Training Needs in Quantum Computing

Stefan Seegerer, Mikio Nakahara

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.

Maria Schuld, Francesco Petruccione

Chilakala Lokanath Reddy

This study introduces a groundbreaking hybrid framework integrating quantum computing (QC) into deep learning for efficient fault diagnosis in electrical power systems. Leveraging the strengths of conditional restricted Boltzmann machines and deep networks, our approach addresses computational challenges through novel QC-based training methodologies. The research unfolds in seven phases, from quantum computing infrastructure to statistical analysis, showcasing the implementation of a cutting-edge quantum processor, TensorFlow-based deep learning, and Quantum-Deep Learning Interface. Results demonstrate a quantum advantage in accuracy, efficiency, and training time reduction. Challenges and opportunities highlight the need for technological maturity, algorithmic complexity solutions, and seamless quantum-classical system interfacing. Future scope encompasses refining algorithms, broadening use cases, and collaborating for responsible deployment. This work marks a transformative step towards computational intelligence, contributing to the synergy of quantum computing and deep learning.

Lewis Westfall, Avery M. Leider

Franziska Greinert, Malte S. Ubben, Ismet N. Dogan +2 more

Abstract The transition of second-generation quantum technologies from a research topic to a topic of industrial relevance has led to a growing number of quantum companies and businesses that are exploring quantum technologies. Examples would include a start-up building a quantum key distribution device, a large company working on integrating a quantum sensing core into a product, or a company providing quantum computing consultancy. They all face different challenges and needs in terms of building their quantum workforce and training in quantum concepts, technologies and how to derive value from them. With the study documented in this paper, we aim to identify these needs and provide a picture of the industry’s requirements in terms of workforce development and (external) training and materials. We discuss, for example, the shortage of engineers and jobs relevant to the quantum industry, the challenge of getting people interested in quantum, and the need for training at different levels and in different formats – from awareness raising and self-learning materials to university courses in quantum systems engineering. The findings are based on 34 semi-structured interviews with industry representatives and a follow-up questionnaire to validate some of the issues raised in the interviews. These results have influenced activities in EU projects, including an update of the European Competence Framework for Quantum Technologies.

Madhusudan Singh Irish Singh, Bharat S. Rawal