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Related Experiment Video

Updated: Sep 17, 2025

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform

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Published on: August 2, 2019

Optimized quantum folding Barrett reduction for quantum modular multipliers.

Jian Zhang¹, Seong-Min Cho¹, Changyeol Lee¹

¹Department of Electrical Engineering, Graduate School of Hanyang University, Seoul, 04763, South Korea.

Scientific Reports

|July 2, 2025

Summary

This summary is machine-generated.

We developed an optimized quantum modular multiplication circuit using Barrett reduction. This new approach significantly reduces circuit complexity and T-depth, improving performance for quantum computations.

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Area of Science:

Quantum Computing
Quantum Algorithms
Modular Arithmetic

Background:

Quantum circuit design faces limitations in modular operations due to reversibility constraints.
Efficient modular multiplication is crucial for various quantum algorithms and cryptographic applications.

Purpose of the Study:

To propose and implement an optimized quantum modular operation scheme based on Barrett reduction.
To reduce the T-depth and resource requirements of quantum modular multiplication circuits.

Main Methods:

Implemented three versions of quantum circuits for Barrett reduction, including an optimized folding approach.
Analyzed quantum resource requirements (gate counts, qubit usage) and T-depth for each version.
Compared the performance of the proposed optimized scheme against existing methods.

Main Results:

The optimized folding Barrett reduction scheme demonstrates superior performance.
Achieved a significantly reduced T-depth of [Formula: see text] compared to traditional methods with T-depth of approximately [Formula: see text].
The proposed circuit is compatible with quantum-quantum and quantum-classical multiplication.

Conclusions:

The optimized Barrett reduction scheme offers a more efficient solution for quantum modular multiplication.
This advancement can enhance the feasibility of complex quantum algorithms requiring modular arithmetic.
The reduced circuit complexity paves the way for more scalable quantum computing applications.