Evidence map›Paper›PMID 42469215›Full record

ArticleLight, science & applications2026

All-optical computing towards 100-GHz clock rates.

Gordon H Y Li, Midya Parto, Jinhao Ge, Qing-Xin Ji, Maodong Gao, Yan Yu, James Williams, Robert M Gray, Christian R Leefmans, Nicolas Englebert and 2 more

Abstract read
In one paragraph

Article in Light, science & applications, 2026. 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

12 authors.

Gordon H Y Li *Department of Applied Physics, California Institute of Technology, Pasadena, 91125, CA, USA.ORCID http://orcid.org/0000-0001-8184-4915
Midya Parto *Department of Electrical Engineering, California Institute of Technology, Pasadena, 91125, CA, USA.ORCID http://orcid.org/0000-0003-2100-5671
Jinhao Ge *T. J. Watson Laboratory of Applied Physics, California Institute of Technology, Pasadena, 91125, CA, USA.
Qing-Xin JiT. J. Watson Laboratory of Applied Physics, California Institute of Technology, Pasadena, 91125, CA, USA.ORCID http://orcid.org/0000-0002-6336-8350
Maodong GaoPhysics and Informatics Laboratories, NTT Research, Inc., Sunnyvale, 94085, CA, USA.
Yan YuT. J. Watson Laboratory of Applied Physics, California Institute of Technology, Pasadena, 91125, CA, USA.
James WilliamsDepartment of Electrical Engineering, California Institute of Technology, Pasadena, 91125, CA, USA.
Robert M GrayDepartment of Electrical Engineering, California Institute of Technology, Pasadena, 91125, CA, USA.ORCID http://orcid.org/0000-0001-5980-8774
Christian R LeefmansDepartment of Applied Physics, California Institute of Technology, Pasadena, 91125, CA, USA.
Nicolas EnglebertDepartment of Electrical Engineering, California Institute of Technology, Pasadena, 91125, CA, USA.ORCID http://orcid.org/0000-0002-5170-9576
Kerry J VahalaT. J. Watson Laboratory of Applied Physics, California Institute of Technology, Pasadena, 91125, CA, USA.ORCID http://orcid.org/0000-0003-1783-1380
Alireza MarandiDepartment of Applied Physics, California Institute of Technology, Pasadena, 91125, CA, USA. marandi@caltech.edu.ORCID http://orcid.org/0000-0002-0470-0050

Funding

National Science Foundation (NSF) 1918549United 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

A computer's clock rate ultimately determines the minimum time between sequential operations or instructions. Despite exponential advances in electronic computer performance due to Moore's Law and increasingly parallel system architectures, clock rates of conventional processors have remained stagnant at ~5 GHz for nearly two decades. This creates a significant challenge for applications requiring real-time processing or control of ultrafast information systems. Here, we break this barrier by proposing and experimentally demonstrating computing based on an all-optical recurrent neural network leveraging the ultrafast characteristics of linear and nonlinear optical operations while circumventing electronic bottlenecks. The all-optical computer realizes linear operations, nonlinear functions, and memory entirely in the optical domain with accuracy surpassing a purely linear model up to 80 GHz clock rates depending on the task. We experimentally demonstrate a prototypical task of noisy waveform classification as well as perform ultrafast in-situ analysis of the soliton states from integrated optical microresonators. We further illustrate the application of the architecture for generative artificial intelligence based on quantum fluctuations to generate images even in the absence of input optical signals. Our results highlight the potential of all-optical computing beyond what can be achieved with digital electronics by utilizing ultrafast linear, nonlinear, and memory functions and quantum fluctuations.

Identifiers

PMID42469215
PMCPMC13379394

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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.