Quantum Computing and Cloud Technologies in Decision Support
Abstract
This chapter surveys quantum computing and its integration with cloud infrastructures for decision support. It introduces the algorithmic core (Shor, Grover, variational circuits, and quantum linear-algebra routines), then situates current devices in the Noisy Intermediate-Scale Quantum (NISQ) regime – sources of noise, depth limits, gate-error rates, error-mitigation techniques, and the pathway to fault tolerance via surface codes and below-threshold operation. On the systems side, it compares deployment patterns from local simulators and on-prem accelerators to managed back-ends and examines orchestration, security, data-sovereignty, and carbon-budget considerations. Application sections treat chemistry and materials as native targets; finance, logistics, and language tasks are presented through instance-wise benchmarking against tuned classical baselines. The chapter formalizes hybrid design patterns in which quantum processors act as specialized co-processors within classical loops, with workload placement, auditability, and incident reporting aligned to current governance expectations. It then analyses quantum-cloud risks (multi-tenant side channels, energy footprint) and geopolitical dynamics (deglobalization, digital colonialism) and outlines federated and edge-to-core cloud modalities supporting Industry 5.0 aims of personalization, sustainability, and antifragility. The closing sections summarize technical obstacles (coherence, control, scalable error correction), catalogue public/educational access routes, and provide readiness checklists and architecture templates for teams preparing quantum-assisted workflows.
