Theory / Concepts#
This section explains the theoretical foundations of QML-HCS, covering quantum principles, causal inference, and the mathematical structure behind hypercausal hybrid learning systems.
Associated Paper#
QML-HCS: A Hypercausal Quantum Machine Learning Framework for Non-Stationary Environments
Hector E. Mozo
This paper introduces the theoretical foundations of QML-HCS by formalizing a hypercausal learning model for non-stationary environments. It defines the core execution semantics, including multi-branch future generation, projection policies, and continuous causal feedback mechanisms, and presents the mathematical structure used to maintain coherence and stability under distributional drift. The paper focuses on establishing the architectural and conceptual framework that informs the design and behavior of the QML-HCS software.