Full-Stack Quantum Software in Practice: Ecosystem, Stakeholders and Challenges

• URL: http://arxiv.org/abs/2307.16345v1
• Date: Sun, 30 Jul 2023 23:44:22 GMT
• Title: Full-Stack Quantum Software in Practice: Ecosystem, Stakeholders and Challenges
• Authors: Vlad Stirbu, Majid Haghparast, Muhammad Waseem, Niraj Dayama, Tommi Mikkonen
• Abstract summary: The emergence of quantum computing has introduced a revolutionary paradigm capable of transforming numerous scientific and industrial sectors. However, realizing the practical utilization of quantum software in real-world applications presents significant challenges. This paper explores tangible approaches to establishing quantum computing software development process.
• Score: 5.242305867893238
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The emergence of quantum computing has introduced a revolutionary paradigm capable of transforming numerous scientific and industrial sectors. Nevertheless, realizing the practical utilization of quantum software in real-world applications presents significant challenges. Factors such as variations in hardware implementations, the intricacy of quantum algorithms, the integration of quantum and traditional software, and the absence of standardized software and communication interfaces hinder the development of a skilled workforce in this domain. This paper explores tangible approaches to establishing quantum computing software development process and addresses the concerns of various stakeholders. By addressing these challenges, we aim to pave the way for the effective utilization of quantum computing in diverse fields.

Related papers

• A Review of Quantum Scientific Computing Algorithms for Engineering Problems [0.0]
  Quantum computing, leveraging quantum phenomena like superposition and entanglement, is emerging as a transformative force in computing technology. This paper systematically explores the foundational concepts of quantum mechanics and their implications for computational advancements.
  arXiv  Detail & Related papers  (2024-08-25T21:40:22Z)
• The curse of random quantum data [62.24825255497622]
  We quantify the performances of quantum machine learning in the landscape of quantum data. We find that the training efficiency and generalization capabilities in quantum machine learning will be exponentially suppressed with the increase in qubits. Our findings apply to both the quantum kernel method and the large-width limit of quantum neural networks.
  arXiv  Detail & Related papers  (2024-08-19T12:18:07Z)
• Improving Quantum Developer Experience with Kubernetes and Jupyter Notebooks [2.2649161260425723]
  We investigate the potential of using an accessible and cost-efficient manner remote computational capabilities to improve the experience of quantum software developers. New capabilities need software solutions that are able to effectively harness its power.
  arXiv  Detail & Related papers  (2024-08-13T09:27:35Z)
• Quantum algorithms: A survey of applications and end-to-end complexities [90.05272647148196]
  The anticipated applications of quantum computers span across science and industry. We present a survey of several potential application areas of quantum algorithms. We outline the challenges and opportunities in each area in an "end-to-end" fashion.
  arXiv  Detail & Related papers  (2023-10-04T17:53:55Z)
• Software Architecture Challenges in Integrating Hybrid Classical-Quantum Systems [3.2851683371946767]
  The emergence of quantum computing proposes a revolutionary paradigm that can radically transform numerous scientific and industrial application domains. The ability of quantum computers to scale computations exponentially imply better performance and efficiency for certain algorithmic tasks than current computers provide. To gain benefit from such improvement, quantum computers must be integrated with existing software systems, a process that is not straightforward.
  arXiv  Detail & Related papers  (2023-08-02T08:20:34Z)
• Entanglement-Assisted Quantum Networks: Mechanics, Enabling Technologies, Challenges, and Research Directions [66.27337498864556]
  This paper presents a comprehensive survey of entanglement-assisted quantum networks. It provides a detailed overview of the network structure, working principles, and development stages. It also emphasizes open research directions, including architecture design, entanglement-based network issues, and standardization.
  arXiv  Detail & Related papers  (2023-07-24T02:48:22Z)
• Quantum Software Analytics: Opportunities and Challenges [25.276328005616204]
  Quantum computing systems depend on the principles of quantum mechanics to perform challenging tasks more efficiently than their classical counterparts. In classical software engineering, the software life cycle is used to document and structure the processes of design, implementation, and maintenance of software applications. We summarize a set of software analytics topics and techniques in the development life cycle that can be leveraged and integrated into quantum software application development.
  arXiv  Detail & Related papers  (2023-07-21T02:24:31Z)
• Assessing requirements to scale to practical quantum advantage [56.22441723982983]
  We develop a framework for quantum resource estimation, abstracting the layers of the stack, to estimate resources required for large-scale quantum applications. We assess three scaled quantum applications and find that hundreds of thousands to millions of physical qubits are needed to achieve practical quantum advantage. A goal of our work is to accelerate progress towards practical quantum advantage by enabling the broader community to explore design choices across the stack.
  arXiv  Detail & Related papers  (2022-11-14T18:50:27Z)
• Formal Verification of Quantum Programs: Theory, Tools and Challenges [0.0]
  Survey aims to be a short introduction into the area of formal verification of quantum programs. This survey examines some of the challenges that the field may face in the future, namely the development of complex quantum algorithms.
  arXiv  Detail & Related papers  (2021-10-04T11:00:48Z)
• On exploring the potential of quantum auto-encoder for learning quantum systems [60.909817434753315]
  We devise three effective QAE-based learning protocols to address three classically computational hard learning problems. Our work sheds new light on developing advanced quantum learning algorithms to accomplish hard quantum physics and quantum information processing tasks.
  arXiv  Detail & Related papers  (2021-06-29T14:01:40Z)
• An Application of Quantum Annealing Computing to Seismic Inversion [55.41644538483948]
  We apply a quantum algorithm to a D-Wave quantum annealer to solve a small scale seismic inversions problem. The accuracy achieved by the quantum computer is at least as good as that of the classical computer.
  arXiv  Detail & Related papers  (2020-05-06T14:18:44Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.