feat: ADR-080 P1+P2 remediation — refactor, perf, tests, safety

P1 fixes (this sprint):
- P1-6: Extract sensing-server modules (cli, types, csi, pose) from main.rs
- P1-7: DDA ray march for tomography — O(max(n)) replaces O(n^3) voxel scan
- P1-8: Batch neural inference — Tensor::stack/split for single GPU call
- P1-10: Eliminate 112KB/frame alloc — islice replaces deque→list copy

P2 fixes (this quarter):
- P2-11: Python unit tests for 8 modules (rate_limit, auth, error_handler,
  pose_service, stream_service, hardware_service, health_check, metrics)
- P2-13: MAT simulated data safety guard — blocking overlay + pulsing banner
- P2-14: Wire token blacklist into auth verification + logout endpoint
- P2-15: Frame budget benchmark — confirms pipeline well under 50ms budget

Addresses 8 of 10 remaining issues from QE analysis (ADR-080).

Co-Authored-By: claude-flow <ruv@ruv.net>

v1/src/api/main.py

@@ -17,7 +17,7 @@ from starlette.exceptions import HTTPException as StarletteHTTPException
 
 from src.config.settings import get_settings
 from src.config.domains import get_domain_config
-from src.api.routers import pose, stream, health
+from src.api.routers import pose, stream, health, auth
 from src.api.middleware.auth import AuthMiddleware
 from src.api.middleware.rate_limit import RateLimitMiddleware
 from src.api.dependencies import get_pose_service, get_stream_service, get_hardware_service
@@ -263,6 +263,12 @@ app.include_router(
     tags=["Streaming"]
 )
 
+app.include_router(
+    auth.router,
+    prefix=f"{settings.api_prefix}",
+    tags=["Authentication"]
+)
+
 
 # Root endpoint
 @app.get("/")