Peter Ashwin

Peter Ashwin

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Peter Ashwin

University of Exeter

Research Focus & Metrics

Academic Career Length

37Years (1990-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 March 2012 in Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
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PAPeter Ashwin
Peter Ashwin
SWSebastian Wieczorek
Sebastian Wieczorek
RVRenato Vitolo
Renato Vitolo
PCPeter Michael Cox
Peter Michael Cox
Tipping points associated with bifurcations (B-tipping) or induced by noise (N-tipping) are recognized mechanisms that may potentially lead to sudden climate change. We focus here on a novel class of tipping points, where a sufficiently rapid change to an input or parameter of a system may cause the system to ‘tip’ or move away from a branch of attractors. Such rate-dependent tipping, or R-tipping, need not be associated with either bifurcations or noise. We present an example of all three types of tipping in a simple global energy balance model of the climate system, illustrating the possibility of dangerous rates of change even in the absence of noise and of bifurcations in the underlying quasi-static system.

1 September 1994 in Physics Letters A
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PAPeter Ashwin
Peter Ashwin
JBJorge Buescu
Jorge Buescu
ISIan Stewart
Ian Stewart

6 January 2016 in The Journal of Mathematical Neuroscience
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PAPeter Ashwin
Peter Ashwin
SCStephen Coombes
Stephen Coombes
RNRachel Nicks
Rachel Nicks
The tools of weakly coupled phase oscillator theory have had a profound impact on the neuroscience community, providing insight into a variety of network behaviours ranging from central pattern generation to synchronisation, as well as predicting novel network states such as chimeras. However, there are many instances where this theory is expected to break down, say in the presence of strong coupling, or must be carefully interpreted, as in the presence of stochastic forcing. There are also surprises in the dynamical complexity of the attractors that can robustly appear—for example, heteroclinic network attractors. In this review we present a set of mathematical tools that are suitable for addressing the dynamics of oscillatory neural networks, broadening from a standard phase oscillator perspective to provide a practical framework for further successful applications of mathematics to understanding network dynamics in neuroscience.

1 May 1996 in Nonlinearity
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PAPeter Ashwin
Peter Ashwin
JBJorge Buescu
Jorge Buescu
ISIan Stewart
Ian Stewart

1 March 1992 in Journal of Nonlinear Science
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PAP. Ashwin
P. Ashwin
JSJ. W. Swift
J. W. Swift

1 January 2015 in Chaos: An Interdisciplinary Journal of Nonlinear Science
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PAPeter Ashwin
Peter Ashwin
OBOleksandr Burylko
Oleksandr Burylko
We suggest a definition for a type of chimera state that appears in networks of indistinguishable phase oscillators. Defining a “weak chimera” as a type of invariant set showing partial frequency synchronization, we show that this means they cannot appear in phase oscillator networks that are either globally coupled or too small. We exhibit various networks of four, six, and ten indistinguishable oscillators, where weak chimeras exist with various dynamics and stabilities. We examine the role of Kuramoto-Sakaguchi coupling in giving degenerate (neutrally stable) families of weak chimera states in these example networks.