H-ImmQπDecoder v2.0: A Bio-Inspired Quantum Error Decoder Integrating Immune Adaptation, Quantum-π Phase Control, and Quantum Metabolism - Barack Ndenga (Publisher, 2025)
In this work, I introduce the H-ImmQπDecoder v2.0, a new class of quantum error decoder that integrates three novel mechanisms: an immune-inspired adaptive memory capable of learning, mutating, and generating new local correction strategies, a dynamic π-field representing spatio-temporal quantum coherence and noise topology, a Quantum Metabolism regulating the decoder’s adaptive behavior through an internal energy function. In addition, the decoder implements a non-linear Quantum-π Phase Correction mechanism that operates beyond discrete Pauli corrections by applying continuous phase alignment driven by π-field gradients. To my knowledge, no existing quantum decoder employs a bio-inspired immune system, a hydrodynamic π-field, and metabolic feedback simultaneously. The architecture presented here is therefore fundamentally new, and I formally claim its novelty and authorship. The proposed decoder is designed to handle correlated, non-Markovian, or topologically structured noise, situations where conventional decoders (MWPM, BP, NN-based) rapidly degrade. I provide the conceptual framework, usage conditions, algorithmic details, and practical motivation for real quantum processors. Keywords: quantum error correction (QEC), immune-inspired algorithms, π-field dynamics, continuous phase correction, quantum metabolism, adaptive decoding, correlated noise.
A bio-inspired quantum error decoder integrating immune adaptation, dynamic π-field modeling, nonlinear Quantum-π phase correction, and quantum metabolic regulation. The H-ImmQπDecoder v2.0 introduces a new paradigm of Bio-QEC for correlated and non-Markovian quantum noise.