As quantum computing theory is attracting attention from researchers nowadays, visualizing the quantum computing process is necessary for fundamental quantum computing education and research. Especially, connecting traditional computational theory with advanced quantum computing concepts is an extremely important step in learning and understanding quantum computing. In this paper, we propose a practical interactive interface for simulating Quantum Turing Machine (QTM) in Augmented Reality (AR) that combines the traditional Turing machine computational model with the quantum computing simulation. Through such an interface, users can use a C-like script to represent a QTM and simulate such QTM in an immersive augmented reality platform through the Vuforia AR engine. After validating our proposed QTM AR simulator through a series of experiments, we show the great potential to apply our QTM AR simulator to quantum computing education through an interactive visualization interface in augmented reality.
As quantum computing theory is attracting attention from researchers nowadays, visualizing the quantum computing process is necessary for fundamental quantum computing education and research. Especially, connecting traditional computational theory with advanced quantum computing concepts is an extremely important step in learning and understanding quantum computing. In this paper, we propose a practical interactive interface for simulating Quantum Turing Machine (QTM) in Augmented Reality (AR) that combines the traditional Turing machine computational model with the quantum computing simulation. Through such an interface, users can use a C-like script to represent a QTM and simulate such QTM in an immersive augmented reality platform through the Vuforia AR engine. After validating our proposed QTM AR simulator through a series of experiments, we show the great potential to apply our QTM AR simulator to quantum computing education through an interactive visualization interface in augmented reality.
Quantum computing (QC) is an intrinsically complex yet exciting discipline with increasing practical relevance. A deep understanding of QC requires the integration of knowledge across numerous technical fields, such as physics, computing and mathematics. This work aims to investigate how immersive Virtual Reality (VR) compares to a desktop environment (‘web-applet’) as an educational tool to help teach individuals QC fundamentals. We developed two interactive learning tutorials, one utilising the ‘Bloch sphere’ visualisation to represent a single-qubit system, and the other exploring multi-qubit systems through the lens of ‘quantum entanglement’. We evaluate the effectiveness of each medium to teach QC fundamentals in a user study with 24 participants. We find that the Bloch sphere visualisation was well-suited to VR over a desktop environment. Our results also indicate that mathematics literacy is an important factor in facilitating greater learning with this effect being notably more pronounced when using VR. However, VR did not significantly improve learning in a multi-qubit context. Our work provides valuable insights which contribute to the emerging field of Quantum HCI (QHCI) and VR for education.
Quantum computing is a promising approach of computation that is based on equations from Quantum Mechanics and nanotechnology. Understanding and simulating quantum operations on a classical computer has different approaches and is modeled in different ways. However, the most repute ways are Quantum Turing Machine, Network Model or circuit model of connected gates and Quantum Programming Language. Many simulators do exist that varies in many features such as implementation languages, target platforms, paradigms, visuality, and applied quantum algorithms. There was a developmental trade-off between the simplicity and the functionality of the simulator. The goals and research activities are outlined as follows: First, surveying the quantum computing world, its characteristics, issues, problems, and challenges. Second, surveying the existing quantum simulators, illustrating representative simulators of major approaches, their features, and functionalities. Third, introducing a framework to provide the power of quantum computing , while insisting the simplicity and high usability. Finally, providing a case study for a new quantum algorithm based on the introduced framework.
The emergence of digital and cognitive Web 3.0 demands a move towards immersive applications that drive innovation across verticals like Industry 5.0, gaming, healthcare, and allied sectors. These sectors are led by key developments in Augmented Reality (AR) and Virtual Reality (VR), which offer end users a nuanced, haptic, and immersive Quality-of-Interaction (QoI). To manage end-user QoI, AR/VR applications rely on real-time, high-fidelity simulations, AI-driven control, and Next-Generation Wireless Communication Networks (NWGNs). Future applications face pressing needs for high computational capacity, resource optimization, parallel processing of vast amounts of data, and unbreakable security beyond classical cryptographic primitives. Integrating Quantum Computing (QC) into the AR/VR space offers transformative potential to overcome these challenges. Recent surveys have explored the potentials of AR/VR and QC in isolation, but the convergence of these fields remains largely unexplored. This survey aims to bridge this gap by exploring the potential of decoding QC into the AR/VR space. We systematically review existing surveys and present background discussions on QC, quantum AI, quantum resource optimization, and the role of NWGNs in QC-assisted AR/VR. Furthermore, we present a reference architecture for QC-assisted AR/VR, supported by a detailed solution taxonomy. Open issues and future research directions are outlined, and we discuss a novel case study of a QC-enabled Industrial Metaverse integrated with AR/VR. This survey serves as a pivotal resource for researchers and industry leaders aiming to pioneer the next generation of AR/VR experiences powered by QC systems, thereby shaping the future of immersive technologies.
Modern computer science emerged when the eminent British mathematician Alan Turing invented the concept of Turing machine (TM) in 1936. Though very simple and primitive, TM serves as the universal model for all known physical computation devices. The principles of quantum mechanics, another revolutionary scientific discovery of the 20 th century, had never been incorporated in the theory of computation until the early 1980s. P. Benioff first coined the concept of quantum Turing machine (QTM). Motivated by the problem that classical computers cannot simulate quantum systems efficiently, R. Feynman posed the quantum computer as the solution. The field of quantum computation was born.
Quantum computing introduces abstract concepts such as superposition, entanglement, and quantum circuits and algorithms, which many learners find difficult to grasp without strong mathematics or physics backgrounds. This paper proposes the use of virtual reality (VR) to support the teaching of introductory quantum computing. By situating learners in an immersive environment, VR allows students to explore and manipulate visual representations of the qubit and quantum gates, and observe state changes in real-time. The paper outlines how VR settings can foster deeper understanding through sandbox interactivity with visualized abstractions of quantum computing concepts.
This paper explores the potential of quantum entanglement to revolutionize the design and analysis of complex geometric Turing machines. Traditional Turing machines rely heavily on explicit algorithm design, while the inherent properties of quantum entanglement offer a fundamentally different approach to simulating complex geometric patterns and behaviors. We propose a novel architecture leveraging entanglement to model geometric intuition more accurately, ultimately enabling the precise characterization of geometric Turing machine behavior. The core mechanism centers around encoding geometric information within entangled states, allowing for dynamic and nuanced geometric simulations. This work introduces a new framework for geometric Turing machine design, demonstrating the potential for significantly enhanced computational power and a deeper understanding of geometric computation.