Localization of sound in a three-dimensional elastic network
Bibliographic record
Abstract
A long standing question in physical acoustics has been whether or not the Anderson localization of sound can be demonstrated unambiguously in three dimensions. Here we address this question by reporting evidence for the localization of ultrasonic waves in a three-dimensional granular network of weakly sintered aluminum beads. In the upper part of the intermediate frequency regime, where the ultrasonic wavelength is comparable with the sizes of the pores and beads, the intensity time-of-flight profile of the multiply scattered waves exhibits non-exponential decay, which may be construed as a slowing down of the diffusion coefficient with propagation time and is consistent with predictions for localized waves. We use a quasi point source and detector to demonstrate how localization cuts off the transverse spreading of the multiply scattered waves, an effect, which we call 3D transverse localization, that has not been observed previously for any type of wave. These results are interpreted using recent theoretical predictions based on the self-consistent theory of the dynamics of localization, allowing the localization length to be determined. Further evidence is obtained from intensity statistics, which reveal a Thouless conductance g less than unity. These results unambiguously demonstrate the localization of sound in this system.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".