priority":"Medium","source_file":"src/supraluminal_prototype/hardware.py","source_snippet":"class CoilDriver","python_snippet":"from src.supraluminal_prototype.hardware import CoilDriver\ndrv = CoilDriver(max_current=5000.0, hysteresis=0.0)\nvals = [drv.command(i/30.0) for i in range(31)]\n# Near-linear increments\nincs = [vals[i]-vals[i-1] for i in range(1,31)]\nassert max(abs(incs[i]-incs[0]) for i in range(1,len(incs))) < 1e-3*drv.max_current"}
+{"category":"V&V","task":"V&V: power draw vs. model across ramp","priority":"High","source_file":"src/supraluminal_prototype/power.py","source_snippet":"def compute_smearing_energy","python_snippet":"# Placeholder: integrate measured P(t) and compare to model E within tolerance; assert abs(E_meas-E_model)/E_model < 0.1"}
+{"category":"Design","task":"Power electronics block diagram v1","priority":"Medium","source_file":"docs/power_electronics_block.md","source_snippet":"DC bus, ring drivers, protections","python_snippet":"# Placeholder artifact existence check"}
 {"task":"Instantiate MetricBackreactionEvolution with default parameters","priority":"High","source_file":"evolve_3plus1D_with_backreaction.py","source_file_lines":"1:20","source_snippet":"class MetricBackreactionEvolution","python_snippet":"from evolve_3plus1D_with_backreaction import MetricBackreactionEvolution; mbe = MetricBackreactionEvolution(); assert hasattr(mbe, 'laplacian_3d') and callable(mbe.laplacian_3d)"}
 {"task":"Validate laplacian_3d finite-difference implementation","priority":"Medium","source_file":"evolve_3plus1D_with_backreaction.py","source_file_lines":"40:70","source_snippet":"def laplacian_3d(self, field):","python_snippet":"import numpy as np; from evolve_3plus1D_with_backreaction import MetricBackreactionEvolution; mbe = MetricBackreactionEvolution(grid_size=(10,10,10)); f = np.ones((10,10,10)); lap = mbe.laplacian_3d(f); assert np.allclose(lap, 0)"}
 {"task":"Check stress_energy_tensor returns expected keys and shapes","priority":"High","source_file":"evolve_3plus1D_with_backreaction.py","source_file_lines":"140:170","source_snippet":"def stress_energy_tensor(self, phi, pi):","python_snippet":"import numpy as np; from evolve_3plus1D_with_backreaction import MetricBackreactionEvolution; mbe = MetricBackreactionEvolution(grid_size=(8,8,8)); phi = np.zeros((8,8,8)); pi = np.zeros_like(phi); T = mbe.stress_energy_tensor(phi, pi); assert all(k in T for k in ['T_00','T_11','T_22','T_33']); assert T['T_00'].shape == (8,8,8)"}