Evidence map›Paper›PMID 37018406›Full record

ArticleScience advances2023

Disordered topological graphs enhancing nonlinear phenomena.

Zhetao Jia, Matteo Seclì, Alexander Avdoshkin, Walid Redjem, Elizabeth Dresselhaus, Joel Moore, Boubacar Kanté

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Science advances, 2023. 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

7 authors.

Zhetao JiaDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA 94720, USA.ORCID 0000-0002-2897-4793
Matteo SeclìDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA 94720, USA.ORCID 0000-0002-9608-096X
Alexander AvdoshkinDepartment of Physics, University of California, Berkeley, Berkeley, CA 94720, USA.
Walid RedjemDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA 94720, USA.
Elizabeth DresselhausDepartment of Physics, University of California, Berkeley, Berkeley, CA 94720, USA.ORCID 0000-0002-2602-2625
Joel MooreDepartment of Physics, University of California, Berkeley, Berkeley, CA 94720, USA.ORCID 0000-0002-4294-5761
Boubacar KantéDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA 94720, USA.ORCID 0000-0001-5633-4163

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Complex networks play a fundamental role in understanding phenomena from the collective behavior of spins, neural networks, and power grids to the spread of diseases. Topological phenomena in such networks have recently been exploited to preserve the response of systems in the presence of disorder. We propose and demonstrate topological structurally disordered systems with a modal structure that enhances nonlinear phenomena in the topological channels by inhibiting the ultrafast leakage of energy from edge modes to bulk modes. We present the construction of the graph and show that its dynamics enhances the topologically protected photon pair generation rate by an order of magnitude. Disordered nonlinear topological graphs will enable advanced quantum interconnects, efficient nonlinear sources, and light-based information processing for artificial intelligence.

Identifiers

PMID37018406
PMCPMC10075993

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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.