Evidence map›Paper›PMID 41455792›Full record

ArticleScientific reports2025

Enhancing the yield of bucket brigade quantum random access memory using redundancy repair.

Dongmin Kim, Sengthai Heng, Sanghyeon Lee, Youngsun Han

Abstract read
In one paragraph

Article in Scientific reports, 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

4 authors.

Dongmin KimDepartment of AI Convergence, Pukyong National University, Nam-gu, Busan, 48513, South Korea.
Sengthai HengDepartment of AI Convergence, Pukyong National University, Nam-gu, Busan, 48513, South Korea.
Sanghyeon LeeDepartment of AI Convergence, Pukyong National University, Nam-gu, Busan, 48513, South Korea.
Youngsun HanDepartment of AI Convergence, Pukyong National University, Nam-gu, Busan, 48513, South Korea. youngsun@pknu.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantum random access memory (qRAM) is an essential computing element for running oracle-based quantum algorithms. qRAM exploits quantum superposition to access all data stored in the memory cells simultaneously and guarantees the superior performance of quantum algorithms. A qRAM memory cell comprises logical qubits encoded through quantum error correction technology for successful operation against various quantum noises. In addition to quantum noise, the low-technology nodes based on silicon technology can increase the qubit density and may introduce defective qubits. As qRAM comprises many qubits, its yield will be reduced by defective qubits; these qubits must be handled using QEC scheme. However, the QEC scheme requires numerous physical qubits, which burdens resource overhead. In this paper, to resolve this overhead problem, we propose a novel quantum memory architecture that compensates for defective qubits by introducing redundant qubits. We also analyze the yield improvement offered by our proposed quantum memory architecture by varying the ideal fabrication error rate from 0.5 to 1% for different numbers of logical qubits in the qRAM. We demonstrate that for the qRAM comprising 1024 logical qubits, eight redundant logical qubits improved the yield by 95.92% from that of qRAM not employing the redundant repair scheme.

Indexed as

Quantum error correction (QEC)Quantum random access memory (qRAM)Redundant repairYield improvement

Identifiers

PMID41455792
PMCPMC12831000

What OpenQuestion holds

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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.