Evidence map›Paper›PMID 41410820›Full record

ReviewNano convergence2025

Photonic variational quantum eigensolver for NISQ-compatible quantum technology.

Kang-Min Hu, Min Namkung, Hyang-Tag Lim

Abstract readReview
In one paragraph

Review in Nano convergence, 2025. 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

3 authors.

Kang-Min Hu *Center for Quantum Technology, Korea Institute of Science and Technology (KIST), Seoul, 02792, Korea.
Min Namkung *Center for Quantum Technology, Korea Institute of Science and Technology (KIST), Seoul, 02792, Korea.
Hyang-Tag LimCenter for Quantum Technology, Korea Institute of Science and Technology (KIST), Seoul, 02792, Korea. forestht@gmail.com.ORCID http://orcid.org/0000-0002-4068-2902

Funding

Institute for Information and Communications Technology Promotion RS-2023-00222863, RS-2025-02292999Korea Institute of Science and Technology 2E33541, 2E33571National Research Council of Science and Technolog CAP21034-000, GTL25011-000national research foundation of korea RS-2022-NR068817, 2023M3K5A1094805, RS-2024-00336079
6 · The paper itself

Abstract

Quantum computers have the potential to deliver speed-ups for solving certain important problems that are intractable for classical counterparts, making them a promising avenue for advancing modern computation. However, many quantum algorithms require deep quantum circuits, which are challenging to implement on current noisy devices. To address this limitation, variational quantum algorithms have been actively developed, enabling practical quantum computing in the noisy intermediate-scale quantum (NISQ) era. Among them, the variational quantum eigensolver (VQE) stands out as a leading approach for solving problems in quantum chemistry, many-body physics, and even integer factorization. The VQE algorithm can be implemented on various quantum hardware platforms, including photonic systems, quantum dots, trapped ions, neutral atoms, and superconducting circuits. In particular, photonic platforms offer several advantages: they operate at room temperature, exhibit low decoherence, and support multiple degrees of freedom, making them suitable for scalable, high-dimensional quantum computation. Here we present methodologies for realizing VQE on photonic systems, highlighting their potential for practical quantum computing. We first provide a theoretical overview of the VQE framework, focusing on the procedure for variationally estimating ground state energies. We then explore how photonic systems can implement these processes, showing that a wide variety of problems can be addressed using either multiple qubit states or a single qudit state.

Indexed as

Photonic systemQuantum computationVariational quantum eigensolver

Identifiers

PMID41410820
PMCPMC12714684

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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.