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Record W4412973535 · doi:10.1121/10.0038035

Anderson localization of acoustic waves in three dimensional resonant microbead suspensions

2025· article· en· W4412973535 on OpenAlexaff
Fanambinana Delmotte, Thomas Brunet, Jacques Leng, J. H. Page

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRandom lasers and scattering media
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsAnderson localizationAcoustic waveAmbiguityFocus (optics)PhysicsScalar (mathematics)AcousticsScatteringUltrasonic sensorScalar fieldPosition (finance)Classical mechanicsOpticsCondensed matter physicsComputer scienceMathematicsGeometry

Abstract

fetched live from OpenAlex

Anderson localization is one of the most fascinating wave phenomena that may occur in strongly scattering heterogeneous media. Since the 1980s, the experimental search for this halt of diffusive transport in 3-D disordered systems has continued to be the focus of intense research, whether for quantum particles or classical waves. In the latter case, the experimental demonstration remains challenging for light waves, contrary to ultrasonic elastic waves, for which it has already been proven without ambiguity. In this talk, I will describe a new set of two independent time- and position-resolved experiments, using techniques that were first developed to clearly establish the existence of localized regimes in mesoglasses made of sintered beads. Here, I will focus on scalar acoustic waves and report unambiguous evidence of the transitions between diffusion and localization in suspensions made of soft metallic resonant beads, inspired by recent advances in the field of soft acoustic metamaterials. These experiments allow us to determine the mobility edges of the localization regimes with high precision. Finally, as it is easy to vary the concentration in our model system, we will show that there is an optimal intermediate concentration beyond which localization disappears.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.704
Threshold uncertainty score0.199

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.237
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicRandom lasers and scattering mediaFrench-language works237,207