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

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.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-12-27
DOI
https://doi.org/10.1038/s41598-025-32955-2
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Sengthai Heng, Sanghyeon Lee, Dongmin Kim, Youngsun Han
Scientific Reports
Quantum Computing Algorithms and Architecture
article

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

Sengthai Heng, Sanghyeon Lee, Dongmin Kim, Youngsun Han
article en

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.

Scientific ReportsVol. 16(1)
Pukyong National University (KR)
Openalex Percentile: Top 18%
Quantum Computing Algorithms and Architecture
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.