Evidence map›Paper›PMID 37253721›Full record

ArticleLight, science & applications2023

Photonic elementary cellular automata for simulation of complex phenomena.

Gordon H Y Li, Christian R Leefmans, James Williams, Alireza Marandi

Abstract read
In one paragraph

Article in Light, science & applications, 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. Deep learning with photonic neural cellular automata.Light, science & applications · 2024
    Article
  2. Review
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

4 authors.

Gordon H Y LiDepartment of Applied Physics, California Institute of Technology, Pasadena, CA, 91125, USA.ORCID http://orcid.org/0000-0001-8184-4915
Christian R LeefmansDepartment of Applied Physics, California Institute of Technology, Pasadena, CA, 91125, USA.
James WilliamsDepartment of Electrical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA.
Alireza MarandiDepartment of Applied Physics, California Institute of Technology, Pasadena, CA, 91125, USA. marandi@caltech.edu.ORCID http://orcid.org/0000-0002-0470-0050

Funding

National Science Foundation (NSF) 1846273National Science Foundation (NSF) 1918549United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research (AF Office of Scientific Research) FA9550-20-1-0040United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO) W911NF-23-1-0048
6 · The paper itself

Abstract

Cellular automata are a class of computational models based on simple rules and algorithms that can simulate a wide range of complex phenomena. However, when using conventional computers, these 'simple' rules are only encapsulated at the level of software. This can be taken one step further by simplifying the underlying physical hardware. Here, we propose and implement a simple photonic hardware platform for simulating complex phenomena based on cellular automata. Using this special-purpose computer, we experimentally demonstrate complex phenomena, including fractals, chaos, and solitons, which are typically associated with much more complex physical systems. The flexibility and programmability of our photonic computer present new opportunities to simulate and harness complexity for efficient, robust, and decentralized information processing using light.

Identifiers

PMID37253721
PMCPMC10229568

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.