Evidence map›Paper›PMID 41605961›Full record

ArticleNature communications2026

Coherent Ising machine based on polarization symmetry breaking in a driven Kerr resonator.

Liam Quinn, Yiqing Xu, Julien Fatome, Gian-Luca Oppo, Stuart G Murdoch, Miro Erkintalo, Stéphane Coen

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

7 authors.

Liam QuinnPhysics Department, The University of Auckland, Auckland, New Zealand. liam.quinn@auckland.ac.nz.
Yiqing XuPhysics Department, The University of Auckland, Auckland, New Zealand.ORCID http://orcid.org/0000-0001-5573-7964
Julien FatomeLaboratoire Interdisciplinaire Carnot de Bourgogne (ICB), UMR 6303 CNRS, Université Bourgogne Europe, 9 Avenue Alain Savary, Dijon, France.
Gian-Luca OppoSUPA and Department of Physics, University of Strathclyde, Glasgow, EU, Scotland.ORCID http://orcid.org/0000-0002-5376-4309
Stuart G MurdochPhysics Department, The University of Auckland, Auckland, New Zealand.ORCID http://orcid.org/0000-0002-9169-9472
Miro ErkintaloPhysics Department, The University of Auckland, Auckland, New Zealand.ORCID http://orcid.org/0000-0001-7753-7007
Stéphane CoenPhysics Department, The University of Auckland, Auckland, New Zealand.ORCID http://orcid.org/0000-0001-5605-5906

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Time-multiplexed networks of degenerate optical parametric oscillators have demonstrated remarkable success in simulating coupled Ising spins, thus providing a promising route to solving complex combinatorial optimization problems. In these systems, referred to as coherent Ising machines, spins are encoded in the oscillator phases, and measured at the system output using phase-sensitive techniques, making intricate phase stabilization necessary. Here, we introduce an optical Ising machine based on spontaneous polarization symmetry breaking in a coherently driven fiber Kerr nonlinear resonator. In our architecture, the spins are encoded in the polarization state, allowing robust, all-intensity readout with off-the-shelf telecom components. By operating in a newly-discovered regime where nonlinearity and topology lock the system's symmetry, we eliminate drift and bias, enabling uninterrupted Ising trials at optical speeds for over an hour, without manual intervention. This all-fiber platform not only simplifies the hardware but also opens a path to more stable, high-throughput coherent optical optimization devices for applications from finance to drug design and beyond.

Identifiers

PMID41605961
PMCPMC12953878

What OpenQuestion holds

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LicenceCC BY
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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.