{"id":613,"date":"2025-02-28T19:50:00","date_gmt":"2025-02-28T19:50:00","guid":{"rendered":"https:\/\/imm.am\/?p=613"},"modified":"2025-04-29T19:58:07","modified_gmt":"2025-04-29T19:58:07","slug":"porting-multi-valued-neural-architectures-to-embedded-quantum-ready-hardware","status":"publish","type":"post","link":"https:\/\/imm.am\/index.php\/2025\/02\/28\/porting-multi-valued-neural-architectures-to-embedded-quantum-ready-hardware\/","title":{"rendered":"Porting Multi-Valued Neural Architectures to Embedded Quantum-Ready Hardware"},"content":{"rendered":"\n<figure class=\"wp-block-image alignleft size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"1024\" src=\"https:\/\/imm.am\/wp-content\/uploads\/2025\/02\/newsFeb2025Quant.png\" alt=\"\" class=\"wp-image-615\" style=\"width:227px;height:auto\" srcset=\"https:\/\/imm.am\/wp-content\/uploads\/2025\/02\/newsFeb2025Quant.png 1024w, https:\/\/imm.am\/wp-content\/uploads\/2025\/02\/newsFeb2025Quant-300x300.png 300w, https:\/\/imm.am\/wp-content\/uploads\/2025\/02\/newsFeb2025Quant-150x150.png 150w, https:\/\/imm.am\/wp-content\/uploads\/2025\/02\/newsFeb2025Quant-768x768.png 768w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><br>In a major step toward quantum-aware embedded systems, the R&amp;D team at Incarnet Mathematical Modelling has successfully ported a custom multi-valued logic neural network\u2014based on the recently introduced class F\\mathcal{F}\u2014to a quantum-ready FPGA platform. The implementation excludes majority and choice functions, enabling lower noise sensitivity and faster logic evaluation. This prototype paves the way for efficient signal classification in low-power, latency-sensitive environments, such as IoT and nanosatellite communication systems.<br><strong>Transforming Networks. Connecting the Future.<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In a major step toward quantum-aware embedded systems, the R&amp;D team at Incarnet Mathematical Modelling has successfully ported a custom multi-valued logic neural network\u2014based on the recently introduced class F\\mathcal{F}\u2014to a quantum-ready FPGA platform. The implementation excludes majority and choice functions, enabling lower noise sensitivity and faster logic evaluation. This prototype paves the way for [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":615,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_themeisle_gutenberg_block_has_review":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-613","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"_links":{"self":[{"href":"https:\/\/imm.am\/index.php\/wp-json\/wp\/v2\/posts\/613","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/imm.am\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/imm.am\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/imm.am\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/imm.am\/index.php\/wp-json\/wp\/v2\/comments?post=613"}],"version-history":[{"count":2,"href":"https:\/\/imm.am\/index.php\/wp-json\/wp\/v2\/posts\/613\/revisions"}],"predecessor-version":[{"id":617,"href":"https:\/\/imm.am\/index.php\/wp-json\/wp\/v2\/posts\/613\/revisions\/617"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/imm.am\/index.php\/wp-json\/wp\/v2\/media\/615"}],"wp:attachment":[{"href":"https:\/\/imm.am\/index.php\/wp-json\/wp\/v2\/media?parent=613"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/imm.am\/index.php\/wp-json\/wp\/v2\/categories?post=613"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/imm.am\/index.php\/wp-json\/wp\/v2\/tags?post=613"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}