{"ID":2845209,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.04107","arxiv_id":"2511.04107","title":"Depth-13 Sorting Networks for 28 Channels","abstract":"We establish new depth upper bounds for sorting networks on 27 and 28 channels, improving the previous best bound of 14 to 13. Our 28-channel network is constructed with reflectional symmetry by combining high-quality prefixes of 16- and 12-channel networks, extending them greedily one comparator at a time, and using a SAT solver to complete the remaining layers.","short_abstract":"We establish new depth upper bounds for sorting networks on 27 and 28 channels, improving the previous best bound of 14 to 13. Our 28-channel network is constructed with reflectional symmetry by combining high-quality prefixes of 16- and 12-channel networks, extending them greedily one comparator at a time, and using a...","url_abs":"https://arxiv.org/abs/2511.04107","url_pdf":"https://arxiv.org/pdf/2511.04107v2","authors":"[\"Chengu Wang\"]","published":"2025-11-06T06:46:29Z","proceeding":"cs.DS","tasks":"[\"cs.DS\",\"cs.DM\"]","methods":"[]","has_code":false}