Evidence map›Paper›PMID 40191671›Full record

ArticleNature photonics2025

Threading light through dynamic complex media.

Chaitanya K Mididoddi, Robert J Kilpatrick, Christina Sharp, Philipp Del Hougne, Simon A R Horsley, David B Phillips

Abstract read
In one paragraph

Article in Nature photonics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

6 authors.

Chaitanya K MididoddiPhysics and Astronomy, University of Exeter, Exeter, UK.ORCID 0000-0002-4877-5003
Robert J Kilpatrick *Physics and Astronomy, University of Exeter, Exeter, UK.ORCID 0000-0001-5119-6355
Christina Sharp *Physics and Astronomy, University of Exeter, Exeter, UK.
Philipp Del HougneUniversité de Rennes, CNRS, IETR - UMR 6164, Rennes, France.ORCID 0000-0002-4821-3924
Simon A R HorsleyPhysics and Astronomy, University of Exeter, Exeter, UK.ORCID 0000-0001-7242-7941
David B PhillipsPhysics and Astronomy, University of Exeter, Exeter, UK.ORCID 0000-0002-3711-4787

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The dynamic scattering of light impacts sensing and communication technologies throughout the electromagnetic spectrum. Here we introduce a new way to control the propagation of light through time-varying complex media. Our strategy is based on the observation that in many dynamic scattering systems, some parts of the medium will change configuration more slowly than others. We experimentally demonstrate a suite of new techniques to identify and guide light through the more temporally stable channels within dynamic scattering media-threading optical fields around multiple highly dynamic pockets hidden at unknown locations inside. We first show how the temporal fluctuations in scattered light can be suppressed by optimizing the wavefront of the incident field. Next, we demonstrate how to accelerate this procedure by two orders of magnitude using a physically realized form of adjoint gradient descent optimization. Finally, we show how the time-averaged transmission matrix reveals a basis of temporal fluctuation eigenchannels that can be used to increase the stability of beam shaping through time-varying complex media such as bending multimode fibres. Our work has potential future applications to a variety of technologies reliant on general wave phenomena subject to dynamic conditions, from optics to microwaves and acoustics.

Indexed as

Adaptive opticsImaging and sensingImaging techniques

Identifiers

PMID40191671
PMCPMC11968404

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.