Quantum Software Security Challenges within Shared Quantum Computing Environments

• URL: http://arxiv.org/abs/2507.17712v1
• Date: Wed, 23 Jul 2025 17:23:34 GMT
• Title: Quantum Software Security Challenges within Shared Quantum Computing Environments
• Authors: Samuel Ovaskainen, Majid Haghparast, Tommi Mikkonen,
• Abstract summary: The number of qubits in quantum computers keeps growing, but most quantum programs remain relatively small because of the noisy nature of the underlying quantum hardware.<n>This article explores and reports the key challenges identified in quantum software security within shared quantum computing environments.
• Score: 2.4742581572364126
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The number of qubits in quantum computers keeps growing, but most quantum programs remain relatively small because of the noisy nature of the underlying quantum hardware. This might lead quantum cloud providers to explore increased hardware utilization, and thus profitability through means such as multi-programming, which would allow the execution of multiple programs in parallel. The adoption of such technology would bring entirely new challenges to the field of quantum software security. This article explores and reports the key challenges identified in quantum software security within shared quantum computing environments.

Related papers

• Sequential Quantum Computing [41.94295877935867]
  We propose and experimentally demonstrate sequential quantum computing (SQC), a paradigm that utilizes multiple or heterogeneous quantum processors.<n>SQC overcomes the limitations of each type of quantum computer by combining their complementary strengths.<n>These results highlight SQC as a powerful and versatile approach for addressing complex quantum optimization problems.
  arXiv  Detail & Related papers  (2025-06-25T17:51:29Z)
• 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)
• Parallel Quantum Computing Simulations via Quantum Accelerator Platform Virtualization [44.99833362998488]
  We present a model for parallelizing simulation of quantum circuit executions. The model can take advantage of its backend-agnostic features, enabling parallel quantum circuit execution over any target backend.
  arXiv  Detail & Related papers  (2024-06-05T17:16:07Z)
• Enhanced quantum state transfer: Circumventing quantum chaotic behavior [35.74056021340496]
  We show how to transfer few-particle quantum states in a two-dimensional quantum network. Our approach paves the way to short-distance quantum communication for connecting distributed quantum processors or registers.
  arXiv  Detail & Related papers  (2024-02-01T19:00:03Z)
• Full-Stack Quantum Software in Practice: Ecosystem, Stakeholders and Challenges [5.242305867893238]
  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.
  arXiv  Detail & Related papers  (2023-07-30T23:44:22Z)
• Quantivine: A Visualization Approach for Large-scale Quantum Circuit Representation and Analysis [31.203764035373677]
  We develop Quantivine, an interactive system for exploring and understanding quantum circuits. A series of novel circuit visualizations are designed to uncover contextual details such as qubit provenance, parallelism, and entanglement. The effectiveness of Quantivine is demonstrated through two usage scenarios of quantum circuits with up to 100 qubits.
  arXiv  Detail & Related papers  (2023-07-18T04:51:28Z)
• QPanda: high-performance quantum computing framework for multiple application scenarios [15.954489124674394]
  This paper proposes QPanda, an application scenario-oriented quantum programming framework with high-performance simulation. It implements high-performance simulation of quantum circuits, a configuration of the fusion processing backend of quantum computers and supercomputers, and compilation and optimization methods of quantum programs for NISQ machines.
  arXiv  Detail & Related papers  (2022-12-29T07:38:50Z)
• Software for Massively Parallel Quantum Computing [1.0118253437732934]
  Recent advances in quantum computing have enabled a class of classically parallel quantum workloads. We present the full-stack software framework developed at Quantum Brilliance to enable multi-modal parallelism for hybrid quantum workloads.
  arXiv  Detail & Related papers  (2022-11-23T23:59:02Z)
• Near-Term Quantum Computing Techniques: Variational Quantum Algorithms, Error Mitigation, Circuit Compilation, Benchmarking and Classical Simulation [5.381727213688375]
  We are still a long way from reaching the maturity of a full-fledged quantum computer. An outstanding challenge is to come up with an application that can reliably carry out a nontrivial task. Several near-term quantum computing techniques have been proposed to characterize and mitigate errors.
  arXiv  Detail & Related papers  (2022-11-16T07:53:15Z)
• 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)
• Optimal Stochastic Resource Allocation for Distributed Quantum Computing [50.809738453571015]
  We propose a resource allocation scheme for distributed quantum computing (DQC) based on programming to minimize the total deployment cost for quantum resources. The evaluation demonstrates the effectiveness and ability of the proposed scheme to balance the utilization of quantum computers and on-demand quantum computers.
  arXiv  Detail & Related papers  (2022-09-16T02:37:32Z)
• 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)

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.