EPJ Web Conf.
Volume 173, 2018Mathematical Modeling and Computational Physics 2017 (MMCP 2017)
|Number of page(s)||8|
|Section||Plenary and Invited Lectures|
|Published online||14 February 2018|
Disentangling Complexity in Bayesian Automatic Adaptive Quadrature
1 Laboratory of Information Technologies, Joint Institute for Nuclear Research, 6, Joliot Curie St., 141980 Dubna, Moscow Region, Russia
2 Horia Hulubei National Institute for Physics and Nuclear Engineering (IFIN-HH), 30, Reactorului St., Mǎgurele – Bucharest, 077125, Romania
Published online: 14 February 2018
The paper describes a Bayesian automatic adaptive quadrature (BAAQ) solution for numerical integration which is simultaneously robust, reliable, and efficient. Detailed discussion is provided of three main factors which contribute to the enhancement of these features: (1) refinement of the m-panel automatic adaptive scheme through the use of integration-domain-length-scale-adapted quadrature sums; (2) fast early problem complexity assessment – enables the non-transitive choice among three execution paths: (i) immediate termination (exceptional cases); (ii) pessimistic – involves time and resource consuming Bayesian inference resulting in radical reformulation of the problem to be solved; (iii) optimistic – asks exclusively for subrange subdivision by bisection; (3) use of the weaker accuracy target from the two possible ones (the input accuracy specifications and the intrinsic integrand properties respectively) – results in maximum possible solution accuracy under minimum possible computing time.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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