The convergence of quantum technologies and high-performance computing offers unique opportunities for research and algorithm development, demanding a skilled workforce to harness the quantum systems' potential.In this lightning talk, we address the growing need to train experts in quantum computing and explore the challenges in training these individuals in quantum computing, including the abstract nature of quantum theory, or the focus on specific frameworks.To overcome these obstacles, we propose selfguided learning resources that offer interactive learning experiences and practical framework-independent experimentation for different target audiences.
The convergence of quantum technologies and high-performance computing offers unique opportunities for research and algorithm development, demanding a skilled workforce to harness the quantum systems' potential.In this lightning talk, we address the growing need to train experts in quantum computing and explore the challenges in training these individuals in quantum computing, including the abstract nature of quantum theory, or the focus on specific frameworks.To overcome these obstacles, we propose selfguided learning resources that offer interactive learning experiences and practical framework-independent experimentation for different target audiences.
Unlock the future of quantum technology with this comprehensive guide that bridges the gap between complex quantum theory and real-world applications, giving you the practical edge needed to solve the next generation’s toughest scientific and industrial problems. At its core, quantum computing leverages the principles of quantum mechanics to process information in fundamentally different ways from classical computing. As physical limits constrain the continued scaling of classical technologies, quantum computing offers a fundamentally new pathway toward solving complex problems in science, engineering, and industry. This book is a comprehensive guide designed to bridge the gap between theoretical principles and real-world quantum computing applications. It explores quantum information theory, a cornerstone of quantum computing, to explain how information is encoded, manipulated, and measured in a quantum system. Topics such as quantum gates, circuits, and the Bloch sphere representation are covered in detail, offering readers a solid grounding in the mechanics of quantum operations. With a focus on practical implementation, this book is tailored for students, researchers, and professionals seeking to delve into the transformative world of quantum computing, where the boundaries of classical computation are redefined. Readers will find the book: Uses step-by-step guides and hands-on tutorials for building quantum circuits and running algorithms; Explores core algorithms through detailed walkthroughs of quantum algorithms, including Shor’s, Grover’s, and Quantum Fourier Transform; Provides hands-on learning through exercises, coding challenges, and projects to reinforce practical skills. Audience Academics, researchers, quantum software developers and hardware engineers, data scientists, AI specialists, and security experts focused on the study and implementation of quantum systems and processors.
Quantum computing is an emerging technology with a burgeoning industry and growing workforce needs. The demand for computer scientists with quantum computing knowledge is increasing, as their skills are needed to make quantum computing a scalable and useful resource. However, few computer scientists are formally educated in quantum computing, with most education occurring in physics curricula. Although some open source learning resources and software tools for quantum computing are available, they employ a quantum mechanical, hardware-driven framing that poses accessibility challenges for computing-focused learners. Educational games have seen some success in quantum computing outreach initiatives, particularly in building intuition for quantum mechanical concepts, but rarely relate to computing practices. This submission outlines a doctoral research programme that seeks to develop computing-centred interactions with quantum computing systems, and to explore how play can be leveraged in these interactions as a means of building quantum intuitions in a computing context.
As we enter the post-Moore era, we experience the rise of various non-von-Neumann-architectures to address the increasing computational demand for modern applications, with quantum computing being among the most prominent and promising technologies. However, this development creates a gap in current computer science curricula since most quantum computing lectures are strongly physics-oriented and have little intersection with the remaining curriculum of computer science. This fact makes designing an appealing course very difficult, in particular for non-physicists. Furthermore, in the academic community, there is consensus that quantum computers are going to be used only for specific computational tasks (e.g., in computational science), where hybrid systems - combined classical and quantum computers - facilitate the execution of an application on both quantum and classical computing resources. A hybrid system thus executes only certain suitable parts of an application on the quantum machine, while other parts are executed on the classical components of the system. To fully exploit the capabilities of hybrid systems and to meet future requirements in this emerging field, we need to prepare a new generation of computer scientists with skills in both distributed computing and quantum computing. To bridge this existing gap in standard computer science curricula, we designed a new lecture and exercise series on Hybrid Quantum-Classical Systems, where students learn how to decompose applications and implement computational tasks on a hybrid quantum-classical computational continuum. While learning the inherent concepts underlying quantum systems, students are obligated to apply techniques and methods they are already familiar with, making the entrance to the field of quantum computing comprehensive yet appealing and accessible to students of computer science.
