Quantum computing has emerged recently as a new computational paradigm. It considers quantum bits (qubits) instead of classical bits. However, quantum algorithms are often very difficult to understand. In this paper, we propose a tool for quantum software visualization. It presents visually the state of multiple-qubits and its evolution at runtime during the execution of a quantum program. This tool allows a unique representation of a quantum state, contrary to the usual vector notation. We show how the problem of visualizing a quantum state can be reduced to a set visualization problem, and our tool uses rainbow boxes to visualize the resulting sets. We also present the application of the proposed tool to quantum teleportation, an algorithm of high importance in cryptography. Finally, we discuss the limit of this approach and its perspectives, in particular for teaching quantum computing.
Quantum computing has emerged recently as a new computational paradigm. It considers quantum bits (qubits) instead of classical bits. However, quantum algorithms are often very difficult to understand. In this paper, we propose a tool for quantum software visualization. It presents visually the state of multiple-qubits and its evolution at runtime during the execution of a quantum program. This tool allows a unique representation of a quantum state, contrary to the usual vector notation. We show how the problem of visualizing a quantum state can be reduced to a set visualization problem, and our tool uses rainbow boxes to visualize the resulting sets. We also present the application of the proposed tool to quantum teleportation, an algorithm of high importance in cryptography. Finally, we discuss the limit of this approach and its perspectives, in particular for teaching quantum computing.
The focus of this Visualization Viewpoints article is to provide some background on quantum computing (QC), to explore ideas related to how visualization helps in understanding QC, and examine how QC might be useful for visualization with the growth and maturation of both technologies in the future. In a quickly evolving technology landscape, QC is emerging as a promising pathway to overcome the growth limits in classical computing. In some cases, QC platforms offer the potential to vastly outperform the familiar classical computer by solving problems more quickly or that may be intractable on any known classical platform. As further performance gains for classical computing platforms are limited by diminishing Moore's Law scaling, QC platforms might be viewed as a potential successor to the current field of exascale-class platforms. While present-day QC hardware platforms are still limited in scale, the field of quantum computing is robust and rapidly advancing in terms of hardware capabilities, software environments for developing quantum algorithms, and educational programs for training the next generation of scientists and engineers. After a brief introduction to QC concepts, the focus of this article is to explore the interplay between the fields of visualization and QC. First, visualization has played a role in QC by providing the means to show representations of the quantum state of single-qubits in superposition states and multiple-qubits in entangled states. Second, there are a number of ways in which the field of visual data exploration and analysis may potentially benefit from this disruptive new technology though there are challenges going forward.
Abstract Quantum computing utilizes the concepts of quantum mechanics, including superposition and entanglement, to execute calculations that are impractical for traditional computers. Central to this approach is the qubit, a quantum equivalent of the traditional bit, capable of being in a superposition of states. Nonetheless, the conceptual essence of quantum states renders them hard to visualize and comprehend, particularly for students and professionals who are unfamiliar with the domain. To tackle this issue, we created an interactive qubit visualization tool using Streamlit, enabling real-time exploration of qubit behavior under quantum operations.The app enables users to control qubit states directly by modifying the real and imaginary components of probability amplitudes, guaranteeing the normalization of the state vector. It also incorporates a set of essential quantum gates, including Hadamard, Pauli-X, Pauli-Y, and Pauli-Z, as well as continuous rotation gates (Rx, Ry, Rz). In contrast to distinct button-driven functions, the rotation gates are implemented dynamically via angle sliders, enabling users to witness seamless, real-time updates to the qubit state. This provides an intuitive understanding of qubit evolution as it revolves around the Bloch sphere axes.The tool displays the outcomes in both numerical and graphical formats. Users are able to observe the quantum state vector, as well as the probabilities of obtaining |0⟩ and |1⟩, and visual depictions through probability bar charts and Bloch sphere visualizations. By providing a live, interactive setting, this platform connects the divide between mathematical theory and conceptual grasp of quantum mechanics. It functions as both a learning tool for students and a prototyping support for researchers, rendering quantum computation more approachable and captivating.
Quantum algorithms which are performed on quantum computers are hardly developed, because the principle of quantum computers are totally different from classical computers. We would like to discuss the way of visualization to assist understanding quantum algorithms. As the first step, we have developed visualization system of the Bloch sphere, which is the popular way to show the status of one quantum bit. In the system, we can see the Bloch sphere as 3DCG and interact with it. Next, we discuss the problems of visualizing multiple quantum bits and quantum algorithms.
In the last year, quantum computing has rapidly transitioned from a purely theoretical field into applied engineering, where multiple algorithms can approach combinatorial optimization problems, machine learning, and cryptography in novel ways, often achieving speedup compared to classical solutions. In this context, there is an increasing need for educational tools that connect mathematical principles from quantum information theory with practical experimentation. Yet, most existing educational resources remain either highly theoretical or provide fragmented code examples, with limited analysis and applications to real-world use cases. As a result, students’ experiences appear restricted, with non-interactive tools for learning. This work presents a comprehensive framework for teaching quantum computing through interactive resources, developed via MATLAB Live Scripts. By combining theory, executable code, and visualization tools within a single environment, this framework enhances learners’ ability to see and reason about quantum algorithms step by step. Following the principles of Project-Based Learning in STEM education, we present a diverse collection of quantum resources, including algorithms for optimization, communication, and error correction. Each project operates as a self-contained learning unit, offering modularity, white-box implementations, and tools for visualization and analysis. Beyond its educational impact, this framework also employs and extends the MATLAB Support Package for Quantum Computing, offering an open-source, reproducible environment suitable for courses and independent study.
Quantum computing (QC) has experienced rapid growth in recent years with the advent of robust programming environments, readily accessible software simulators and cloud-based QC hardware platforms, and growing interest in learning how to design useful methods that leverage this emerging technology for practical applications. From the perspective of the field of visualization, this article examines research challenges and opportunities along the path from initial feasibility to practical use of QC platforms applied to meaningful problems.
The rapid progress quantum devices have made in recent years has led to the need for systems that bridge the gap between quantum algorithms and quantum hardware. To this purpose different full-stack quantum programming platforms have been developed, providing high level languages for expressing quantum algorithms and providing compilers for making those quantum algorithms executable on a given quantum device. OpenQL is one such a platform, with support for compiling a variety of quantum program inputs into a quantum circuit, ready to be executed on the targeted quantum hardware. OpenQL is an evolving tool in which new features are constantly added to improve its performance and extend its functionality. In order to enhance OpenQL and provide some extra support to the researchers using OpenQL for their experiments, a visualization tool with three main functionalities has been developed in this thesis project. First, a circuit visualizer, with support for both visualizing the circuit output of the OpenQL compiler as an abstract gate representation and a pulse representation, which has been made specifically for quantum hardware running on superconducting qubits. Secondly, a mapping graph visualizer, which allows displaying the logical to physical qubit mapping per program cycle. And lastly a qubit interaction graph generator, which shows the required interactions between qubits of a given quantum algorithm.