Andrew Seltzman | Searcharxiv

arXiv2026

Optimization of Precipitate Segmentation Through Linear Genetic Programming of Image Processing

Current analysis of additive manufactured niobium-based copper alloys relies on hand annotation due to varying contrast, noise, and image artifacts present in micrographs, slowing iteration speed in alloy development. We present a filtering and segmentation algorithm for detecting precipitates in FIB cross-section micrographs, optimized using linear genetic programming (LGP), which accounts for the various artifacts. To this end, the optimization environment uses a domain-specific language for image processing to iterate on solutions. Programs in this language are a list of image-filtering blocks with tunable parameters that sequentially process an input image, allowing for reliable generation and mutation by a genetic algorithm. Our environment produces optimized human-interpretable MATLAB code representing an image filtering pipeline. Under ideal conditions--a population size of 60 and a maximum program length of 5 blocks--our system was able to find a near-human accuracy solution with an average evaluation error of 1.8% when comparing segmentations pixel-by-pixel to a human baseline using an XOR error evaluation. Our automation work enabled faster iteration cycles and furthered exploration of the material composition and processing space: our optimized pipeline algorithm processes a 3.6 megapixel image in about 2 seconds on average. This ultimately enables convergence on strong, low-activation, precipitation hardened copper alloys for additive manufactured fusion reactor parts.

cs.CV↗

arXiv2025

Virtual Critical Coupling in High-Power Resonant Systems

Exciting high-power resonators pose challenges such as managing power reflections, which can cause energy losses and damage system components. This is crucial for applications like Lower Hybrid Current Drive (LHCD) systems in tokamaks, where plasma stability and confinement depend on efficient energy transfer. In this work, we introduce the Virtual Critical Coupling mechanism to address reflection-related challenges in S-band resonators. We theoretically designed a complex frequency excitation signal tailored to the resonator's characteristics, facilitating efficient energy storage and minimizing reflections without mechanical modifications. Using a custom low-level RF system, we conducted experiments at 32 mW and 600 kW with a 5 MW S-band klystron, demonstrating a ninefold reduction in reflection coefficients compared to traditional monochromatic excitation in high-power tests. This approach enhances the efficiency and stability of high-power resonant systems, potentially advancing nuclear fusion energy production.

physics.optics↗