journal article·2025-10-01Open access

Design and implementation of a nanoscale digital switched network for quantum-based communication applications

Rongxuan Jin, Mohammad Saleh

AIP Advances· Volume 15· Issue 10

Abstract

In the modern era, communications and data exchanges via devices and users are fundamental to the transmission of data on networks and connections. The use of circuit-switched networks is critical in the routing of input information between the users of the network, in which high speed, low power consumption, and small area usage are important. However, it is essential to design and build low-power, high-speed devices, such as circuit-switched networks, because the implementation of these essential structures will result in a significant improvement in the overall performance efficiency of the network system structure. Furthermore, low energy consumption and limited occupied area are regarded as significant challenges in circuit-switched networks in traditional non-complementary metal-oxide semiconductor (CMOS) technology, so high-performance quantum technology must be used in order to overcome these crucial shortcomings. An emerging nanotechnology known as quantum-dot cellular automata (QCA) has many potential advantages over CMOS, including a much smaller area, low energy dissipation, and fast operating speed. This paper proposes an optimized design and implementation of a QCA-based crossbar switch for transmitter and receiver circuits to create an efficient circuit-switched network. The new designs are superior to their counterparts in existing designs in that all utilize a coplanar layout that has low cell count, low latency, and low power consumption. Design and validation testing are performed using QCADesigner 2.0.3 and QCADesigner-E tools, which establish that the performance measures of the proposal have significantly improved over earlier work.
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Research context

OpenAlex topics: Quantum-Dot Cellular Automata · Advancements in Semiconductor Devices and Circuit Design · Advanced Memory and Neural Computing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Electronic Engineering, Xi’an Aeronautical University 1 , Xi’an, Shaanxi 710077,

Engineering Department, Aleppo University 2 ,

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