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Amplification of computational power by the multiplication of bacteria exploring microfluidic networks encoding
Ayyappasamy Sudalaiyadum Perumal1, Falco C M J M van Delft2, Giulia Ippoliti1
1Department of Bioengineering, McGill University, Faculty of Engineering, Montreal, QC, Canada.
Microsystems & Nanoengineering
|August 11, 2026
Summary
Researchers developed a novel biocomputer using bacteria in microfluidic networks to solve NP-complete problems like the Subset Sum Problem (SSP). This approach offers exponentially growing computational power, potentially outperforming electronic computers.
Area of Science:
- Biocomputation
- Microfluidics
- Computational Complexity
Background:
- NP-complete problems require exponential computational resources.
- Electronic and DNA computing face limitations with increasing problem sizes.
Purpose of the Study:
- Demonstrate a proof-of-concept for a bacterial biocomputer.
- Solve the Subset Sum Problem (SSP) using a microfluidic network.
Main Methods:
- Utilized motile bacteria exploring a microfluidic network.
- Encoded the Subset Sum Problem (SSP) algorithm within the network design.
- Leveraged bacterial multiplication for combinatorial computation.
Main Results:
- Successfully demonstrated bacterial biocomputation for an NP-complete problem.
- Observed continuous amplification of computational power through bacterial multiplication.
- Identified scaling points where bacterial biocomputing surpasses electronic computation.
Conclusions:
- Bacterial biocomputation in microfluidic networks offers scalable solutions for complex problems.
- This approach presents low error rates, low energy requirements, and exponential resource growth.
- Suggests potential for bacterial-driven biocomputation to overcome limitations of current computing paradigms.
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