<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Notes on XLOPTIX</title><link>https://www.xloptix.com/blog/notes/</link><description>Recent content in Notes on XLOPTIX</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sun, 18 Oct 2026 08:21:01 -0700</lastBuildDate><atom:link href="https://www.xloptix.com/blog/notes/index.xml" rel="self" type="application/rss+xml"/><item><title>A Glass Galaxy</title><link>https://www.xloptix.com/blog/2026/10/18/a-glass-galaxy/</link><pubDate>Sun, 18 Oct 2026 08:21:01 -0700</pubDate><guid>https://www.xloptix.com/blog/2026/10/18/a-glass-galaxy/</guid><description>&lt;p>Recently, a project led me down an interesting path. I applied linear Principal Component Analysis (PCA) to the index profiles of glasses in the SCHOTT glass catalog at 20°C. The Sellmeier dispersion equation for these glasses has six parameters, and accordingly, there were six principal components. However, the first three principal components captured most of the index-variation information. This, along with the fact that I cannot visualize more than three dimensions, led me to focus on the first three principal components for this visualization.&lt;/p></description></item></channel></rss>