How do constraints affect the behaviour of a complex system?
Lead Research Organisation:
Imperial College London
Department Name: Physics
Abstract
In a system consisting of simple agents, how do constraints affect the emergent macroscopic behaviours? In nature, there are many examples of emergent behaviour in complex systems, for example, the Gutenberg-Richter law of earthquakes, the power-law behaviour of price fluctuations, the connectivity of social networks etc. However, these complex systems are finite in size. How does the finiteness of these systems perturb the inherent (ideal) behaviour that one would observe in an infinite system? Can one extract the scaling behaviour of the perturbation from finite systems that would eventually allow one to extrapolate to the infinite system? The notion of finite-size scaling in critical systems is one such example, but in a limited domain. Another related question is whether smaller systems are inherently more predictable due to the constraints. If yes, can one exploit this increased predictability to extrapolate the predictability of larger systems? These investigations are first pursued in simplified complex systems. TheResearch Area: Complexity Science
Research Area: Complexity Science
Strategic Area: Mathematical Sciences & Physical Sciences
Research Area: Complexity Science
Strategic Area: Mathematical Sciences & Physical Sciences
Publications
Ciacci A
(2020)
Understanding the transition from paroxysmal to persistent atrial fibrillation.
in Physical review research
Falkenberg M
(2019)
Identifying Potential Re-Entrant Circuit Locations From Atrial Fibre Maps.
in Computing in cardiology
Falkenberg M
(2019)
Unified mechanism of local drivers in a percolation model of atrial fibrillation.
in Physical review. E
Falkenberg M
(2020)
Identifying time dependence in network growth
in Physical Review Research
Franks NR
(2019)
Digging the optimum pit: antlions, spirals and spontaneous stratification.
in Proceedings. Biological sciences
McGillivray MF
(2018)
Machine learning methods for locating re-entrant drivers from electrograms in a model of atrial fibrillation.
in Royal Society open science
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/N509486/1 | 01/10/2016 | 31/03/2022 | |||
1992401 | Studentship | EP/N509486/1 | 01/10/2017 | 30/09/2021 | Max Falkenberg Mcgillivray |
Description | New theories for the cause of certain cardiac arrhythmia with proposals on how to improve treatment. Complementary work studying constraints in network analysis. Potential to shift paradigm and change dominant methods in the field. |
Exploitation Route | Theoretical models which may lead to new diagnostic methods in cardiology. Conceptual challenge to current paradigm in network analysis which may lead to more robust analysis methods. |
Sectors | Digital/Communication/Information Technologies (including Software),Healthcare,Pharmaceuticals and Medical Biotechnology |
Description | BHF ElectroCardioMaths Group |
Organisation | Imperial College London |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Physics subgroup of the BHF funded ElectroCardioMaths group applying physics approaches to problems in cardiac electrophysiology. |
Collaborator Contribution | See outcomes below |
Impact | 2 Publications 1 Conference Paper 2 Working Papers 1 Patent Pending |
Start Year | 2014 |
Description | University of Auckland Bioengineering Department |
Organisation | University of Auckland |
Department | Auckland Bioengineering Institute (ABI) |
Country | New Zealand |
Sector | Academic/University |
PI Contribution | Theoretical modeling using Auckland Data. |
Collaborator Contribution | Data acquisition and processing. |
Impact | Paper under review |
Start Year | 2019 |