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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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Biological computation running on quantum computation.

Koichiro Matsuno¹

¹Nagaoka University of Technology, Nagaoka, 940-2188, Japan.

|June 27, 2021

Summary

This summary is machine-generated.

Biological computation uses indexical quantum computation, reducing complexity via parallel processors. This approach enables agents to perceive and interact with their unique environmental affordances.

Keywords:

Affordance Complexity Entanglement Environment Internal measurement Quantum computation Umwelt

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Area of Science:

Theoretical Biology
Quantum Computing
Computational Neuroscience

Background:

Classical computation relies on symbolic manipulation, which can be computationally complex.
Biological systems exhibit complex behaviors that may benefit from alternative computational paradigms.

Purpose of the Study:

To explore the functional advantages of indexical quantum computation in biological phenomena.
To investigate how indexical quantum computation reduces computational complexity compared to classical methods.
To understand the role of concurrent processors and environmental perception in biological agency.

Main Methods:

Conceptual analysis of indexical quantum computation versus symbolic computation.
Exploration of parallel processing in quantum computational models.
Application of Uexküll's umwelt and Gibson's affordance theories to quantum computation.

Main Results:

Indexical quantum computation offers reduced computational complexity through parallel processing.
Concurrent processors in quantum computation perceive unique environmental contexts.
This approach supports agentive environmental interaction, forming umwelten and affordances.

Conclusions:

Indexical quantum computation provides a powerful, less complex model for biological phenomena.
The framework aligns with concepts of biological agency and environmental interaction.
This paradigm offers a new perspective on the relationship between computation and biological systems.