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arXiv:1606.09225

Quintuple: a Python 5-qubit quantum computer simulator to facilitate cloud quantum computing

C. Corbett Moran

Published Jun 29, 2016• 2 citations
arXivHTMLPDF

Abstract

In May 2016 IBM released access to its 5-qubit quantum computer to the scientific community, its "IBM Quantum Experience" since acquiring over 25,000 users from students, educators and researchers around the globe. In the short time since the "IBM Quantum Experience" became available, a flurry of research results on 5-qubit systems have been published derived from the platform hardware. Quintuple is an open-source object-oriented Python module implementing the simulation of the "IBM Quantum Experience" hardware. Quintuple quantum algorithms can be programmed and run via a custom language fully compatible with the "IBM Quantum Experience" or in pure Python. Over 40 example programs are provided with expected results, including Grover's Algorithm and the Deutsch-Jozsa algorithm. Quintuple contributes to the study of 5-qubit systems and the development and debugging of quantum algorithms for deployment on the "IBM Quantum Experience" hardware.

DOI
10.48550/arxiv.1606.09225

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In May 2016 IBM released access to its 5-qubit quantum computer to the scientific community, its "IBM Quantum Experience" since acquiring over 25,000 users from students, educators and researchers around the globe. In the short time since the "IBM Quantum Experience" became available, a flurry of research results on 5-qubit systems have been published derived from the platform hardware. Quintuple is an open-source object-oriented Python module implementing the simulation of the "IBM Quantum Experience" hardware. Quintuple quantum algorithms can be programmed and run via a custom language fully compatible with the "IBM Quantum Experience" or in pure Python. Over 40 example programs are provided with expected results, including Grover's Algorithm and the Deutsch-Jozsa algorithm. Quintuple contributes to the study of 5-qubit systems and the development and debugging of quantum algorithms for deployment on the "IBM Quantum Experience" hardware.
In May 2016 IBM released access to its 5-qubit quantum computer to the scientific community, its “IBM Quantum Experience” since acquiring over 60,000 users from students, educators and researchers around the globe. In the time since the “IBM Quantum Experience” became available, a flurry of research results on 5-qubit systems has been published derived from the platform hardware. Quintuple is an open-source object-oriented Python module implementing the ideal simulation of “IBM’s Quantum Experience” hardware. Quintuple quantum algorithms can be programmed and run via a custom language fully compatible with the “IBM’s Quantum Experience” or in pure Python. Over 40 example programs are provided with expected results, including Grover’s Algorithm and the Deutsch-Jozsa algorithm. Quintuple’s implementation is aimed at students and educators wishing to incorporate quantum computing into the classroom and enables students to follow a quantum computing calculation step-by-step and to verify hand calculations. For these students and educators, Quintuple contributes to the study of 5-qubit systems and the development and debugging of quantum algorithms for deployment on the “IBM Quantum Experience” hardware.
In the past few years, IBM has expanded their Quantum Experience to include a high-level Python module called Qiskit as well as a 15-qubit machine (ibmq_16_melbourne). In order to evaluate IBM’s progress, we create an overview of the processes involved in developing and running an algorithm on IBM’s quantum machines. This includes exploring the new resources that IBM has made available recently including the Qiskit Python module. Then, we test textbook algorithms such as the Deutsch-Jozsa algorithm, Grover’s search algorithm, and Quantum Fourier Transform on ibmq_16_melbourne and compare the results with the output of a simulator. Constraints imposed by IBM’s Quantum Experience and significant differences between algorithm performance on IBM's quantum hardware and the simulator will be used to assess IBM’s quantum computing capabilities.
Quantum computing is a rapidly emerging and promising field with the potential to transform various research domains including drug design, network technologies, and sustainable energy solutions. Due to the inherent complexity and divergence from classical computing, several major quantum computing libraries have been developed to implement quantum algorithms, namely IBM Qiskit, Amazon Braket, Cirq, PyQuil, and PennyLane. These libraries enable quantum simulations on classical computers and execution on corresponding quantum hardware, such as Qiskit programs on IBM quantum computers. Despite the variations among these platforms, the core concepts remain the same. One notable challenge is the absence of a Python-based quantum interpreter to connect these five frameworks, a gap that remains to be fully addressed. In response, our work introduces a tool called Qinterpreter, accessible through a user-friendly web interface, the Quantum Science Gateway QubitHub, which operates alongside Jupyter Notebooks. Built using the Python Object-Oriented Programming System, Qinterpreter unifies the five well-known quantum libraries into a single framework. Designed as an educational tool for students and researchers entering the quantum domain, Qinterpreter enables the straightforward development and execution of quantum circuits across such platforms. This work highlights the quantum programming versatility and accessibility of Qinterpreter and underscores our ultimate goal of pervading Quantum Computing through younger, less specialized, and diverse cultural and national communities.
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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.
One of the greatest technological advancements in the last century lies in digital computer science. The idea of storing information and performing complicated calculations with the help of bits, i.e., 0 and 1. But due to a sudden surge in data, the classical computer system has been becoming weak in data processing. Quantum computers offer promising substantial speedup over classical computers for many applications. Quantum chip fabrication has made remarkable gains in recent years, with the number of qubits and fidelity growing. In general computing, a binary digit is the smallest unit of information or a bit. “In quantum computing, the term Qubit (Quantum Bit) serves the exact function of the term bit.” IBM Research released the IBMQ Experience in 2018, the first quantum computer that anyone can use and make accessible to a huge audience of different countries through cloud access. IBM also introduced the tool QISKIT (Quantum information software kit), which enables teachers, researchers, and developers to write coding and run their coding on quantum machines. It also includes different packages of quantum computing. In this paper, the author has discussed different steps to install qiskit. Mainly this paper focused on the “programming and application side of quantum computing.” Qiskit tools used in the python programming language. The “quantum circuits” are fabricated with the use of quantum gates and favorable algorithms with less execution time