Evidence map›Paper›PMID 38498068›Full record

ReviewNano convergence2024

An elementary review on basic principles and developments of qubits for quantum computing.

Eunmi Chae, Joonhee Choi, Junki Kim

Abstract readReview
In one paragraph

Review in Nano convergence, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Quantum computing applications in drug discovery.Briefings in bioinformatics · 2026
    Review
  4. Article
  5. Review
  6. Article
  7. Superconducting artificial neural networks and quantum circuits.Beilstein journal of nanotechnology · 2026
    Article
  8. Article
  9. 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

3 authors.

Eunmi ChaeDepartment of Physics, Korea University, Seoul , 02841, Republic of Korea. echae@korea.ac.kr.ORCID http://orcid.org/0000-0001-6128-5909
Joonhee ChoiDepartment of Electrical Engineering, Stanford University, Stanford, CA, 94305, USA. joonhee.choi@stanford.edu.
Junki KimSKKU Advanced Institute of Nanotechnology (SAINT) & Department of Nano Science and Technology, Sungkyunkwan University, Suwon, 16419, Republic of Korea. junki.kim.q@skku.edu.

Funding

Ministry of Education, Science and Technology RS-2023-00302576National Research Foundation of Korea 2021M3H3A1085299National Research Foundation of Korea 2022M3C1C8097622National Research Foundation of Korea 2022M3E4A105136512National Research Foundation of Korea 2022M3E4A1077340National Research Foundation of Korea 2022M3K4A109712211National Research Foundation of Korea 2022R1C1C100375812Stanford University the startup fund and the Terman Faculty Fellowship
6 · The paper itself

Abstract

An elementary review on principles of qubits and their prospects for quantum computing is provided. Due to its rapid development, quantum computing has attracted considerable attention as a core technology for the next generation and has demonstrated its potential in simulations of exotic materials, molecular structures, and theoretical computer science. To achieve fully error-corrected quantum computers, building a logical qubit from multiple physical qubits is crucial. The number of physical qubits needed depends on their error rates, making error reduction in physical qubits vital. Numerous efforts to reduce errors are ongoing in both existing and emerging quantum systems. Here, the principle and development of qubits, as well as the current status of the field, are reviewed to provide information to researchers from various fields and give insights into this promising technology.

Indexed as

Quantum computersQuantum operationsQubits

Identifiers

PMID38498068
PMCPMC10948723

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.