In this chapter we take a look at quantum computing in the cloud with IBM Q: the first platform of its kind. The chapter starts with an overview of the composer, the web console used to visually create circuits, submit experiments, explore hardware devices, and more. Next, you will learn how to create your first experiment and submit it to the simulator or real quantum device. IBM Quantum features a powerful REST API to control the life cycle of the experiment, and this chapter will show you how with detailed descriptions of the endpoints and request parameters. Finally, the chapter ends with a series of exercises to put your REST API skills to the test. Let’s get started.
In this chapter we take a look at quantum computing in the cloud with IBM Q: the first platform of its kind. The chapter starts with an overview of the composer, the web console used to visually create circuits, submit experiments, explore hardware devices, and more. Next, you will learn how to create your first experiment and submit it to the simulator or real quantum device. IBM Quantum features a powerful REST API to control the life cycle of the experiment, and this chapter will show you how with detailed descriptions of the endpoints and request parameters. Finally, the chapter ends with a series of exercises to put your REST API skills to the test. Let’s get started.
In this chapter we take a look at quantum computing in the cloud with IBM Q Experience: the first platform of its kind. The chapter starts with an overview of the Composer, the web console used to visually create circuits, submit experiments, explore hardware devices, and more. Next, you will learn how to create your first experiment and submit it to the simulator or real quantum device. IBM Q Experience features a powerful REST API to control the life cycle of the experiment, and this chapter will show you how with detailed descriptions of the end points and request parameters. Finally, the chapter ends with a practical implementation of the official Python library (dubbed IBMQuantumExperience) for Node JS. This custom Node JS library will put your asynchronous Javascript and REST API skills to the test. Let’s get started.
Abstract This practical guide introduces hands-on quantum computing, based on IBM Q learning resources. The exercises were completed by the author on April 28, 2024, using IBM Q cloud resources. The course provides a practical framework for understanding and experimenting with modern quantum computers, covering realistic use cases, circuit execution, and best practices for operating quantum processors with 100 or more qubits. Participants explore the concept of quantum usefulness, which refers to the practical utility of quantum computers in solving real-world problems, distinguishing it from quantum advantage, which is the point where quantum systems outperform classical computers on meaningful tasks. The course emphasizes that while classical computers remain highly powerful and adaptive, the evolving capabilities of quantum processors offer unique opportunities in computation that can complement classical methods. Hands-on exercises guide participants through practical aspects of designing and executing quantum circuits, running experiments on simulators and cloud-accessible quantum hardware, and interpreting results. This approach bridges theoretical knowledge with applied skills, enabling students and researchers to explore the current potential and limitations of quantum computing. The guide also contextualizes quantum computing within decades of classical computational development, highlighting how quantum devices may transform computational paradigms in fields such as optimization, chemistry, cryptography, and machine learning.
Abstract This practical guide provides a detailed introduction to quantum logic gates and unitary operators as implemented on the IBM Q platform. It focuses on the fundamental gate structures used in quantum programming, particularly within the Composer interface, and provides screenshots and detailed descriptions of each operator’s functionality. The guide emphasizes the operational role of gates in controlling qubit states and constructing quantum circuits. To enhance understanding, the behavior of gates is visualized on the Bloch sphere, demonstrating how single-qubit operations rotate qubit states around the XXX, YYY, and ZZZ axes, as well as how phase shifts and amplitude adjustments modify the qubit. These operations are essential for measurement, state preparation, and precise manipulation of quantum systems. The relevance of this study is underscored by the rapid development of quantum technologies and the increasing accessibility of quantum computing platforms like IBM Q. A thorough understanding of quantum gates and their implementations is critical for advancing quantum algorithm design and for training specialists capable of deploying quantum computational solutions in fields ranging from cryptography to complex physical system simulations. This guide provides both theoretical insights and practical exercises, bridging the gap between abstract quantum mechanics and applied quantum programming, thereby equipping readers with foundational skills for effective circuit construction and quantum computation.
Quantum Computing (QC) has evolved from a few custom quantum computers, which were only accessible to their creators, to an array of commercial quantum computers that can be accessed on the cloud by anyone. Accessing these cloud quantum computers requires a complex chain of tools that facilitate connecting, programming, simulating algorithms, estimating resources, submitting quantum computing jobs, retrieving results, and more. Some steps in the chain are hardware dependent and subject to change as both hardware and software tools, such as available gate sets and optimizing compilers, evolve. Understanding the trade-offs inherent in this process is essential for evaluating the power and utility of quantum computers. ARLIS has been systematically investigating these environments to understand these complexities. The work presented here is a detailed summary of three months of using such quantum programming environments. We show metadata obtained from these environments, including the connection metrics to the different services, the execution of algorithms, the testing of the effects of varying the number of qubits, comparisons to simulations, execution times, and cost. Our objective is to provide concrete data and insights for those who are exploring the potential of quantum computing. It is not our objective to present any new algorithms or optimize performance on any particular machine or cloud platform; rather, this work is focused on providing a consistent view of a single algorithm executed using out-of-the-box settings and tools across machines, cloud platforms, and time. We present insights only available from these carefully curated data.
Quantum computers form a technological cluster with huge growth in the last few years. Although this technology is of still very limited size: perhaps the reason it is not seen as a technology which may be mass produced or of public use in the near future: it is one of the most promising developments with a potential to change the world. The IBM Quantum Experience Platform makes it possible for every person around the world, without limitation as to geographical location, to get acquainted with the technology of quantum computing. It is a resource for both researchers and enthusiasts entering the quantum world. With the development of the platform, IBM has proven that the programming and writing code executable on a quantum computer can be easy and accessible (it is a cloud platform) even to people lacking any deep knowledge of quantum mechanics. The construction of the Controlled Square Root of Z gate is achieved using only existing predefined gates in the Composer tool. This newly created gate could be used for further work on quantum algorithms and opens a new feasible way to write quantum code.
Quantum computing is a new emerging technology which is capable of performing specific types of calculations more efficiently than classical computers. Yet quantum computers have their own limitations in terms of noise, decoherence, and qubits numbers, so the current research focus on hybrid quantum-classical computation where classical computers work in conjunction with quantum devices to perform computation. This chapter discusses the architecture of quantum-ready clouds and describes how to effectively run a hybrid quantum-classical workflows over cloud environment. It introduces the middleware and Application Programming Interface (API) in order to support communication between cloud environment and quantum hardware. Furthermore, the chapter shows how the orchestration mechanism to coordinate the classical cloud resources and quantum processors, and presents a simple workflow model for data routing, processing, and analysis utilizing classical/cloud and quantum hardware.