Evidence map›Paper›PMID 41851076›Full record

ArticleLight, science & applications2026

Quantum-enhanced reconfigurable in-memory stochastic computing.

Hong-Zhe Yang, Jian-Peng Dou, Feng Lu, Xiao-Wen Shang, Chao-Ni Zhang, Heng Zhou, Hao Tang, Xian-Min Jin

Abstract read
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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

8 authors.

Hong-Zhe Yang *Center for Integrated Quantum Information Technologies (IQIT), School of Physics and Astronomy and State Key Laboratory of Photonics and Communications, Shanghai Jiao Tong University, Shanghai, China.
Jian-Peng Dou *Center for Integrated Quantum Information Technologies (IQIT), School of Physics and Astronomy and State Key Laboratory of Photonics and Communications, Shanghai Jiao Tong University, Shanghai, China.
Feng LuCenter for Integrated Quantum Information Technologies (IQIT), School of Physics and Astronomy and State Key Laboratory of Photonics and Communications, Shanghai Jiao Tong University, Shanghai, China.
Xiao-Wen ShangCenter for Integrated Quantum Information Technologies (IQIT), School of Physics and Astronomy and State Key Laboratory of Photonics and Communications, Shanghai Jiao Tong University, Shanghai, China.ORCID http://orcid.org/0000-0003-2454-0012
Chao-Ni ZhangCenter for Integrated Quantum Information Technologies (IQIT), School of Physics and Astronomy and State Key Laboratory of Photonics and Communications, Shanghai Jiao Tong University, Shanghai, China.
Heng ZhouCenter for Integrated Quantum Information Technologies (IQIT), School of Physics and Astronomy and State Key Laboratory of Photonics and Communications, Shanghai Jiao Tong University, Shanghai, China.
Hao TangCenter for Integrated Quantum Information Technologies (IQIT), School of Physics and Astronomy and State Key Laboratory of Photonics and Communications, Shanghai Jiao Tong University, Shanghai, China.ORCID http://orcid.org/0000-0001-8418-924X
Xian-Min JinCenter for Integrated Quantum Information Technologies (IQIT), School of Physics and Astronomy and State Key Laboratory of Photonics and Communications, Shanghai Jiao Tong University, Shanghai, China. xianmin.jin@sjtu.edu.cn.ORCID http://orcid.org/0000-0002-2809-7882

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In-memory computing, which enables computation directly within memory, represents an efficient approach to processing massively parallel computation tasks that are intractable for conventional computers. However, implementations of in-memory computing have been primarily limited to the classical regime, with its nonclassical counterpart yet to be fully explored. Quantum memory, with its unique capability to generate, preserve, and nontrivially operate on quantum states, offers spectacular quantum-enhanced advantages and is thus a promising candidate for in-memory computing. Here, leveraging a room-temperature quantum memory, we demonstrate a quantum-enhanced and reconfigurable in-memory stochastic computing system, where correlated photons, randomly produced in the quantum memory, serve as the computing resources. We show that addition and multiplication operations can be straightforwardly achieved by accumulating photon counts, and multiple computing tasks can be accelerated by mapping them into parallel accumulations of photon counts. Furthermore, the calculation results are obtained through stochastic processes, ensuring security in remote computation since no efficient information can be distinguished by eavesdropping on a small portion of the computation data. This in-memory computing system is enhanced by nonclassical correlations, which accelerate computing process and may stimulate future research and applications in the emerging field of quantum-enhanced computing architectures.

Identifiers

PMID41851076
PMCPMC13000280

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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.