| EPSRC Reference: |
EP/X019926/1 |
| Title: |
From signal detection to quantum dynamics in biology |
| Principal Investigator: |
Brody, Professor D |
| Other Investigators: |
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| Department: |
Mathematics |
| Organisation: |
University of Surrey |
| Scheme: |
Standard Research - NR1 |
| Starts: |
01 June 2023 |
Ends: |
31 May 2024 |
Value (£): |
71,931
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| EPSRC Research Topic Classifications: |
| Non-linear Systems Mathematics |
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| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
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Summary on Grant Application Form |
Biological systems are constantly exposed to changing environments but manage to adapt to them by gathering information about the conditions of their surroundings and processing this information to arrive at best strategies. Adaptation is essential to survival and signal detection is quintessential to adaptation. Hence all biological processes are generated by their information-processing capabilities. How can one then model the dynamical behaviours of biological systems? A highly effective way forward is to model the flow of noisy information available to biological systems. Their dynamical behaviours can logically be derived from the techniques of stochastic filtering and signal detection. That is, mathematical techniques of signal detection is the most suited method to model dynamical systems driven by signal detection.
Perhaps a much less intuitive obserrvation is that dynamical equations governing the evolution of a broad class of quantum systems likewise are equations for optimal signal detection, and there are reasons to believe that all quantum dynamics may be governed by underlying information-processing capabilities of fundamental particles. A particle immersed in an environment, energetically interacting with particles in the environment, will follow an energetically preferred dynamics --- but this requires the particle to extract information about the conditions of the environment, and at a quantum level this information is necessarily noisy. Hence the most efficient way forward is to conduct optimal signal processing, leading to quantum dynamics. In other words, nature is highly efficient.
The observation that both quantum and biological dynamics are governed by underlying signal detection problems is striking, leading to the hypothesises that optimal signal detection capability is fundamental to laws of nature, and that dynamical equations governing the evolution of quantum systems can, mutatis mutandis, applied to model dynamical behaviours of biological systems. These ideas, set out in my recent paper (Scientific Report vol. 12, 3042 (2022)), have been applied to model tropic motions of green plants, and they will be developed further in this research programme to explore ways to test the models, to analyse dynamical behaviours of other biological systems, and to reach out biological researchers, with the view towards making a significant contribution to understanding dynamical behaviours of biological systems. Along the way, new mathematical insights can be gained on certain types of stochastic equations admitting quantum-mechanical characteristics.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.surrey.ac.uk |