Evidence map›Paper›PMID 42350380›Full record

ArticleNature communications2026

Geometric phase sensing using seismic waves for comprehensive volcano monitoring at Kı̄lauea Hawaii.

Bingxu Luo, Susan Beck, Pierre Deymier, Keith Runge, Eric Kiser, Pranabendu Moitra, Falk Huettmann, Samy Missoum, Marat Latypov, Elizabeth Whitney and 2 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Bingxu LuoNew Frontiers of Sound Science and Technology Center, The University of Arizona, Tucson, AZ, USA. bingxuluo@arizona.edu.ORCID http://orcid.org/0000-0001-7075-1529
Susan BeckNew Frontiers of Sound Science and Technology Center, The University of Arizona, Tucson, AZ, USA.
Pierre DeymierNew Frontiers of Sound Science and Technology Center, The University of Arizona, Tucson, AZ, USA.ORCID http://orcid.org/0000-0002-1088-7958
Keith RungeNew Frontiers of Sound Science and Technology Center, The University of Arizona, Tucson, AZ, USA.ORCID http://orcid.org/0000-0001-6467-7481
Eric KiserDepartment of Geosciences, The University of Arizona, Tucson, AZ, USA.
Pranabendu MoitraDepartment of Geosciences, The University of Arizona, Tucson, AZ, USA.
Falk HuettmannNew Frontiers of Sound Science and Technology Center, The University of Arizona, Tucson, AZ, USA.ORCID http://orcid.org/0000-0003-4315-5451
Samy MissoumNew Frontiers of Sound Science and Technology Center, The University of Arizona, Tucson, AZ, USA.
Marat LatypovNew Frontiers of Sound Science and Technology Center, The University of Arizona, Tucson, AZ, USA.ORCID http://orcid.org/0000-0003-4416-0877
Elizabeth WhitneyNew Frontiers of Sound Science and Technology Center, The University of Arizona, Tucson, AZ, USA.ORCID http://orcid.org/0000-0002-2187-874X
Jiayang WangNew Frontiers of Sound Science and Technology Center, The University of Arizona, Tucson, AZ, USA.
Sinan S SchabibNew Frontiers of Sound Science and Technology Center, The University of Arizona, Tucson, AZ, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monitoring volcanic activity requires sensitive tools capable of detecting subtle subsurface changes across eruptive cycles. While seismic methods are widely used to study volcanic unrest, few provide continuous tracking throughout eruptive stages with clearly interpretable signals. We present a geometric phase sensing approach, rooted in topological acoustics, that encodes the intrinsic geometry of the seismic wavefield. By integrating signals across a station array, the geometric phase change (Δη) captures wavepath-integrated medium perturbations, providing a stable measure of evolving subsurface conditions distinct from conventional waveform coherence metrics. Applied to Kı̄lauea volcano, Δη closely tracks precursory magmatic pressurization and co-eruptive caldera collapse during the 2018 eruption, identifies two major intrusion events and post-eruptive recovery spanning five eruptions from 2020 to 2024. Δη exhibits systematic and interpretable signatures of eruptive transitions, even under strongly perturbed ambient noise conditions. Numerical simulations corroborate these observations, indicating a sensitivity of  ~15.0% per MPa to subsurface pressure changes. By leveraging geometric phase approach, we establish a monitoring framework applicable to volcanic and other dynamic Earth systems.

Identifiers

PMID42350380
PMCPMC13448816

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.