Quantum computing (QC) promises to be a transformative technology with impact on various application domains, such as optimization, cryptography, and material science. However, the technology has a sharp learning curve, and practical evaluation and characterization of quantum systems remains complex and challenging, particularly for students and newcomers from computer science to the field of quantum computing. To address this educational gap, we introduce Q-BEAST, a practical course designed to provide structured training in the experimental analysis of quantum computing systems. Q-BEAST offers a curriculum that combines foundational concepts in quantum computing with practical methodologies and use cases for benchmarking and performance evaluation on actual quantum systems. Through theoretical instruction and handson experimentation, students gain experience in assessing the advantages and limitations of real quantum technologies. With that, Q-BEAST supports the education of a future generation of quantum computing users and developers. Furthermore, it also explicitly promotes a deeper integration of High Performance Computing (HPC) and QC in research and education.
Quantum technologies are increasingly recognized as a strategic priority for economic competitiveness, national security, and technological innovation in the United States. As quantum systems transition from research prototypes to deployable technologies, attention has shifted toward the preparedness of the quantum workforce, particularly the alignment between higher education and industry skill needs. While prior research has examined individual aspects of quantum education or workforce demand, few studies integrate systematic curriculum analysis with documented industry expectations. This study addresses that gap by analyzing primary U.S. masters programs in quantum science and technology, focusing on curriculum structure and skill development. Using a structured coding framework, course offerings were mapped across six quantum-relevant skill categories and aggregated to produce program-level skill profiles. These profiles were then compared with industry-identified competencies reported in recent workforce studies. The findings reveal strong emphasis on quantum theory across programs, alongside substantial variability in technical skills, applied learning opportunities, and professional development components. The results highlight areas of alignment as well as persistent gaps related to workforce readiness, cross-disciplinary integration, and emerging technological demands. This study provides a scalable framework for evaluating quantum education programs and offers evidence-based insights for curriculum design, workforce policy, and the continued development of the U.S. quantum ecosystem.
The ongoing accelerated development and exploration of Quantum Computing (QC) - systems, software, algorithms and applications - has generated a huge amount of interest and need among a wide range of organisations and user communities to better understand the technology paradigm, its maturity, limitations and opportunities, and positioning alongside classical high-performance computing (HPC) methods and tools. This interest and need to learn about QC has been accentuated by the rapidness and breadth of developments in QC that is being disseminated in both mainstream and specialist scien-tific/technical media as well as the accessibility to early quantum computing systems and tools. It has become a challenge for the (potential) user community to sift through the material catering to developing bottom-up fundamental scientific/mathematical skills as well as top-down exploitation oriented knowledge. As the National and one among the European Competence Centres in HPC, the Irish Centre for High-End Computing (ICHEC) has worked with an international advisory board composed of quantum computing technology developers, the user community and the Irish State Agency's network that is responsible for national enterprise skills development in ICT to create and deliver a blended course which is customisable, modular and stackable, thereby offering different learning path-ways to professional learners from the academic, enterprise and public sector communities with inhomogeneous backgrounds. Particular emphasis is laid on the stakes of engaging learners and organisations with different knowledge basis, skills and learning objectives, as well as making the content suitably-positioned and approachable to all (e.g. varied levels of mathematical knowledge required for basic understanding of quantum computing versus developing quantum algorithms). In this paper, we discuss the Quantum Programming Certifi-cation Course (QPCC) by summarising the 4-year design process with the advisory board, drawing from ICHEC's experience in national and European HPC and QC R&D projects as well as preparation of strategies and joint white papers, and methods to address gaps between mainstream academic programmes in quantum technologies and existing training courses (such as MOOCs, tutorials, workshops). We discuss the approaches in QPCC to target professional learners from inhomogeneous backgrounds, tools and pedagogical approaches in preparing and delivering the training material, opportunities and challenges in positioning QPCC within the academic framework, and sum-marise open opportunities for developing collaborative solutions.