Memory-efficient emulation of physical tabular data using quadtree decomposition
Carlson, Jared
Computational physics
Computer science
Physics--Computer simulation
Thesis (M.S.)--Michigan State University. Computational Mathematics, Science and Engineering - Master of Science, 2022
Computationally expensive functions are sometimes replaced in simulations with an emulator that approximates the true function (e.g., equations of state, wavelength-dependent opacity, or composition-dependent materials properties). For functions that have a constrained domain of interest, this can be done by discretizing the domain and performing a local interpolation on the tabulated function values of each local domain. For these so-called tabular data methods, the method of discretizing the domain and mapping the input space to each subdomain can drastically influence the memory and computational costs of the emulator. This is especially true for functions that vary drastically in different regions. We present a method for domain discretization and mapping that utilizes quadtrees, which results in significant reductions in the size of the emulator with minimal increases to computational costs or loss of global accuracy. We apply our method to the electron-positron Helmholtz free energy equation of state and show over an order of magnitude reduction in memory costs for reasonable levels of numerical accuracy.
Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).
Includes bibliographical references.
O'Shea, Brian
Couch, Sean
2022
text
Electronic dissertations
application/pdf
1 online resource (39 p.) : ill.
local:Carlson_grad.msu_0128N_18784
en
Attribution 4.0 International
M.S.
Masters
Computational Mathematics, Science and Engineering - Master of Science
Michigan State University