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Abstract Automatic differentiation (AD) enables powerful metasurface inverse design but requires extensive theoretical and programming expertise. We present a Model Context Protocol (MCP) assisted framework that allows researchers to conduct inverse design with differentiable solvers through large language models (LLMs). Since LLMs inherently lack knowledge of specialized solvers, our proposed solution provides dynamic access to verified code templates and comprehensive documentation through dedicated servers. The LLM autonomously accesses these resources to generate complete inverse design codes without prescribed coordination rules. Evaluation on the Huygens meta-atom design task with the differentiable TorchRDIT solver shows that while both natural language and structured prompting strategies achieve high success rates, structured prompting significantly outperforms in design quality, workflow efficiency, computational cost, and error reduction. The minimalist server design, using only 5 APIs, demonstrates how MCP makes sophisticated computational tools accessible to researchers without programming expertise, offering a generalizable integration solution for other scientific tasks. 

Abstract Solving mathematical equations faster and more efficiently has been a Holy Grail for centuries for scientists and engineers across all disciplines. While electronic digital circuits have revolutionized equation solving in recent decades, it has become apparent that performance gains from brute-force approaches of compute-solvers are quickly saturating over time. Instead, paradigms that leverage the universes’ natural tendency to minimize a system’s free energy, such as annealers or Ising Machines, are being sought after due to favorable complexity scaling. Here, we introduce a programmable analog solver leveraging the formal mathematical equivalence between Maxwell’s equations and photonic circuitry. It features a mesh network of nanophotonic beams to find solutions to partial differential equations. As an example, we designed, fabricated, and demonstrated a novel application-specific photonic integrated circuit comprised of electro-optically reconfigurable nodes and experimentally validated 90 % accuracy with respect to a commercial solver. Finally, we tested this photonic integrated chip performance by simulating thermal diffusion on a spacecraft’s heat shield during re-entry to a planet’s atmosphere. The programmable light-circuitry presented herein offers a facile route for solving complex problems and thus will have profound potential applications across many scientific and engineering fields. 

Programmable and reconfigurable optics hold significant potential for transforming a broad spectrum of applications, spanning space explorations to biomedical imaging, gas sensing, and optical cloaking. The ability to adjust the optical properties of components like filters, lenses, and beam steering devices could result in dramatic reductions in size, weight, and power consumption in future optoelectronic devices. Among the potential candidates for reconfigurable optics, chalcogenide‐based phase change materials (PCMs) offer great promise due to their non‐volatile and analogue switching characteristics. Although PCM have found widespread use in electronic data storage, these memory devices are deeply sub‐micron‐sized. To incorporate phase change materials into free‐space optical components, it is essential to scale them up to beyond several hundreds of microns while maintaining reliable switching characteristics. This study demonstrated a non‐mechanical, non‐volatile transmissive filter based on low‐loss PCMs with a 200 × 200 µm²switching area. The device/metafilter can be consistently switched between low‐ and high‐transmission states using electrical pulses with a switching contrast ratio of 5.5 dB. The device was reversibly switched for 1250 cycles before accelerated degradation took place. The work represents an important step toward realizing free‐space reconfigurable optics based on PCMs. 

Reconfigurable or programmable photonic devices are rapidly growing and have become an integral part of many optical systems. The ability to selectively modulate electromagnetic waves through electrical stimuli is crucial in the advancement of a variety of applications from data communication and computing devices to environmental science and space explorations. Chalcogenide‐based phase‐change materials (PCMs) are one of the most promising material candidates for reconfigurable photonics due to their large optical contrast between their different solid‐state structural phases. Although significant efforts have been devoted to accurate simulation of PCM‐based devices, in this paper, three important aspects which have often evaded prior models yet having significant impacts on the thermal and phase transition behavior of these devices are highlighted: the enthalpy of fusion, the heat capacity change upon glass transition, as well as the thermal conductivity of liquid‐phase PCMs. The important topic of switching energy scaling in PCM devices, which also helps explain why the three above‐mentioned effects have long been overlooked in electronic PCM memories but only become important in photonics, is further investigated. These findings offer insight to facilitate accurate modeling of PCM‐based photonic devices and can inform the development of more efficient reconfigurable optics.