Multiresolution imaging of mantle reflectivity structure using SS and P'P' precursors
Bibliographic record
Abstract
Knowledge of the mantle reflectivity structure is highly dependent on our ability to efficiently extract, and properly interpret, small seismic arrivals. Among the various data types and techniques, long-period SS/PP precursors and high-frequency receiver functions are routinely utilized to increase the confidence of the recovered mantle stratifications at distinct spatial scales. However, low resolution and a complex Fresnel zone are glaring weaknesses of SS precursors, while over-reliance on receiver distribution is a formidable challenge for the analysis of converted waves from oceanic regions. A promising high frequency alternative to receiver functions is P′P′ precursors, which are capable of resolving mantle structures at vertical and lateral resolution of ∼5 and ∼200 km, respectively, owing to their spectral content, shallow angle of incidence and near-symmetric Fresnel zones. This study presents a novel processing method for both SS (or PP) and P′P′ precursors based on deconvolution, stacking, Radon transform and depth migration. A suite of synthetic tests is performed to quantify the fidelity and stability of this method under different data conditions. Our multiresolution survey of the mantle at targeted areas near Nazca-South America subduction zone reveal both olivine and garnet related transitions at depths below 400 km. We attribute a depressed 660 to thermal variations, whereas compositional variations atop the upper-mantle transition zone are needed to explain the diminished or highly complex reflected/scattered signals from the 410 km discontinuity. We also observe prominent P′P′ reflections within the transition zone, and the anomalous amplitudes near the plate boundary zone indicate a sharp (∼10 km thick) transition that likely resonates with the frequency content of P′P′ precursors. The migration of SS precursors in this study shows no evidence of split 660 reflections, but potential majorite–ilmenite (590–640 km) and ilmenite–perovskite transitions (740–750 km) are identified based on similarly processed high-frequency P′P′ precursors. Additional findings of severely scattered energy in the lithosphere and distinct lower mantle reflections at ∼800 km could be potentially important but require further verifications. Overall, our improved imaging methods and the strong sensitivity of P′P′ precursors to the existence, depth, sharpness and strength of reflective structures offer significant future promise for the understanding of mantle mineralogy and dynamics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".