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International Conference for Emerging Technology (INCET)

Programmable Swap Gate for Quantum Computing Applications

Kabir Gaba, Sapna Tiwari, Komal Sharma, Gaurav Kumar Bharti

Published May 23, 2025• 1 citation
Publisher

Abstract

Quantum logic gates are fundamental building blocks of quantum computing, enabling the manipulation of quantum bits (qubits) for computations and communications. This paper presents a novel approach to implementing the SWAP gate, a crucial two-qubit quantum operation, using Python programming. The SWAP gate facilitates the exchange of quantum states between two qubits and plays a significant role in qubit routing and circuit optimization. The implementation leverages Python's quantum computing libraries, such as Qiskit, to simulate and validate the functionality of the SWAP gate. Numerical simulations demonstrate the successful operation of the gate and its integration into larger quantum circuits. The paper provides a comprehensive guide for Python-based SWAP gate development, contributing to the advancement of quantum algorithm design and for different applications in quantum computing.

DOI
10.1109/incet64471.2025.11140914

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Quantum logic gates are fundamental building blocks of quantum computing, enabling the manipulation of quantum bits (qubits) for computations and communications. This paper presents a novel approach to implementing the SWAP gate, a crucial two-qubit quantum operation, using Python programming. The SWAP gate facilitates the exchange of quantum states between two qubits and plays a significant role in qubit routing and circuit optimization. The implementation leverages Python's quantum computing libraries, such as Qiskit, to simulate and validate the functionality of the SWAP gate. Numerical simulations demonstrate the successful operation of the gate and its integration into larger quantum circuits. The paper provides a comprehensive guide for Python-based SWAP gate development, contributing to the advancement of quantum algorithm design and for different applications in quantum computing.
Abstract The SWAP gate (SWAP operator) is a two-qubit quantum gate that exchanges the states of the two qubits. It is widely used to move quantum information between qubits within a circuit, enabling flexible rearrangement of quantum states. SWAP gates are essential for circuit optimization, especially in architectures where qubit connectivity is limited. By efficiently redistributing qubit states, they allow complex operations to be performed even when the physical layout restricts direct interactions between certain qubits. This gate is a fundamental building block for implementing modular and scalable quantum circuits. Understanding the SWAP gate is crucial for designing efficient quantum algorithms and managing qubit resources in practical quantum computations. Its use is particularly significant in near-term noisy intermediate-scale quantum (NISQ) devices, where minimizing gate count and optimizing qubit layout are critical for performance.
For many practical applications, Quantum computers offer major speed-ups over traditional machines. The production of quantum chips has recently made tremendous strides, with the quantity of Qubits increasing and fidelity increasing. The smallest unit of information is the binary digit i.e. bit in general computing. In Quantum Computing the term Qubit (Quantum Bit) is used for the same purpose. In order to differentiate between a classical bit and a Qubit, Bra-Ket or Dirac notation is used. So, the Qubits are represented as |0〉 and |1〉 and are often read as Ket 0 for zero state and Ket 1 for one state. In this paper mainly programming and application sides of Quantum Computing are focused. For that, Qiskit module and its tools are used in Python programming language. General circuit optimization scheme is given. The Quantum circuits with the concept of Quantum Gates implemented are stronger compared to the optimizing algorithm and with faster execution time. In addition, for prime factorization, access to IBM's Quantum computer is carried out successfully.
Abstract Advances in quantum information science are closely related to our ability to prepare, manipulate, and measure the states of multiple quantum bits (qubits). To this end, quantum gates are the key components by which specific operations over individual and multiple qubits are implemented. In the context of quantum optics, qubits can be encoded in any degree of freedom of a multi-photon state, e.g. polarization, frequency or spatial configuration. The faithful reciprocal exchange of information between two qubits, a so-called SWAP, is one of the fundamental operations that underpin modern quantum architectures. Here, we present a novel method realizing multiple-qubit SWAP operations over several qubits, without relying on any other gates, in an integrated-photonic setting. In principle, our approach allows for the implementation of SWAP operations with unity efficiency regardless of the number of involved qubits. Further, we discuss how this approach can be applied to qudits. Our findings provide a powerful new functional element for the design of compact quantum-photonic circuitry.
Recent advancements in computing speed and capacity of Artificial Intelligence (AI) algorithms have reached a saturation level in performance due to the continuous application of Moore's law which resulted in the memory wall phenomenon. Quantum computing (QC), based on the principles of quantum mechanics which include superposition and entanglement, has the potential to contribute to the advancements of AI by providing exponential speedup. Quantum computers use quantum bits, also known as qubits, as the metric to demonstrate the power of quantum technology. Qubits, the fundamental unit of quantum information can exist in two states, 0 and 1, simultaneously, leveraging the principle of superposition. Quantum gates are the building blocks of quantum circuits, operating on qubits to transform one quantum state into another, and are comparative to classical logic gates. Designing and simulating quantum circuits can be completed using the Qiskit library design by IBM. Qiskit is a cloud-based, open access platform to real quantum computers with 5 to 16 qubits. This paper offers a straightforward tutorial on implementing one, two and three-qubit quantum gates, as well as designing quantum circuits using the Qiskit library, illustrated with an example of a quantum half adder implementation.
This paper explains the roadmap for running quantum circuit programs based on the Qiskit library in quantum simulators as well as real cloud-based IBM quantum computers. Qiskit is a free and open-source software development platform based on the Python programming language that is used in quantum programming. Qiskit acts as a link between quantum computing’s theoretical foundations and the practical aspects of programming and experimentation. It also allows users to experiment with and develop quantum algorithms, as well as simulate and execute them on simulators and real-world cloud-based quantum devices. It also simplifies the quantum programming process and allows a diverse range of people to participate in the exciting world of quantum computing. The paper, on the other hand, provides the mathematical foundation for analyzing quantum circuits and algorithms using linear algebra principles, as they provide the tools needed to describe and manipulate quantum states and operations. Furthermore, the paper shows quantum circuit design and implementation using real Qiskit codes.
Quantum computing promises an exponential speedup improvement in the time required to solve certain computational problems by leveraging the principles of quantum mechanics.While the potential power of quantum computers is well-established, their practical implementation poses significant challenges ranging from scalability to decoherence and noise.This paper presents QPy, a Python-based quantum circuit simulator that I programmed and designed to track the quantum state of a model quantum computer through the application of quantum gates to qubits.By performing the requisite matrix calculations, the simulator facilitates the understanding of quantum algorithms through the visualization of the underlying mathematics.This tool enables researchers to explore and implement various quantum protocols efficiently to test and build algorithms.