Summary This talk explores the potential of quantum computing and the current market status. It focuses on PASQAL’s technology using neutral atoms for scalable quantum computing. The main categories of algorithms designed for neutral atom quantum computers and their real-world applications are summarized. The energy industry has numerous quantum applications, including energy resource management, grid optimization, complex system optimization, simulation, and battery design. Three disruptive examples are highlighted. Integration of quantum hardware with HPC centers is crucial. The talk addresses challenges, the expected maturity of quantum computing, and the integration challenges with HPC centers. It prompts us to consider the future of HPC centers in the era of quantum computing.
Summary This talk explores the potential of quantum computing and the current market status. It focuses on PASQAL’s technology using neutral atoms for scalable quantum computing. The main categories of algorithms designed for neutral atom quantum computers and their real-world applications are summarized. The energy industry has numerous quantum applications, including energy resource management, grid optimization, complex system optimization, simulation, and battery design. Three disruptive examples are highlighted. Integration of quantum hardware with HPC centers is crucial. The talk addresses challenges, the expected maturity of quantum computing, and the integration challenges with HPC centers. It prompts us to consider the future of HPC centers in the era of quantum computing.
Quantum computing has evolved from a largely theoretical discipline into a field of growing interest for commercial and industrial applications. Recent advances in quantum hardware, algorithms, and cloud-based access have enabled early experimentation outside academic environments, raising questions about its potential impact on real-world decision-making and operational problems. This paper provides an overview of the current state of quantum computing with a focus on its emerging relevance in commercial contexts. It examines the categories of problems that have attracted attention from industry, particularly those involving high combinatorial complexity such as optimization, scheduling, logistics, and resource allocation. The analysis also reviews the global landscape of companies and initiatives engaged in quantum computing, highlighting different technological approaches, maturity levels, and regional characteristics. In parallel, the paper discusses the principal challenges and limitations that constrain widespread adoption, including hardware immaturity, algorithmic readiness, cost factors, and organizational requirements. By considering both opportunities and risks, this study aims to present a balanced and realistic perspective on the role quantum computing may play in business environments. The objective is to clarify the current position of quantum computing within the broader technological landscape and to support informed interpretation of its potential, limitations, and future trajectory in commercial applications.
The manipulation of neutral atoms by light is at the heart of countless scientific discoveries in the field of quantum physics in the last three decades. The level of control that has been achieved at the single particle level within arrays of optical traps, while preserving the fundamental properties of quantum matter (coherence, entanglement, superposition), makes these technologies prime candidates to implement disruptive computation paradigms. In this paper, we review the main characteristics of these devices from atoms / qubits to application interfaces, and propose a classification of a wide variety of tasks that can already be addressed in a computationally efficient manner in the Noisy Intermediate Scale Quantum\cite{Preskill_NISQ} era we are in. We illustrate how applications ranging from optimization challenges to simulation of quantum systems can be explored either at the digital level (programming gate-based circuits) or at the analog level (programming Hamiltonian sequences). We give evidence of the intrinsic scalability of neutral atom quantum processors in the 100-1,000 qubits range and introduce prospects for universal fault tolerant quantum computing and applications beyond quantum computing.
The objective of this work is to study the application of quantum computing methods for the development of Machine Learning algorithms and their integration into neutral atom computers. Quantum computing is an emerging technology that is gaining significant relevance in both industrial and academic research and development sectors. This work will provide a historical introduction to the emergence of quantum computing, analyzing the motivation for its development and discussing its current state. An introduction to the fundamentals of quantum computing will also be provided, starting from the very basics of quantum mechanics. Following this, the operation of Pasqal’s neutral atom quantum computer will be explained. Finally, the work will demonstrate how to use the quantum computing tools offered by Pasqal’s computer to implement a purely quantum algorithm (Bernstein-Vazirani) and to solve a clustering problem.
While quantum computing (QC) is considered as a paradigm shift in our basic understanding of physical computation, effective implementation of QC in energy applications also depends on progress and development in the dimensions of both QC hardware and algorithms. To fully address the status and future challenges of QC applied within the energy sector, in this presentation, we firstly summarize recent advancements on the applications of QC to energy infrastructure and materials, complex energy system processes, advanced manufacturing, and energy system security. Then, we will demonstrate the results of QC performed both on a simulator and a quantum device targeting on energy-related applications.
Abstract Quantum computing and quantum-inspired technologies are set to significantly impact the energy sector, enhancing optimisation and simulation processes to enable studies that cannot be performed today. At Siemens Energy, our studies have shown potential to address complex challenges in grid management, power distribution, and scarce resource allocation. One of the important examples of where quantum computing holds promise is in the field of optimisation, where physical systems are used to find low energy (i.e. high quality) states (i.e. solutions) to systems that could support many configurations (i.e. combinatorial optimisation problems). The integration of quantum computing into the energy industry promises to deliver improvements in several fields, including cost reduction, increased system reliability, and importantly to be able to make better use of existing resources. Currently in the early stages of research and development, Siemens Energy’s work is showing that combinatorial optimisation problems are all around us in the energy sector. Practical quantum-inspired and hybrid approaches can be used today to solve some of these problems and bring benefits in areas which would have previously not employed optimisation traditionally. This gives us the opportunity and tools to attempt new and innovative approaches to decarbonisation and attempt previously insoluble challenges in the industry.
This chapter explores the transformative potential of quantum computing across various industries, with a focus on its applications in energy and financial services. Quantum computing, leveraging principles of quantum physics, promises to revolutionize problem-solving and optimization processes that are beyond the capabilities of classical computing. In the energy sector, quantum machine learning enhances supply and demand forecasting, while Quantum Annealing optimizes energy production schedules through the Unit Commitment Problem. These quantum approaches address the complexities of volatile energy markets and the integration of renewable energy sources, providing innovative solutions for cost-effective and reliable energy management. In financial services, quantum computing offers advancements in portfolio optimization, risk analysis, and fraud detection, enabling faster and more efficient data processing. The chapter also highlights the necessity for financial institutions to develop post-Quantum cryptography strategies to secure cryptographic systems against emerging quantum threats. Despite its potential, the widespread adoption of quantum computing faces significant challenges, including the high cost of quantum machines, integration issues with classical systems, and the nascent stage of the technology. Nonetheless, preparing business structures for the forthcoming quantum era and leveraging current capabilities are essential steps for organizations. The chapter concludes with an outlook on the future applications of quantum computing in sectors such as healthcare, pharmaceuticals, and defense, underscoring its role as a catalyst for a sustainable and technologically advanced future.