Towards reliable quantum software, algorithm and use-case development: Multidisciplinary analysis from the perspective of Finnish industries

• URL: http://arxiv.org/abs/2506.16246v1
• Date: Thu, 19 Jun 2025 12:05:47 GMT
• Title: Towards reliable quantum software, algorithm and use-case development: Multidisciplinary analysis from the perspective of Finnish industries
• Authors: Matti Silveri, Tommi Mikkonen, Kimmo Halunen, Teiko Heinosaari, Aravind Plathanam Babu, Vlad Stirbu, Oskari Kerppo, Majid Haghparast, Andrés D. Muñoz-Moller,
• Abstract summary: TORQS has studied the dilemma of reliable software development and potential for quantum computing for Finnish industries from multidisciplinary points of views.<n>Here we condense the main observations and results of the project into an essay roadmap and timeline for investing in quantum software, algorithms, hardware, and business.
• Score: 1.7529550873546489
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Quantum computing is a disruptive technology with the potential to transform various fields. It has predicted abilities to solve complex computational problems beyond the reach of classical computers. However, developing quantum software faces significant challenges. Quantum hardware is yet limited in size and unstable with errors and noise. A shortage of skilled developers and a lack of standardization delay adoption. Quantum hardware is in the process of maturing and is constantly changing its characteristics rendering algorithm design increasingly complex, requiring innovative solutions. Project "Towards reliable quantum software development: Approaches and use-cases" TORQS has studied the dilemma of reliable software development and potential for quantum computing for Finnish industries from multidisciplinary points of views. Here we condense the main observations and results of the project into an essay roadmap and timeline for investing in quantum software, algorithms, hardware, and business.

Related papers

• Quantum Software Engineering and Potential of Quantum Computing in Software Engineering Research: A Review [8.626933144631955]
  This paper aims to review the role of quantum computing in software engineering research and the latest developments in quantum software engineering.<n>We begin by introducing quantum computing, exploring its fundamental concepts, and discussing its potential applications in software engineering.
  arXiv  Detail & Related papers  (2025-02-13T03:22:36Z)
• How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits [3.970891204847277]
  Small-scale demonstrations have become possible for quantum algorithmic primitives on hundreds of physical qubits.<n>We show how the road to scaling could be paved by adopting existing semiconductor technology to build much higher-quality qubits.<n>We argue that, to tackle industry-scale classical optimization and machine learning problems, heterogeneous quantum-probabilistic computing with custom-designed accelerators should be considered.
  arXiv  Detail & Related papers  (2024-11-15T18:22:46Z)
• 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)
• Shaping photons: quantum computation with bosonic cQED [41.94295877935867]
  We discuss the progress, challenges, and future directions in building a bosonic cQED quantum computer. We conclude with our views of the key challenges that lie on the horizon, as well as scientific and cultural strategies for overcoming them.
  arXiv  Detail & Related papers  (2023-11-07T09:59:57Z)
• 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)
• Quantum Software Engineering Challenges from Developers' Perspective: Mapping Research Challenges to the Proposed Workflow Model [5.287156503763459]
  Software engineering of quantum programs can be approached from two directions. In this paper, we aim at bridging the gap by starting with the quantum computing workflow and by mapping existing software engineering research to this workflow.
  arXiv  Detail & Related papers  (2023-08-02T13:32:31Z)
• Quantum Computing Toolkit From Nuts and Bolts to Sack of Tools [0.0]
  Quantum computing has the potential to provide exponential performance benefits in processing over classical computing. It utilizes quantum mechanics phenomena (such as superposition, entanglement, and interference) to solve a computational problem. Quantum computers are in the nascent stage of development and are noisy due to decoherence, i.e., quantum bits deteriorate with environmental interactions.
  arXiv  Detail & Related papers  (2023-02-17T14:08:44Z)
• Quantum Machine Learning: from physics to software engineering [58.720142291102135]
  We show how classical machine learning approach can help improve the facilities of quantum computers. We discuss how quantum algorithms and quantum computers may be useful for solving classical machine learning tasks.
  arXiv  Detail & Related papers  (2023-01-04T23:37:45Z)
• Recent Advances for Quantum Neural Networks in Generative Learning [98.88205308106778]
  Quantum generative learning models (QGLMs) may surpass their classical counterparts. We review the current progress of QGLMs from the perspective of machine learning. We discuss the potential applications of QGLMs in both conventional machine learning tasks and quantum physics.
  arXiv  Detail & Related papers  (2022-06-07T07:32:57Z)
• Long-Time Error-Mitigating Simulation of Open Quantum Systems on Near Term Quantum Computers [38.860468003121404]
  We study an open quantum system simulation on quantum hardware, which demonstrates robustness to hardware errors even with deep circuits containing up to two thousand entangling gates. We simulate two systems of electrons coupled to an infinite thermal bath: 1) a system of dissipative free electrons in a driving electric field; and 2) the thermalization of two interacting electrons in a single orbital in a magnetic field -- the Hubbard atom. Our results demonstrate that algorithms for simulating open quantum systems are able to far outperform similarly complex non-dissipative algorithms on noisy hardware.
  arXiv  Detail & Related papers  (2021-08-02T21:36:37Z)
• 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)
• Electronic structure with direct diagonalization on a D-Wave quantum annealer [62.997667081978825]
  This work implements the general Quantum Annealer Eigensolver (QAE) algorithm to solve the molecular electronic Hamiltonian eigenvalue-eigenvector problem on a D-Wave 2000Q quantum annealer. We demonstrate the use of D-Wave hardware for obtaining ground and electronically excited states across a variety of small molecular systems.
  arXiv  Detail & Related papers  (2020-09-02T22:46:47Z)
• 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.