<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Physics on Dmitry Serikov</title><link>https://dmitryserikoff.com/tags/physics/</link><description>Recent content in Physics on Dmitry Serikov</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Wed, 03 Jun 2026 00:00:00 +0300</lastBuildDate><atom:link href="https://dmitryserikoff.com/tags/physics/index.xml" rel="self" type="application/rss+xml"/><item><title>Want to Try Theoretical Physics This Evening? I Built a Python Framework for That</title><link>https://dmitryserikoff.com/posts/want-to-try-theoretical-physics-this-evening/</link><pubDate>Wed, 03 Jun 2026 00:00:00 +0300</pubDate><guid>https://dmitryserikoff.com/posts/want-to-try-theoretical-physics-this-evening/</guid><description>&lt;p>Theoretical physics has a brutal cost of entry: years of prerequisites before
you get to touch anything real. I wanted to lower that first step — not the
science, just the step. So I built &lt;strong>SFT&lt;/strong> (Spectral Flow Transform), a Python
framework that treats complex systems through their spectral fingerprints:
frequencies in audio, energy levels in physical systems, modes in simulations.&lt;/p>
&lt;p>Three things it does well: predict how a spectrum shifts when parameters
change, solve the inverse problem — find parameters that produce a spectral
shape you want — and measure how complex a system actually is via spectral
rank.&lt;/p></description></item></channel></rss>