超快激光微加工中的可编程与静态光束整形：批判性综述
Programmable vs. Static Beam Shaping in Ultrafast Laser Micromachining: A Critical Review
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中文总结 AI 辅助
本综述针对超快激光微加工光束整形，提出应从硬件-算法协同设计视角替代传统的可编程与静态光学元件划分，评估了相关技术与算法，为下一代系统提供了设计框架与基准方法。
中文摘要 AI 辅助
光束整形已成为决定超快激光微加工的吞吐量、精度和工艺鲁棒性的主要因素之一。尽管如此，该领域仍主要通过可编程与静态光学元件的历史区分来解读，而这一框架越来越无法解释近期的进展。本综述重新审视了这一视角，认为光束整形应被理解为硬件-算法协同设计问题。在高功率空间光调制器、机器学习全息术、混合光学架构和大规模并行处理等方面，近期进展均指向同一结论：性能更多取决于光学硬件与计算算法的协同设计，而非任何单一光学元件。为建立共同的比较基础，在涵盖光学性能、可编程性、计算成本和工业部署的统一七轴框架内，对七种光束整形技术和五个算法家族进行了评估。该分析明确了吞吐量与灵活性之间长期存在的权衡已真正消失的领域。在工业并行烧蚀和高通量双光子聚合中，可编程器件如今可维持曾仅为静态光学元件所用的平均功率，这表明以硬件为中心的比较已无法反映最新技术水平。除综述近期进展外，本研究还为下一代光束整形系统提供了预测性设计框架，引入了基准测试方法、实用技术选择标准、可衡量的研究里程碑，以及用于提高未来研究可比性的报告标准。
英文摘要
Beam shaping has become one of the principal determinants of throughput, precision, and process robustness in ultrafast laser micromachining. Despite this, the field is still largely interpreted through a historical distinction between programmable and static optical elements, a framework that increasingly fails to explain recent advances. This review reexamines that perspective and argues that beam shaping should instead be understood as a hardware-algorithm co-design problem. Across high-power spatial light modulators, machine-learning holography, hybrid optical architectures, and massively parallel processing, recent advances converge on the same conclusion: performance depends more on the codesign of optical hardware and computational algorithms than on any individual optical component. To establish a common basis for comparison, seven beam-shaping technologies and five algorithm families are evaluated within a unified seven-axis framework spanning optical performance, programmability, computational cost, and industrial deployment. This analysis identifies where the long-standing trade-off between throughput and flexibility has genuinely disappeared. In industrial parallel ablation and high-throughput two-photon polymerisation, programmable devices now sustain average powers once reserved for static optics, demonstrating why hardware-centred comparisons no longer capture the state of the art. Beyond reviewing recent developments, this work provides a predictive design framework for the next generation of beam-shaping systems. It introduces a benchmarking methodology, practical technology-selection criteria, measurable research milestones, and a reporting standard for improving comparability across future studies.
