<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Mathematical Proof on Lynx Tech Blog</title><link>https://blog.lynxflow.co/en/tags/mathematical-proof/</link><description>Recent content in Mathematical Proof on Lynx Tech Blog</description><generator>Hugo -- gohugo.io</generator><language>en</language><lastBuildDate>Sun, 09 Aug 2026 00:00:00 +0800</lastBuildDate><atom:link href="https://blog.lynxflow.co/en/tags/mathematical-proof/index.xml" rel="self" type="application/rss+xml"/><item><title>AI Solves a 25-Year-Old Open Mathematical Problem in Communications</title><link>https://blog.lynxflow.co/en/posts/ai-cracks-25-year-mimo-detection-problem/</link><pubDate>Sun, 09 Aug 2026 00:00:00 +0800</pubDate><guid>https://blog.lynxflow.co/en/posts/ai-cracks-25-year-mimo-detection-problem/</guid><description>&lt;img src="https://blog.lynxflow.co/images/ai-cracks-25-year-mimo-detection-problem.png" alt="Featured image of post AI Solves a 25-Year-Old Open Mathematical Problem in Communications" /&gt;A Problem That Had Been Stuck for 25 Years Was Solved by AI in a Week There is a classic hard problem in wireless communications called MIMO detection: the transmitter packs N bits into an N×N channel and sends them out; the signal gets scrambled and mixed with noise along the way, and the receiver has to recover the original bits exactly.
In theory, there is a brute-force approach: enumerate all 2^N possible bit combinations and find the one that best matches. But once N gets even moderately la</description></item></channel></rss>