开源量子机器学习库，让非专家也能在真实硬件上运行量子算法。
Qiskit Machine Learning: an open-source library for quantum machine learning tasks at scale on quantum hardware and classical simulators
- 封装量子计算原语，统一对接经典模拟器与真实量子硬件。
- 支持从简单实验到复杂模型的全链条开发，适合初学者与科研人员。
- 基于Apache 2.0协议开源，可自由扩展和定制使用。
我们介绍了 Qiskit Machine Learning (ML)，一个将量子计算与传统机器学习相结合的高层级 Python 库。其 API 抽象了 Qiskit 的基本原语，便于与经典模拟器和量子硬件交互。Qiskit ML 最初于 2019 年作为概念验证代码推出，现已发展为模块化、直观易用的工具，既适合非专业用户，也支持量子计算科学家和开发者进行扩展与精细控制。该库为公开开源项目，采用 Apache Version 2.0 许可证分发。
原文摘要 · Abstract (English)
We present Qiskit Machine Learning (ML), a high-level Python library that combines elements of quantum computing with traditional machine learning. The API abstracts Qiskit's primitives to facilitate interactions with classical simulators and quantum hardware. Qiskit ML started as a proof-of-concept code in 2019 and has since been developed to be a modular, intuitive tool for non-specialist users while allowing extensibility and fine-tuning controls for quantum computational scientists and developers. The library is available as a public, open-source tool and is distributed under the Apache version 2.0 license.
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