IEEE International Conference on Quantum Computing and Engineering (QCE)
QPCC: A Quantum Programming Course for Inhomogeneous Cohorts of Professional Learners
Emil Dimitrov, Conor Dunne, Venkatesh Kannan, Karthik Krishnakumar, Pablo Lauret Martínez de Rituerto, Pablo Suárez Vieites, Rajarshi Tiwari, Richard A. Wolf
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.
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.
Investments in quantum technologies, which are based on the effects of quantum mechanics, have escalated in recent years, with big players such as IBM, Google, and Microsoft engaging in the race for quantum supremacy. Some potential benefits of this cutting-edge technology include developing new drugs and materials through accurate molecule simulation, establishing more secure and reliable communication channels, and finding faster solutions for complex optimization problems. As quantum technologies evolve, however, the demand for new software, interfaces, and end-to-end systems to properly program and explore the advantages of quantum mechanics becomes paramount. This requires engineers, especially software engineers, and computer scientists, to have multidisciplinary knowledge and skills. Unfortunately, introductory quantum computing and technologies courses are mostly available in physics, and most engineering and computer science courses do not have modules on quantum physics, leading to a talent gap in the current job market. Therefore, this paper proposes a short teaching plan for introducing quantum computing to students with a more technology-based background, such as computer science and engineering students. This plan uses active learning methodologies, such as Challege-Based Teaching, to better engage these students and contextualize the many applications of this new technology. The initial teaching plan consists of a 3-hour seminar introducing the main quantum mechanics concepts and the technology applications, a 3-hour introduction to the math fundamentals and quantum logic gates, and a 3-hour handson workshop using the IBM Qiskit platform. Two versions of this plan were executed in two different moments: (1) a one-day event open to undergraduate students from different institutions and backgrounds, and (2) a 3-day internal training course for computer science and information technology management undergraduate students from our higher education institution. Data was collected during both events through online forms and interviews to measure the learning outcomes of the produced material and better understand the public interest in the field. The results identified key elements for better teaching quantum computing for computer scientists and engineers, providing guidelines for developing a more extensive and term-long teaching plan for undergraduate technology courses.
With quantum computing (QC) maturing, high-performance computing (HPC) centers are already preparing to host early-phase production versions of such systems. Unlike their experimental predecessors in physics laboratories, with a very small and dedicated user community, this next generation of systems needs to serve a wider user community and must work in concert with existing HPC systems and software stacks. This article describes our vision for an integrated ecosystem that combines existing HPC and evolving quantum software stacks into a single system to enable a common and continuous user experience. This integration comes with several major challenges as quantum systems pose significantly different requirements including increased need for compilation at run time, long optimization times, statistical evaluations of results, and the need to work with few centralized resources. To overcome these challenges, new scheduling approaches on the HPC side and new programming approaches on the QC side are required.
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) introduces a novel mode of computation with the possibility of greater computational power that remains to be exploitedpresenting exciting opportunities for high-performance computing (HPC) applications. However, recent advancements in the field have made clear that QC does not supplant conventional HPC, but can rather be incorporated into current heterogeneous HPC infrastructures as an additional accelerator, thereby enabling the optimal utilization of both paradigms. The desire for such integration significantly affects the development of software for quantum computers, which in turn influences the necessary software infrastructure. To date, previous review articles have investigated various quantum programming tools (QPTs) (such as languages, libraries, frameworks) in their ability to program, compile, and execute quantum circuits. However, the integration effort with classical HPC frameworks or systems has not been addressed. This study aims to characterize existing QPTs from an HPC perspective, investigating if existing QPTs have the potential to be efficiently integrated with classical computing models and determining where work is still required. This work structures a set of criteria into an analysis blueprint that enables HPC scientists to assess whether a QPT is suitable for a high-performance computing quantum computing (HPCQC) environment.
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.
With recent progress in the development of large-scale, general-purpose, fault-tolerant quantum computing (QC), significant effort is being made in the cybersecurity community to create viable long-term solutions mitigating the threat of quantum computers breaking classical public-key based security schemes. The current post-quantum cryptography (PQC) standardization process led by the National Institute of Standards and Technology (NIST) has standardized cryptographic protocols designed to be resistant to QC. PQC education is still in its early stages, with limited curricular materials available for broad distribution in an appropriate academic format. Another challenge is developing curricula for students with different levels of computing and cryptographic preparedness. The modular approach to curriculum development has been proven to be an effective method for introducing new concepts. The authors of this work have several years of experience teaching cryptography and PQC courses at two academic institutions. We introduce two types of PQC instruction modules at varying levels of complexity: Awareness and Proficiency. The suggested contents, learning outcomes, and duration for each module are presented.