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Color code decoder with improved scaling for correcting circuit-level noise — Seok-Hyung Lee (Sydney) Two-dimensional color codes are a promising candidate for fault-tolerant quantum computing because of their advantages, including high encoding rates and the capability to implement Clifford gates transversally. However, decoding these color codes, especially under circuit-level noise, presents a significant challenge due to their intrinsic structure and the complexity in extracting syndrome. In this talk, I introduce a color-code decoder that efficiently tackles these issues by combining two minimum-weight perfect matching (MWPM) decoders for each color, which can be generalized to handle circuit-level noise by employing detector error models. I provide comprehensive analyses of the decoder, covering its threshold and sub-threshold scaling, which show that the decoder outperforms existing matching-based decoders. Key Highlights & Overview: Learning <strong>Color Code Error Correction Zoo</strong> is essential for modern technical workflows and software skills. Explore curated video courses, expert walkthroughs, and detailed lesson notes today on <strong>TutorTube</strong>.