Evidence map›Paper›PMID 41716237›Full record

ArticleNature photonics2025

Integrated electro-optic digital-to-analog link for efficient computing and arbitrary waveform generation.

Yunxiang Song, Yaowen Hu, Xinrui Zhu, Keith Powell, Letícia Magalhães, Fan Ye, Hana Warner, Shengyuan Lu, Xudong Li, Dylan Renaud and 6 more

Abstract read
In one paragraph

Article in Nature photonics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
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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

16 authors.

Yunxiang SongJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Yaowen HuJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Xinrui ZhuJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Keith PowellJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Letícia MagalhãesJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Fan YeHyperLight Corporation, 501 Massachusetts Ave, Cambridge, MA 02139, USA.
Hana WarnerJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Shengyuan LuJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Xudong LiJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Dylan RenaudJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Norman LippokJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Di ZhuDepartment of Materials Science and Engineering, National University of Singapore, Singapore 117575, Singapore.
Benjamin VakocWellman Center of Photomedicine, Harvard Medical School and Massachusetts General Hospital, Boston, MA 02114, USA.
Mian ZhangHyperLight Corporation, 501 Massachusetts Ave, Cambridge, MA 02139, USA.
Neil SinclairJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Marko LončarJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.

Funding

TRD3: Percutaneous and Interstitial ImagingP41EB015903 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI Jacqueline Namati · 2012 to 2026
$22.4M
Lithium Niobate on Insolator (LNOI) Photonic Circuit Lasers for High-Speed, Wide-field OCTR21EY031895 · NEI · MASSACHUSETTS GENERAL HOSPITAL · PI LONCAR, MARKO, VAKOC, BENJAMIN JAMES · 2020 to 2021
$465k
NEI NIH HHS R21 EY031895NIBIB NIH HHS P41 EB015903
6 · The paper itself

Abstract

The rapid growth in artificial intelligence and modern communication systems demands innovative solutions for increased computational power and advanced signaling capabilities. Integrated photonics, leveraging the analog nature of electromagnetic waves at the chip scale, offers a promising complement to approaches based on digital electronics. To fully unlock their potential as analog processors, establishing a common technological base between conventional digital electronic systems and analog photonics is imperative to building next-generation computing and communications hardware. However, the absence of an efficient interface has critically challenged comprehensive demonstrations of analog advantage thus far, with the scalability, speed, and energy consumption as primary bottlenecks. Here, we address this challenge and demonstrate a general electro-optic digital-to-analog link (EO-DiAL) enabled by foundry-based lithium niobate nanophotonics. Using purely digital inputs, we achieve on-demand generation of (i) optical and (ii) electronic waveforms at information rates up to 186 Gbit/s. The former addresses the digital-to-analog electro-optic conversion challenge in photonic computing, showcasing high-fidelity MNIST encoding while consuming 0.058 pJ/bit. The latter enables a pulse-shaping-free microwave arbitrary waveform generation method with ultrabroadband tunable delay and gain. Our results pave the way for efficient and compact digital-to-analog conversion paradigms enabled by integrated photonics and underscore the transformative impact analog photonic hardware may have on various applications, such as computing, optical interconnects, and high-speed ranging.

Identifiers

PMID41716237
PMCPMC12915995

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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.