Evidence map›Paper›PMID 41345398›Full record

ArticleNature communications2025

Single-shot hyperspectral wavefront imaging.

Baptiste Blochet, Nathalie Lebas, Pascal Berto, Dimitrios Papadopoulos, Marc Guillon

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Baptiste BlochetUniversité Paris Cité, CNRS, Saints-Pères Paris Institute for the Neurosciences, Paris, France. baptiste.blochet@u-paris.fr.ORCID http://orcid.org/0000-0003-1457-4542
Nathalie LebasLULI-CNRS, CEA, Sorbonne Universite, Ecole Polytechnique, Institut Polytechnique de Paris, Palaiseau, France.
Pascal BertoUniversité Paris Cité, CNRS, Saints-Pères Paris Institute for the Neurosciences, Paris, France.
Dimitrios PapadopoulosLULI-CNRS, CEA, Sorbonne Universite, Ecole Polytechnique, Institut Polytechnique de Paris, Palaiseau, France.
Marc GuillonUniversité Paris Cité, CNRS, Saints-Pères Paris Institute for the Neurosciences, Paris, France. marc.guillon@u-paris.fr.ORCID http://orcid.org/0000-0002-9945-4605

Funding

Agence Nationale de la Recherche (French National Research Agency) ANR-21-CE24-001401Agence Nationale de la Recherche (French National Research Agency) ANR-24-CE42-1853
6 · The paper itself

Abstract

Single-shot hyperspectral wavefront sensing is essential for applications like spatio-spectral coupling metrology in high-power laser or fast material dispersion imaging. Under broadband illumination, traditional wavefront sensors assume an achromatic wavefront, which makes them unsuitable. We introduce a hyperspectral wavefront sensing scheme based on the Hartmann wavefront sensing principles, employing a multicore fiber as a Hartmann mask to overcome these limitations. Our system leverages the angular memory effect and limited spectral correlation width of the multicore fiber, encoding wavefront gradients into displacements and the spectral information into uncorrelated speckle patterns. This method retains the simplicity, compactness, and single-shot capability of conventional wavefront sensors, with only a slight increase in computational complexity. It also allows a tunable trade-off between spatial and spectral resolution. We demonstrate its efficacy for recording the hyperspectral wavefront cube from single-pulse acquisitions at the Apollon multi-petawatt laser facility, and for performing multispectral microscopic imaging of dispersive phase objects.

Identifiers

PMID41345398
PMCPMC12774951

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.