Qubernetes: Towards a Unified Cloud-Native Execution Platform for Hybrid Classic-Quantum Computing
- URL: http://arxiv.org/abs/2408.01436v1
- Date: Fri, 19 Jul 2024 06:33:10 GMT
- Title: Qubernetes: Towards a Unified Cloud-Native Execution Platform for Hybrid Classic-Quantum Computing
- Abstract summary: The emergence of quantum computing proposes a revolutionary paradigm that can transform numerous scientific and industrial application domains.
The ability of quantum computers to scale computations beyond what the current computers are capable of implies better performance and efficiency for certain algorithmic tasks.
We propose a unified execution model that addresses the challenges that emerge from building hybrid classical-quantum applications at scale.
- Score: 2.2649161260425723
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Context: 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 beyond what the current computers are capable of implies better performance and efficiency for certain algorithmic tasks. Objective: However, to benefit from such improvement, quantum computers must be integrated with existing software systems, a process that is not straightforward. In this paper, we propose a unified execution model that addresses the challenges that emerge from building hybrid classical-quantum applications at scale. Method: Following the Design Science Research methodology, we proposed a convention for mapping quantum resources and artifacts to Kubernetes concepts. Then, in an experimental Kubernetes cluster, we conducted experiments for scheduling and executing quantum tasks on both quantum simulators and hardware. Results: The experimental results demonstrate that the proposed platform Qubernetes (or Kubernetes for quantum) exposes the quantum computation tasks and hardware capabilities following established cloud-native principles, allowing seamless integration into the larger Kubernetes ecosystem. Conclusion: The quantum computing potential cannot be realised without seamless integration into classical computing. By validating that it is practical to execute quantum tasks in a Kubernetes infrastructure, we pave the way for leveraging the existing Kubernetes ecosystem as an enabler for hybrid classical-quantum computing.
Related papers
- Strategic Plan for Neutral Atom Quantum Computation [84.56908019536233]
We present a strategic plan for neutral atom quantum computation, bringing together hardware development and theory advancements.<n>The concept of practical quantum advantage is defined, along with how to verify claims of advantage, and approaches to designing quantum algorithms that deliver practical advantage.
arXiv Detail & Related papers (2026-07-23T17:36:19Z) - Quantum-enhanced Computer Vision: Going Beyond Classical Algorithms [50.573955644831386]
Quantum-enhanced Computer Vision (QeCV) is a new research field at the intersection of computer vision, machine learning and quantum computing.<n>It has high potential to transform how visual signals are processed and interpreted with the help of quantum computing.<n>This survey contributes to the existing literature on QeCV with a holistic review of this research field.
arXiv Detail & Related papers (2025-10-08T17:59:51Z) - SeQUeNCe GUI: An Extensible User Interface for Discrete Event Quantum Network Simulations [55.2480439325792]
SeQUeNCe is an open source simulator of quantum network communication.
We implement a graphical user interface which maintains the core principles of SeQUeNCe.
arXiv Detail & Related papers (2025-01-15T19:36:09Z) - Assessing and Advancing the Potential of Quantum Computing: A NASA Case Study [11.29246196323319]
We describe NASA's work in assessing and advancing the potential of quantum computing.
We discuss advances in algorithms, both near- and longer-term, and the results of our explorations on current hardware and with simulations.
This work also includes physics-inspired classical algorithms that can be used at application scale today.
arXiv Detail & Related papers (2024-06-21T19:05:42Z) - Training Computer Scientists for the Challenges of Hybrid
Quantum-Classical Computing [0.5277756703318045]
We propose a new lecture and exercise series on Hybrid Quantum-Classical Systems.
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 to apply techniques and methods they are already familiar with.
arXiv Detail & Related papers (2024-03-01T10:14:50Z) - A Quantum-Classical Collaborative Training Architecture Based on Quantum
State Fidelity [50.387179833629254]
We introduce a collaborative classical-quantum architecture called co-TenQu.
Co-TenQu enhances a classical deep neural network by up to 41.72% in a fair setting.
It outperforms other quantum-based methods by up to 1.9 times and achieves similar accuracy while utilizing 70.59% fewer qubits.
arXiv Detail & Related papers (2024-02-23T14:09:41Z) - Quantum Algorithm Cards: Streamlining the development of hybrid
classical-quantum applications [0.0]
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 implies 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 (2023-10-04T06:02:59Z) - The QUATRO Application Suite: Quantum Computing for Models of Human
Cognition [49.038807589598285]
We unlock a new class of applications ripe for quantum computing research -- computational cognitive modeling.
We release QUATRO, a collection of quantum computing applications from cognitive models.
arXiv Detail & Related papers (2023-09-01T17:34:53Z) - The Basis of Design Tools for Quantum Computing: Arrays, Decision
Diagrams, Tensor Networks, and ZX-Calculus [55.58528469973086]
Quantum computers promise to efficiently solve important problems classical computers never will.
A fully automated quantum software stack needs to be developed.
This work provides a look "under the hood" of today's tools and showcases how these means are utilized in them, e.g., for simulation, compilation, and verification of quantum circuits.
arXiv Detail & Related papers (2023-01-10T19:00:00Z) - 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) - Practical application-specific advantage through hybrid quantum
computing [0.0]
We present a hybrid quantum cloud based on a memory-centric and heterogeneous multiprocessing architecture.
We show the advantage of hybrid algorithms compared to standard classical algorithms in both the computational speed and quality of the solution.
arXiv Detail & Related papers (2022-05-10T12:58:41Z) - Quantum Federated Learning with Quantum Data [87.49715898878858]
Quantum machine learning (QML) has emerged as a promising field that leans on the developments in quantum computing to explore large complex machine learning problems.
This paper proposes the first fully quantum federated learning framework that can operate over quantum data and, thus, share the learning of quantum circuit parameters in a decentralized manner.
arXiv Detail & Related papers (2021-05-30T12:19:27Z) - Tensor Network Quantum Virtual Machine for Simulating Quantum Circuits
at Exascale [57.84751206630535]
We present a modernized version of the Quantum Virtual Machine (TNQVM) which serves as a quantum circuit simulation backend in the e-scale ACCelerator (XACC) framework.
The new version is based on the general purpose, scalable network processing library, ExaTN, and provides multiple quantum circuit simulators.
By combining the portable XACC quantum processors and the scalable ExaTN backend we introduce an end-to-end virtual development environment which can scale from laptops to future exascale platforms.
arXiv Detail & Related papers (2021-04-21T13:26:42Z) - Quantum Computation [0.0]
We will discuss and summarized the core principles and practical application areas of quantum computation.
The mapping of computation onto the behavior of physical systems is a historical challenge.
We will evaluate the essential technology required for quantum computers to be able to function correctly.
arXiv Detail & Related papers (2020-06-04T11:57:18Z)
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.