The Binary–Quantum Bridge for AGI: Information-Preserving Differentiable Programs with a Causal Objective

 The Binary–Quantum Bridge (BQB) is a mathematical framework for analyzing a dual objective
 in AGI design: maintain differentiable, information-preserving learning dynamics while guaran
teeing classical, auditable behavior at decision commit. It is not an engineering blueprint. We
 recommend archiving this work and deferring any real-world development until (i) interpretability
 benchmarks, (ii) incident response and containment, and (iii) externally auditable objective
 governance are established and independently verified.   Addressed to Suriya Gunasekar, Microsoft.