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A Novel and Ultra-Efficient Design of Reversible Quantum Vedic Multiplier Cover

A Novel and Ultra-Efficient Design of Reversible Quantum Vedic Multiplier

Open Access
|Dec 2025

Abstract

Quantum computing has attracted increased attention in recent years owing to substantial advancements in quantum algorithms and system architecture. Quantum algorithms are implemented using quantum circuits. These circuits include an intrinsic reversibility and often have a substantial Boolean component that requires synthesis. A crucial characteristic of reversible circuits is the preservation of parity. Parity-preserving logic is a category that maintains the parity of both inputs and outputs, facilitating the detection of permanent and transient errors. Multiplier circuits are essential components in digital computing systems, playing a crucial role in the development of various hardware, including arithmetic circuits. This paper first introduces a novel block based on a transformationbased synthesis technique from the elementary quantum gates. Then it proposes a distinctive 2×2 parity-preserving reversible quantum Vedic multiplier based on the recommended block and prior gates. In addition, further designs of Vedic multipliers are provided, encompassing 4-bit, 8-bit, and 16-bit configurations. We illustrate that our design brings superior outcomes regarding quantum cost (QC), constant inputs (CI) count, CNOT-V/V+ count, garbage outputs (GO) count, and gate count (GC) in comparison to earlier designs. This study achieves an average decrease of 23.09%, 37.51%, 37.51%, 54.89%, and 19.38% in QC, CI, GO, GC, and CNOT-V/V+ count, respectively. Furthermore, all suggested circuits undergo appraisal and validation within the IBM quantum laboratory.

DOI: https://doi.org/10.2478/qic-2025-0030 | Journal eISSN: 3106-0544 | Journal ISSN: 1533-7146
Language: English
Page range: 552 - 567
Submitted on: Apr 1, 2025
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Accepted on: Oct 11, 2025
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Published on: Dec 31, 2025
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2025 Mojtaba Noorallahzadeh, Mohammad Mosleh, published by Cerebration Science Publishing Co., Limited
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.