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Multiple graph realizations method: Improving the accuracy and the efficiency of the shortest path method through random sampling

Multiple graph realizations method: Improving the accuracy and the efficiency of the shortest path method through random sampling
Multiple graph realizations method: Improving the accuracy and the efficiency of the shortest path method through random sampling
We present a new implementation of the shortest path method that calculates accurate travel times in arbitrarily large model spaces without the requirement of large computational times and large amounts of memory, an inherent problem of the Dijkstra's-like algorithms. The Multiple Graph Realizations method is based upon multiple sampling of the model space, using numerous random graphs. The performance of this new method is compared against the conventional way to improve the accuracy of shortest path method, which is to use denser grids and connectivity stencils of higher order. Our results suggest that although for relatively small models, single runs of the shortest path method are more suitable to achieve the desired accuracy, in large models, and after a certain level of desired accuracy, this approach becomes inefficient or even unfeasible, as the requirements in memory and computational time increases dramatically. On the contrary our method can achieve the desired accuracy with linear impact in computational time and negligible impact in required memory.
Body waves, Computational seismology, WAVE PROPAGATION, Wave scattering and diffraction, Numerical modelling, Numerical approximations and analysis
0956-540X
669–679
Bogiatzis, Petros
8fc5767f-51a2-4d3f-aab9-1ee9cfa9272d
Rychert, Catherine
70cf1e3a-58ea-455a-918a-1d570c5e53c5
Harmon, Nicholas
10d11a16-b8b0-4132-9354-652e72d8e830
Bogiatzis, Petros
8fc5767f-51a2-4d3f-aab9-1ee9cfa9272d
Rychert, Catherine
70cf1e3a-58ea-455a-918a-1d570c5e53c5
Harmon, Nicholas
10d11a16-b8b0-4132-9354-652e72d8e830

Bogiatzis, Petros, Rychert, Catherine and Harmon, Nicholas (2021) Multiple graph realizations method: Improving the accuracy and the efficiency of the shortest path method through random sampling. Geophysical Journal International, 227 (1), 669–679. (doi:10.1093/gji/ggab247).

Record type: Article

Abstract

We present a new implementation of the shortest path method that calculates accurate travel times in arbitrarily large model spaces without the requirement of large computational times and large amounts of memory, an inherent problem of the Dijkstra's-like algorithms. The Multiple Graph Realizations method is based upon multiple sampling of the model space, using numerous random graphs. The performance of this new method is compared against the conventional way to improve the accuracy of shortest path method, which is to use denser grids and connectivity stencils of higher order. Our results suggest that although for relatively small models, single runs of the shortest path method are more suitable to achieve the desired accuracy, in large models, and after a certain level of desired accuracy, this approach becomes inefficient or even unfeasible, as the requirements in memory and computational time increases dramatically. On the contrary our method can achieve the desired accuracy with linear impact in computational time and negligible impact in required memory.

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Accepted/In Press date: 24 June 2021
e-pub ahead of print date: 28 June 2021
Published date: 1 October 2021
Keywords: Body waves, Computational seismology, WAVE PROPAGATION, Wave scattering and diffraction, Numerical modelling, Numerical approximations and analysis

Identifiers

Local EPrints ID: 450151
URI: http://eprints.soton.ac.uk/id/eprint/450151
ISSN: 0956-540X
PURE UUID: 71a6bd07-90d3-4c1a-ab13-8d5b6037e0e6
ORCID for Petros Bogiatzis: ORCID iD orcid.org/0000-0003-1902-7476
ORCID for Nicholas Harmon: ORCID iD orcid.org/0000-0002-0731-768X

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Date deposited: 14 Jul 2021 16:30
Last modified: 17 Jul 2021 01:57

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Contributors

Author: Petros Bogiatzis ORCID iD
Author: Nicholas Harmon ORCID iD

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