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Details of Grant 

EPSRC Reference: EP/N023544/1
Title: Exploring instability in complex systems - simulations in no-man's land
Principal Investigator: Sieber, Dr J
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Danish Technical University University of Bristol
Department: Engineering Computer Science and Maths
Organisation: University of Exeter
Scheme: EPSRC Fellowship
Starts: 01 January 2017 Ends: 31 December 2021 Value (£): 639,000
EPSRC Research Topic Classifications:
Mathematical Analysis Non-linear Systems Mathematics
EPSRC Industrial Sector Classifications:
Environment
Related Grants:
Panel History:
Panel DatePanel NameOutcome
19 Jul 2016 EPSRC Mathematical Sciences Fellowship Interviews July 2016 Announced
08 Jun 2016 EPSRC Mathematics Prioritisation Panel Meeting June 2016 Announced
Summary on Grant Application Form
The prediction and analysis of sudden changes in complex systems and models (called tipping) are a current topic in science and an urgent problem for society. A few hotly debated examples are the possible collapse of the Gulf Stream, the sudden loss of vegetation in nutrient-polluted lakes, or the change between the vegetated and desert state in dry regions. While these cases of tipping are well understood in idealised mathematical models, their analysis is restricted in field observations, laboratory experiments and complex model simulations by the impossibility to systematically explore dynamically unstable phenomena. For many complex systems the notion of equilibrium is only defined in a statistical mechanics sense as an emerging phenomenon, which, by its definition, must be stable.

The proposed research will develop general mathematical methods that will remove these restrictions: they will enable experimenters and modellers to discover and track unstable phenomena in laboratory experiments and complex model simulations, or, more generally, in any situation where one can provide input into the system depending on its output in real time. Two features distinguish the systems under study from the idealised models.

* (Limited input only) One has input into the system but may not be able to set the entire internal state at will.

* (Variability) The experiment or model run is repeatable, but the system has internal variability such that outputs are affected by randomness or disturbances.

Several areas will serve as testbeds and springboards to the wider scientific community: individual-based models in ecology, epidemiology and social science, vibration tests in engineering, models of climate subsystems, and abstract spatially extended systems (such as used for neuron population models).

Key Findings
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Summary
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Organisation Website: http://www.ex.ac.uk