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
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     <h3 style="margin-top:0; color:#f87171;">
       QML-HCS: A Hypercausal Quantum Machine Learning Framework for
       Non-Stationary Environments
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       <strong>Hector E. Mozo</strong>
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      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.
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       <a href="https://arxiv.org/abs/2511.17624"
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          arXiv:2511.17624
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        <span>DOI: 10.48550/arXiv.2511.17624</span>

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