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Information-acquiring von Neumann architecture of a computer: A theoretical design

Eiji Konishi

TL;DR

The paper addresses the problem of merging quantum measurement with computer architecture to enable information acquisition. It proposes an approach that models a state-reduction mechanism within CPU pins using a macroscopic charged Bose-Einstein condensate and an orbital superselection rule, realizing a von Neumann-type interaction and a binary meter as a switch. The key contributions include a physically grounded pin model in quantum electrodynamics, a coarse-grained register scheme that yields positive information, and a pathway to information-acquiring AI that stores knowledge derived from event readings. This work significantly links foundational quantum measurement concepts with information theory and AI, outlining a framework where computation can transition from purely functional processing to knowledge-creating information acquisition.

Abstract

We design the information-acquiring von Neumann architecture of a computer in a fine-grained or coarse-grained model of the registers (quickly accessible memories) in the central processing unit, where information is carried by classical bits. This architecture enables both a Hamiltonian process converting a given input pure state to another output pure state of the system to be considered (functionality) and a physical process to acquire information. The latter process is identified with the projection hypothesis (state reduction) in projective quantum measurement in the ensemble interpretation of quantum mechanics. As a novelty of this work, we treat projective quantum measurement as a classical measurement in the coarse-grained model. The main objective is to examine the present author's previously proposed state-reduction mechanism in the architecture within quantum electrodynamics in the presence of the orbital superselection rule. As a result, the electric potential incorporated into the architecture serves as a binary switch for the state reduction. As a consequence of this architecture, information-acquiring artificial intelligence can be established.

Information-acquiring von Neumann architecture of a computer: A theoretical design

TL;DR

The paper addresses the problem of merging quantum measurement with computer architecture to enable information acquisition. It proposes an approach that models a state-reduction mechanism within CPU pins using a macroscopic charged Bose-Einstein condensate and an orbital superselection rule, realizing a von Neumann-type interaction and a binary meter as a switch. The key contributions include a physically grounded pin model in quantum electrodynamics, a coarse-grained register scheme that yields positive information, and a pathway to information-acquiring AI that stores knowledge derived from event readings. This work significantly links foundational quantum measurement concepts with information theory and AI, outlining a framework where computation can transition from purely functional processing to knowledge-creating information acquisition.

Abstract

We design the information-acquiring von Neumann architecture of a computer in a fine-grained or coarse-grained model of the registers (quickly accessible memories) in the central processing unit, where information is carried by classical bits. This architecture enables both a Hamiltonian process converting a given input pure state to another output pure state of the system to be considered (functionality) and a physical process to acquire information. The latter process is identified with the projection hypothesis (state reduction) in projective quantum measurement in the ensemble interpretation of quantum mechanics. As a novelty of this work, we treat projective quantum measurement as a classical measurement in the coarse-grained model. The main objective is to examine the present author's previously proposed state-reduction mechanism in the architecture within quantum electrodynamics in the presence of the orbital superselection rule. As a result, the electric potential incorporated into the architecture serves as a binary switch for the state reduction. As a consequence of this architecture, information-acquiring artificial intelligence can be established.
Paper Structure (5 sections, 8 equations, 1 figure)

This paper contains 5 sections, 8 equations, 1 figure.

Table of Contents

  1. Introduction
  2. State-Reduction Mechanism
  3. The physical model
  4. Derivation of the von Neumann-type interaction
  5. Conclusion

Figures (1)

  • Figure 1: Horizontal (left) and vertical (right) sections of a pin. The gray, red, and light-gray regions (from outer to inner) show the hydrophilic membrane, the surface region, and the bulk water, respectively. Applied voltage $\Delta U$ (system $\psi$) slopes to zero with a finite run length and propagates in the direction of the arrow (the $z$-direction). System $A$ exists in the surface region. The diameter $\ell$ of this tubule is shorter than the resonant wavelength $\approx400$ [$\mu$m] of the radiation from the two-level water molecule.