(Short Paper32) Language Generation Process and Analog Dy namic Recording Model of the Life Code in the In Vivo Analog Quantum Synchronizer (BioQPU) Paradigm: Trial and Error and Weighting Based on Active Rejection of Phase Noise and Chemical Triggers
Year: 2026
Type: preprint
Abstract: The process by which humans spin words and construct long sentences has aspects that cannot be fully explained by the simple search and output model of discrete digital information in classical brain science. In this paper, we first overcome the metaphor of viewing life as a “computer” computing specific algorithms, and redefine the medium on which all memories in the biological system are recorded as an analog “life code (drive recorder of life)” that actively rejects phase noise based on LUCA’s Theorem (phase synchronization with environmental waves), proposing this as a verifiable hypothesis. Building on this, we model the language generation process as an iterative loop of analog resonance optimization. In this loop, waves from this continuous stream, along with their past contexts, are summoned into a quantum entangled space, and words are determined through “forced decoherence (conversion to particles)”—sublimating decoherence, which is considered an error in artificial machines, into a function via chemical triggers from the autonomous analog tuner (Glial OS) in the left brain. Furthermore, we introduce the concept of “selective decoherence” mediated by neurotransmitters via the Glial OS to explain the freedom of human analog memory retrieval. Finally, we consider the physical mechanism by which the time series process of trial and error in sentence construction itself is irreversibly carved onto the life code as “analog dynamic tag weighting,” independent of the computer metaphor.
Author: kotoan.gg
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7221469719
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