Stripy

Triangulation of Spherical and Cartesian points using 2D splines

Get Stripy

Quagmire

Highly scalable framework to simulate landscape evolution on a variety of mesh types

Get Quagmire

PyCurious

Python tool for computing the Curie depth from the magnetic anomaly

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Dr. Ben Mather

Computational Geophysicist

EarthByte Group

Biography

I am a Postdoc in the EarthByte Group at the University of Sydney. I am interested in the inversion of thermochemical properties of the lithosphere subject to available geophysical data and their uncertainties. Inversions that couple multiple datasets ultimately improve the precision and understanding of the thermochemical evolution of the Earth.

I am passionate about open source software! On this website you will find links to repositories where source code is available with examples of how to reproduce peer-reviewed benchmarks and published results. You will also find code snippets that I have found useful - and maybe you will too!

Interests

Data assimilation
Bayesian inversion
Thermochemical evolution
Geothermal heat flux

Education

PhD in Earth Science, 2016
The University of Melbourne
Bachelor of Science (Hons), 2011
Monash University

Experience

Computational Geophysicist

Sydney Informatics Hub

November 2018 – Present Sydney

Coupling of geodynamic codes with surface processes and groundwater flow.

Applied to the Sydney Basin.
Parallel computing frameworks built on PETSc.
Optimisation using deep learning algorithms.

Postdoctoral Research Scientist

Dublin Institute for Advanced Studies

June 2017 – October 2018 Dublin

3D integrated geothermal modelling of Ireland.

Forward and inverse modelling of geothermal heat flux.
Assimilate Curie depth, seismic velocity, gravity anomly, surface heat flow data.

Research assistant

University of Melbourne

February 2016 – June 2017 Melbourne

Developer of Quagmire, a code for parallel surface processes modelling

Multiple meshing algorithms for unstructured, regular, and orthogonal meshes.
Mesh decomposition and solving routines built on PETSc.
Landscape evolution using stream flow algorithms.

Recent Posts

Turning up the heat on Earth temperature modelling

Dr Ben Mather and Prof Louis Moresi from AuScope’s Simulation, Analysis and Modelling (SAM) program have recently developed a novel, speedy and data-driven way to model the temperature of Earth’s crust in southeastern Australia. Their work has since attracted a grant from the International Association of Mathematical Geosciences (IAMG) to refine the new method and investigate earth temperatures further afield in Alaska.

ben mather, jo condon

Last updated on Thursday, 13 Feb 2020 4 min read

Introducing Stripy

Geodynamicists from Sydney and Australian National universities have developed Stripy, a software module that allows scientists to efficiently place GIS ‘wrapping paper’ around the spherical Earth ‘present’. This is the first module to be built for a common scientific programming language like Python, that supports such ‘wrapping’, or mapping features. Here, developer Dr Ben Mather explains Stripy’s key functions for the AuScope Earth modelling community.

ben mather, jo condon

Last updated on Thursday, 13 Feb 2020 2 min read

Continuous Integration with Travis CI

A bit of a late-comer to this game, I’ve just discovered the merits of so-called “continuous integration”. In a Journal of Open Source Software (JOSS) review for stripy, one of the reviewers suggested Travis CI as a way to test if the code is working correctly.

ben mather

Last updated on Thursday, 06 Jun 2019 2 min read

May the 4th be with you...

In an Underworld release far, far away… Geodynamicists struggle to model planetary dynamics due to the Cartesian Empire. Physical observations suffer inappropriate meshing and projections bend minds. The Underworld team builds the ultimate weapon to erase the Cartesian nightmare based on the ancient practice of the Cubed-Sphere mesh.

ben mather

Last updated on Friday, 07 Jun 2019 1 min read

Multiprocessing in Python

Most of the codes I develop run in parallel using MPI (Message Passing Interface) using the python wrapper, mpi4py. There is a reason why highly scalable programs use this approach, and that is because each processor handles its own chunk of memory and communicates with other processors only when it’s needed.

ben mather

Last updated on Thursday, 27 Aug 2020 4 min read

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Recent Publications

Adjoint inversion of the thermal structure of Southeastern Australia

An efficient inversion framework that gives improved estimates of the thermal state of the crust in Victoria using heat flow measurements and Curie depth in a joint inversion using 3D geological models, and numerical models of thermal diffusion. The outcome of this work is an estimation of the basal heat flux, thermal properties and the heat production rates for the various domains in the model together with uncertainty information.

ben mather, louis moresi, peter rayner

PDF Project DOI

PyCurious: A Python module for computing the Curie depth from the magnetic anomaly

PyCurious is a Python package for computing the depth to 580°C from maps of the Earth’s magnetic anomaly using a Bayesian …

ben mather, robert delhaye

PDF Code Project DOI

Stripy: A Python module for (constrained) triangulation in Cartesian coordinates and on a sphere.

The triangulation of scattered points is a common problem in science and engineering when local neighbourhood information is required …

louis moresi, ben mather

PDF Code Project DOI

Constraining the geotherm beneath the British Isles from Bayesian inversion of Curie depth: Integrated modelling of magnetic, geothermal and seismic data

The temperature distribution in the crust, and associated uncertainty, was simulated from the ensemble of Curie depth realisations assigned to a lower thermal boundary condition of a crustal model (inc. sedimentary thickness, Moho depth, heat production, thermal conductivity), constructed from various geophysical and geochemical data sets.

ben mather, javier fullea

PDF Code Dataset Project DOI