Evidence map›Paper›PMID 39678184›Full record

ArticleNanophotonics (Berlin, Germany)2024

Experimental demonstration of a photonic reservoir computing system based on Fabry Perot laser for multiple tasks processing.

Xingxing Guo, Hanxu Zhou, Shuiying Xiang, Qian Yu, Yahui Zhang, Yanan Han, Tao Wang, Yue Hao

Erratum issuedAbstract read
In one paragraph

Article in Nanophotonics (Berlin, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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

5 · Who and what money

Authors and funding

8 authors.

Xingxing GuoState Key Laboratory of Integrated Service Networks, Xidian University, Xi'an 710071, China.
Hanxu ZhouState Key Laboratory of Integrated Service Networks, Xidian University, Xi'an 710071, China.
Shuiying XiangState Key Laboratory of Integrated Service Networks, Xidian University, Xi'an 710071, China.ORCID https://orcid.org/0000-0002-1698-2083
Qian YuState Key Laboratory of Integrated Service Networks, Xidian University, Xi'an 710071, China.
Yahui ZhangState Key Laboratory of Integrated Service Networks, Xidian University, Xi'an 710071, China.
Yanan HanState Key Laboratory of Integrated Service Networks, Xidian University, Xi'an 710071, China.
Tao WangState Key Laboratory of Integrated Service Networks, Xidian University, Xi'an 710071, China.
Yue HaoState Key Discipline Laboratory of Wide Bandgap Semiconductor Technology, School of Microelectronics, Xidian University, Xi'an 710071, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Photonic reservoir computing (RC) is a simple and efficient neuromorphic computing framework for human cortical circuits, which is featured with fast training speed and low training cost. Photonic time delay RC, as a simple hardware implementation method of RC, has attracted widespread attention. In this paper, we present and experimentally demonstrate a time delay RC system based on a Fabry Perot (FP) laser for multiple tasks processing. Here, the various tasks are attempted to perform in parallel in the multiple longitudinal modes of the FP laser. It is found that the time delay RC system based on the FP laser can successfully handle different tasks across multiple longitudinal modes simultaneously. The experimental results demonstrate the potential of the time delay RC system based on the FP laser to achieve multiple tasks processing, providing various possibilities for improving the information processing ability of neural morphology RC systems, and promoting the development of RC systems.

Indexed as

Fabry Perot lasermultiple longitudinal modesmultiple tasks processingphotonic time delay reservoir computing

Identifiers

PMID39678184
PMCPMC11636514

What OpenQuestion holds

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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.