DeepUnfolding_Agent: A Classical_Quantum Adaptive Control API
Computer Science > Computation and Language arXiv:2610.20615 (cs) [Submitted on 21 Jul 2026] Title:DeepUnfolding_Agent: A Classical_Quantum Adaptive Control API Authors:Shanika Iroshi Nanayakkara, Shiva Raj Pokhrel View a PDF of the paper titled DeepUnfolding_Agent: A Classical_Quantum Adaptive Control API, by Shanika Iroshi Nanayakkara and 1 other authors View PDF HTML (experimental)
计算机科学 > 计算与语言 arXiv:2610.20615 (cs) [提交于 2026 年 7 月 21 日] 标题：DeepUnfolding_Agent：一种经典-量子自适应控制 API 作者：Shanika Iroshi Nanayakkara, Shiva Raj Pokhrel 查看题为《DeepUnfolding_Agent：一种经典-量子自适应控制 API》的论文 PDF，作者：Shanika Iroshi Nanayakkara 及其他 1 位作者 查看 PDF HTML（实验性）
Abstract:Adaptive optimization workflows in machine learning, federated learning, quantum machine learning, and hybrid classical quantum systems often embed controller logic directly inside task specific training scripts. This coupling limits reuse, reproducibility, safety validation, and fair comparison across execution environments.
摘要：机器学习、联邦学习、量子机器学习以及混合经典-量子系统中的自适应优化工作流，通常将控制器逻辑直接嵌入到特定任务的训练脚本中。这种耦合限制了跨执行环境的重用性、可重复性、安全性验证以及公平比较。
This paper presents DeepUnfolding Agent, a schema-driven FastAPI platform that exposes deep unfolded adaptive control as an external software service. External executors register a strategy schema, submit round-level diagnostic variables, receive schema-bounded control actions, execute one optimization round, and return feedback for controller update.
本文提出了 DeepUnfolding Agent，这是一个模式驱动的 FastAPI 平台，它将深度展开的自适应控制作为一种外部软件服务公开。外部执行器注册策略模式，提交轮次级别的诊断变量，接收受模式约束的控制动作，执行一轮优化，并返回反馈以进行控制器更新。
The framework separates controller intelligence from domain specific execution through a strategy registry, diagnostic to state adapter, controller factory, safety guard, executor abstraction, feedback update path, SQLite persistence layer, Docker deployment, and reproducible benchmark scripts. The implementation supports classical, quantum-aware, hybrid, Qiskit Aer, and optional IBM quantum processing execution pathways.
该框架通过策略注册表、诊断到状态适配器、控制器工厂、安全防护、执行器抽象、反馈更新路径、SQLite 持久层、Docker 部署和可重复的基准测试脚本，将控制器智能与特定领域的执行分离开来。该实现支持经典、量子感知、混合、Qiskit Aer 以及可选的 IBM 量子处理执行路径。
We validate the software through unit, schema, API, safety, orchestration, Quantum execution, checkpointing, and Docker tests, and demonstrate external user fixed versus adaptive workflows across finance, healthcare, genomics, transport, noisy quantum simulation, and hardware backed IBM Quantum execution. The results show that DeepUnfolding-Agent provides a reusable and traceable adaptive control layer for heterogeneous optimization workflows. Our quantum experiments are interpreted as API level quantum control and hardware portability evidence.
我们通过单元测试、模式测试、API 测试、安全测试、编排测试、量子执行测试、检查点测试和 Docker 测试验证了该软件，并展示了在金融、医疗、基因组学、交通、噪声量子模拟和硬件支持的 IBM 量子执行中，外部用户固定工作流与自适应工作流的对比。结果表明，DeepUnfolding-Agent 为异构优化工作流提供了一个可重用且可追溯的自适应控制层。我们的量子实验被解读为 API 级别的量子控制和硬件可移植性的证据。