Determining the flow of rays or non-interacting particles driven by a force or velocity field is fundamental to modelling many physical processes. These include particle flows arising in fluid mechanics and ray flows arising in the geometrical optics limit of linear wave equations. In many practical applications, the driving field is not known exactly and the dynamics are determined only up to a degree of uncertainty. This paper presents a boundary integral framework for propagating flows including uncertainties, which is shown to systematically interpolate between a deterministic and a completely random description of the trajectory propagation. A simple but efficient discretisation approach is applied to model uncertain billiard dynamics in an integrable rectangular domain.
Skip Nav Destination
,
Article navigation
December 2014
Research Article|
December 05 2014
A boundary integral formalism for stochastic ray tracing in billiards Available to Purchase
David J. Chappell;
David J. Chappell
1School of Science and Technology,
Nottingham Trent University
, Clifton Campus, Nottingham NG11 8NS, United Kingdom
Search for other works by this author on:
Gregor Tanner
Gregor Tanner
2School of Mathematical Sciences,
University of Nottingham
, University Park, Nottingham NG7 2RD, United Kingdom
Search for other works by this author on:
David J. Chappell
1
Gregor Tanner
2
1School of Science and Technology,
Nottingham Trent University
, Clifton Campus, Nottingham NG11 8NS, United Kingdom
2School of Mathematical Sciences,
University of Nottingham
, University Park, Nottingham NG7 2RD, United Kingdom
Chaos 24, 043137 (2014)
Article history
Received:
July 31 2014
Accepted:
November 19 2014
Citation
David J. Chappell, Gregor Tanner; A boundary integral formalism for stochastic ray tracing in billiards. Chaos 1 December 2014; 24 (4): 043137. https://doi.org/10.1063/1.4903064
Download citation file:
Pay-Per-View Access
$40.00
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
Citing articles via
Reservoir computing with the minimum description length principle
Antony Mizzi, Michael Small, et al.
Recent achievements in nonlinear dynamics, synchronization, and networks
Dibakar Ghosh, Norbert Marwan, et al.
Data-driven nonlinear model reduction to spectral submanifolds via oblique projection
Leonardo Bettini, Bálint Kaszás, et al.
Related Content
Boundary integral models of stochastic ray propagation: Discretisation via the collocation and Nyström methods
AIP Conf. Proc. (June 2017)
Estimating Lyapunov exponents in billiards
Chaos (September 2019)
Convergence of Hamiltonian systems to billiards
Chaos (June 1998)
Fermi acceleration and adiabatic invariants for non-autonomous billiards
Chaos (July 2012)
Survival probability for open spherical billiards
Chaos (November 2014)