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Quantitative transformation for implementation of adder circuits in physical systems.

Jeff Jones1, James G H Whiting1, Andrew Adamatzky1

  • 1Centre for Unconventional Computing, University of the West of England, Coldharbour Lane, Bristol BS16 1QY, UK.

Bio Systems
|May 27, 2015
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Summary

This study introduces a novel method to design adding circuits, avoiding spatial complexities. This approach simplifies digital circuit implementation on unconventional substrates like slime mould.

Keywords:
FrequencyFull adderLogic gateOscillatory dynamicsPhysarum polycephalum

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Area of Science:

  • Computational Biology
  • Digital Logic Design
  • Biocomputing

Background:

  • Classical computing relies on spatial arrangements of logic gates, facing challenges with unconventional substrates.
  • Implementing digital circuits on living materials like slime mould is hindered by input/output routing and signal interference.

Purpose of the Study:

  • To explore avoiding spatial propagation, branching, and crossing in adding circuit design.
  • To develop a new mapping strategy for digital circuits on unconventional substrates.
  • To assess the feasibility of implementing these circuits using slime mould.

Main Methods:

  • Analysis of input/output patterns of a single-bit full adder circuit.
  • Development of a quantitative transformation for input patterns to achieve a 1:1 mapping.
  • Simulation and assessment of implementation using slime mould (Physarum polycephalum).

Main Results:

  • A novel 1:1 input-to-output mapping for full adder circuits was achieved, simplifying design.
  • The mapping exhibits an incremental linear progression, suitable for physical implementation.
  • Successful simulation of the circuit design inspired by slime mould dynamics.

Conclusions:

  • The developed transformation simplifies digital circuit design, overcoming spatial limitations.
  • This method enhances the potential for using unconventional computing substrates, such as slime mould, for digital logic.
  • The findings pave the way for novel biocomputing applications.