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Quantum Cloud Computing: A Review, Open Problems, and Future Directions
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Quantum cloud computing is an emerging paradigm of computing that empowers quantum applications and their deployment on quantum computing resources without the need for a specialized environment to host and operate physical quantum computers. This paper reviews recent advances, identifies open problems, and proposes future directions in quantum cloud computing. It discusses the state-of-the-art quantum cloud advances, including the various cloud-based models, platforms, and recently developed technologies and software use cases. Furthermore, it discusses different aspects of the quantum cloud, including resource management, quantum serverless, security, and privacy problems. Finally, the paper examines open problems and proposes the future directions of quantum cloud computing, including potential opportunities and ongoing research in this emerging field.
Forward citations
Cited by 14 Pith papers
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Comparing Classical Simulation and Sample-Based Learning of Quantum Systems
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Evaluation of Noise and Crosstalk in Neutral Atom Quantum Computers
Co-located simulations on a neutral atom machine interfere more when placed closer, and a moving target defense that relocates the victim restores fidelity to about 0.995 in simulator tests.
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Optimizing Resource Allocation in a Distributed Quantum Computing Cloud: A Game-Theoretic Approach
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Systematic Experiment Tracking in Quantum Software: A Case Study of Reservoir Computing with Error Mitigation
MLflow-style experiment tracking, extended with quantum provenance, supports reproducible multi-stage quantum software pipelines, shown on error-mitigated quantum reservoir computing for chaotic time-series prediction.
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Nonclassicality of a delayed remote-controlled quantum computing model
A class of delayed RCQC models exhibits nonclassicality in a semi-device-independent prepare-and-measure scenario via dimension-witness violations, with reversed temporal order.
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Quantum computing for accurate large-scale electronic-structure calculations: DFT-embedded, post-processed quantum-selected configuration interaction
A DFT-embedded quantum-selected configuration interaction framework combines quantum and classical methods to achieve ~1 kcal/mol accuracy on large-scale chemical systems using a subset of qubits from a 144-qubit quan...
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Joint Optimization of Qubit Leasing and Quantum Circuit Distribution
Formulates JQLQCD as ILP, proves NP-completeness, solves special cases in closed form or polynomial time, and evaluates a greedy algorithm with local search on large instances via numerical computations.
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Comparing Classical Simulation and Sample-Based Learning of Quantum Systems
Empirical study finds neural-network learning difficulty (via Hessian eigenvalue and random subspace optimization) correlates with classical simulation hardness parameterized by MPS bond dimension and T-gate count.
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Toward Secure Multitenant Quantum Computing: Circuit Affinity, Crosstalk Patterns, and Grouping Strategies
Crosstalk patterns between quantum circuits on IBM processors are predictable by circuit type and hardware architecture, with high intra-revision consistency and topological decoupling between lattice types.
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QCOEM: Quantum Cloud Orchestration with Evolutionary Multi-Objective Optimization
QCOEM applies NSGA-II/III with AASF to quantum task scheduling and reports roughly 30% higher modeled fidelity and zero rescheduling versus noise-agnostic heuristics in emulation.
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Future-Proofing Cloud Security Against Quantum Attacks: Risk, Transition, and Mitigation Strategies
This survey analyzes quantum vulnerabilities in cloud computing and provides a structured framework for transitioning to post-quantum cryptography with risk assessments and deployment roadmaps.
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Localized Kernel Methods for Signal Processing
The manuscript is internally inconsistent: the abstract describes localized kernel signal processing, while the body is a different paper on quantum task scheduling, leaving the abstract's claims entirely unsupported.
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