- Award ID(s):
- 1912484
- Publication Date:
- NSF-PAR ID:
- 10381589
- Journal Name:
- Journal of High Energy Physics
- Volume:
- 2022
- Issue:
- 3
- ISSN:
- 1029-8479
- Sponsoring Org:
- National Science Foundation
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The proposed approach is computationally very efficient. While application to more realistic synthetic data sets is beyond the scope of this paper, as well as to real data, since that requires additional steps to account for such issues as missing data, we illustrate how this methodology can help inform first order questions such as model resolution in the presence of noise, and trade-offs between different physical parameters (anisotropy, attenuation, crustal structure, etc.) that would be computationally very costly to address adequately, when using conventional full waveform tomography based on single-event wavefield computations.
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