RFChipAgent is a novel multi‑agent flow that uses large language model agents to automate end‑to‑end analog/RF circuit design under human supervision. The system comprises four key components: a retrieval‑augmented generation subsystem that pulls design knowledge from documentation, agents that handle topology selection and schematic/testbench assembly, a hybrid sizing engine that blends TPE and CMA‑ES optimization with simulator feedback, and a trust‑scored simulation database that informs future optimization runs. Validation on GF22FDSOI 60 GHz wideband mm‑wave low‑noise amplifiers demonstrates automated topology generation, specification‑driven exploration, and simulator‑guided optimization, yielding significant reductions in design effort while preserving sign‑off quality.
By Awani Khodkumbhe, Yunfei Feng, Raj Rangarajan, Kevin Wang, Kamal Sahota
arXiv:2606. 01862v1 Announce Type: cross Abstract: Translating user intents into physical radio signals represents the critical yet notoriously tedious final step in wireless prototyping, as it requires intricate knowledge of physical layer details and presents immense implementation challenges.
By Jiazhen Lei, Tianze Cao, Yuxin Sha, Sihan Wang, Bingbing Wang, Fengyuan Zhu, Zeming Yang, Xiaohua Tian
Analog circuit sizing remains a challenging and time-consuming task due to the large design space, strong performance trade-offs, and increasing circuit complexity in scaled technologies. Although rec...
VortexChat is an agentic framework that autonomously performs end-to-end inverse design of integrated photonic devices from natural language specifications. It combines a large language model decision agent with topology generation, gradient-based refinement, and full-wave electromagnetic simulation in a closed-loop architecture, enabling iterative decomposition of design objectives and minimal human intervention. The system successfully generated devices meeting the Vortex100 Benchmark metrics and fabricated a broadband terahertz perfect vortex beam multiplexer that matched simulation predictions.
By Faqian Chong, Yulun Wu, Shilong Li, Andrew Forbes, Hongsheng Chen, Song Han
K-TRAIL is a simulator-guided generative framework that uses diffusion-based layout generation combined with derivative-free ensemble Kalman guidance to design RF and electromagnetic circuits. It allows a black-box EM simulator to refine candidate layouts during generation, supporting synthesis from target S-parameter responses or direct RF performance constraints. Experiments on multi-layer RFIC structures demonstrate improved agreement with target responses and the ability to discover structurally distinct layouts that meet design requirements.
By Piyush Saha, Evan Newell, Hanna O'Leary, Arun Natarajan, Alireza Aghasi
AbsorbEvo is an agentic framework that autonomously designs microwave absorbers by translating natural‑language performance goals into full‑wave‑simulated designs. It combines language reasoning, physics‑based prediction, and historical feedback to guide a candidate evolution strategy, using a low‑cost predictive model to rank designs before simulation. In tests on AbsorbBench‑36, AbsorbEvo achieved a 79.17% task success rate, outperforming generic agents and random search.
By Zhicheng Feng, Yubo Zhao, Xuefeng Yao
Designing high-performance microwave absorbers requires specialized expertise in electromagnetic theory, materials science and simulation programming, and entails time-consuming optimization. Here, we...
arXiv:2610.27797v1 Announce Type: new
Abstract: 6G will be designed faster than it can be built: AI-driven search already proposes physical-layer algorithms at machine speed, while carrying a single...
By Eric Mittag, Lukas Brechtel, Maximilian Stark, Hans D. Schotten
arXiv:2607. 14165v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have demonstrated significant capability in software code generation, their application to analog Electronic Design Automation (EDA) is bottlenecked.
By Dimple Vijay Kochar, Hae-Seung Lee, Anantha P. Chandrakasan
OPERA is an expert‑taught reasoning agent that uses a large language model to design CMOS opamps from specifications to post‑layout sign‑off with open‑source tools. The agent first learns the gm/ID sizing method, then the gLayout framework, and writes a reusable layout generator that closes the layout‑extraction loop. In the SKY130 process, OPERA designed a shared constant‑gm bias and six different opamps that meet all target specifications across 15 PVT corners, with DRC‑clean and LVS‑matched layouts.
By Vishal Saxena, Soumyajit Mandal
The paper introduces a development environment where large language model (LLM) agents design RISC‑V CPUs that are implemented on an FPGA for real‑time performance evaluation. Using on‑board measurements, the approach guides design decisions and accelerates evaluation, achieving a 9.6× speedup over single‑threaded RTL simulation. In a case study, FPGA measurements uncovered long‑run performance degradation that short diagnostic runs missed, leading to candidate selection, root‑cause analysis, and a fix.
By Leo Itoh, Junichiro Kadomoto
arXiv:2608. 01791v2 Announce Type: replace-cross Abstract: The rapid development of photonic integrated circuits (PICs) is shifting the design flow from traditional graphical user interface (GUI)-based methods to script-based methods for higher flexibility, portability, and maintainability.
By Xiaohan Jiang, Zeyu Li, Wei Zhang, Jiang Xu