Inverse Design of Multi-Layer Sub-Pixel-Resolution RF Passives Through Grayscale Diffusion with Flexible S-Parameter Conditioning

TL;DR

This paper introduces a novel inverse design method for multi-layer RF passive components using grayscale diffusion, enabling rapid generation of physically constrained designs from partial S-parameters.

Contribution

It presents a flexible, multi-modal inverse design framework that handles complex constraints and produces manufacturable RF passive components with high accuracy.

Findings

Designs match target S-parameters within 0.77 ± 1.28 dB error

Candidate designs generated in seconds

Validated with fabricated filters on RO4003C substrate

Abstract

Inverse design of RF passive components from S-parameters is a high-dimensional, ill-posed problem, and prior generative approaches are limited to single-layer binary-metallization structures. This paper presents an inverse design approach that generates passive components from partial S-parameter inputs on an $8\times8$ mm board discretized at $64\times64$ pixels with sub-pixel grayscale metallization across 1-20 GHz. The framework generates two-layer copper layouts with vias, with hard physical constraints on feed locations enforced through annealed Langevin projection, flexible multi-modal conditioning on partial S-parameter specifications, port locations, dielectric properties, reference topology, and variable port placement. Candidate designs are generated in seconds, with surrogate-predicted S-parameters matching targets to within $0.77 \pm 1.28$ dB weighted mean absolute error. We validate the approach with two fabricated designs on RO4003C: a manufacturable alternative to a hairpin filter whose coupling gaps violate fabrication rules, and a combline bandpass filter designed from scratch given only target S-parameters.