Full-Waveform Inversion of High-Frequency Teleseismic Body Waves Based on Multiple Plane-Wave Incidence: Methods and Practical Applications
Bibliographic record
Abstract
ABSTRACT Teleseismic full-waveform inversion has recently been applied to image subwavelength-scale lithospheric structures (typically a few tens of kilometers) by utilizing hybrid methods in which an efficient solver for the 1D background model is coupled with a full numerical solver for a small 3D target region. Among these hybrid methods, the coupling of the frequency–wavenumber technique with the spectral element method is one of the most computationally efficient ones. However, it is normally based on a single plane-wave incidence, and thus cannot synthesize secondary global phases generated at interfaces outside the target area. To remedy the situation, we propose to use a multiple plane-wave injection method to include secondary global phases in the hybrid modeling. We investigate the performance of the teleseismic full-waveform inversion based on single and multiple plane-wave incidence through an application in the western Pyrenees and compare it with previously published images and the inversion based on a global hybrid method. In addition, we also test the influence of Earth’s spherical curvature on the tomographic results. Our results demonstrate that the teleseismic full-waveform inversion based on a single plane-wave incidence can reveal complex lithospheric structures similar to those imaged using a global hybrid method and is reliable for practical tomography for small regions with an aperture of a few hundred kilometers. However, neglecting the Earth’s spherical curvature and secondary phases leads to errors on the recovered amplitudes of velocity anomalies (e.g., about 2.8% difference for density and VS, and 4.2% for VP on average). These errors can be reduced by adopting a spherical mesh and injecting multiple plane waves in the frequency–wavenumber-based hybrid method. The proposed plane-wave teleseismic full-waveform inversion is promising for mapping subwavelength-scale seismic structures using high-frequency teleseismic body waves (>1 Hz) including coda waves recorded at large N seismic arrays.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".