Evidence map›Paper›PMID 42230552›Full record

ArticleLight, science & applications2026

Optical in-memory computing using laser array.

Omar Alkhazragi

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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Omar AlkhazragiDepartment of Electrical Engineering, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, 31261, Saudi Arabia. omar.khazragi@kfupm.edu.sa.ORCID http://orcid.org/0000-0001-6247-842X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A new optical in-memory computing system based on an array of vertical-cavity surface-emitting lasers (VCSELs) has the potential to circumvent the Von Neumann bottleneck. The high modulation speed of the lasers in the array allows for fast computing and their high efficiency can enable edge computing in autonomous vehicles and drones. This efficient, highly scalable system was demonstrated to perform 900 million convolutions per second with 98% computing accuracy.

Identifiers

PMID42230552
PMCPMC13230864

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.