<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:dc="http://purl.org/dc/elements/1.1/">
  <channel>
    <title>DEV Community: Biswajyoti Nath</title>
    <description>The latest articles on DEV Community by Biswajyoti Nath (@biswajyotinath).</description>
    <link>https://dev.to/biswajyotinath</link>
    <image>
      <url>https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3909748%2F55ab4b47-a693-43ac-a362-7477af5789f3.jpeg</url>
      <title>DEV Community: Biswajyoti Nath</title>
      <link>https://dev.to/biswajyotinath</link>
    </image>
    <atom:link rel="self" type="application/rss+xml" href="https://dev.to/feed/biswajyotinath"/>
    <language>en</language>
    <item>
      <title>What Happens When You Force All Math Through One Operator?</title>
      <dc:creator>Biswajyoti Nath</dc:creator>
      <pubDate>Sun, 03 May 2026 01:56:25 +0000</pubDate>
      <link>https://dev.to/biswajyotinath/what-happens-when-you-force-all-math-through-one-operator-4poj</link>
      <guid>https://dev.to/biswajyotinath/what-happens-when-you-force-all-math-through-one-operator-4poj</guid>
      <description>&lt;p&gt;Most symbolic systems rely on multiple primitives.&lt;/p&gt;

&lt;p&gt;Addition, multiplication, exponentials, logarithms — each plays a different role in structuring expressions.&lt;/p&gt;

&lt;p&gt;But what happens if you force everything through a single operator?&lt;/p&gt;

&lt;p&gt;This idea becomes concrete with the EML operator:&lt;/p&gt;

&lt;p&gt;eml(x, y) = exp(x) − ln(y)&lt;/p&gt;

&lt;p&gt;In theory, this operator can express all elementary functions.&lt;/p&gt;

&lt;p&gt;But theory doesn’t tell us what happens in practice.&lt;/p&gt;




&lt;h2&gt;
  
  
  The Experiment
&lt;/h2&gt;

&lt;p&gt;I built a small Python framework to explore this idea.&lt;/p&gt;

&lt;p&gt;Instead of chasing universality, the focus is on structure:&lt;br&gt;
What changes when symbolic expressions are forced into a single nonlinear primitive?&lt;/p&gt;

&lt;p&gt;The framework:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;rewrites SymPy expressions into EML trees
&lt;/li&gt;
&lt;li&gt;evaluates them back into standard form
&lt;/li&gt;
&lt;li&gt;measures structural complexity (depth, node count, nonlinear nodes)
&lt;/li&gt;
&lt;li&gt;includes a simple symbolic regression experiment
&lt;/li&gt;
&lt;/ul&gt;




&lt;h2&gt;
  
  
  What Actually Changes?
&lt;/h2&gt;

&lt;p&gt;A few things become immediately obvious:&lt;/p&gt;

&lt;p&gt;• expression trees become significantly deeper&lt;br&gt;&lt;br&gt;
• nonlinear structure increases due to repeated exp/log composition&lt;br&gt;&lt;br&gt;
• domain constraints (like log positivity) become unavoidable  &lt;/p&gt;

&lt;p&gt;So while the representation becomes more uniform, it introduces clear structural overhead.&lt;/p&gt;




&lt;h2&gt;
  
  
  The Key Insight
&lt;/h2&gt;

&lt;p&gt;Same math. Different structure.&lt;/p&gt;

&lt;p&gt;The interesting part isn’t whether one operator can represent everything.&lt;/p&gt;

&lt;p&gt;It’s what that does to the structure of computation.&lt;/p&gt;




&lt;h2&gt;
  
  
  Code + Experiments
&lt;/h2&gt;

&lt;p&gt;GitHub repo:&lt;br&gt;
&lt;a href="https://github.com/biswajyoti-nath/eml-framework" rel="noopener noreferrer"&gt;github.com/biswajyoti-nath/eml-framework&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;Includes:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;transformation system
&lt;/li&gt;
&lt;li&gt;experiments
&lt;/li&gt;
&lt;li&gt;figures
&lt;/li&gt;
&lt;li&gt;paper
&lt;/li&gt;
&lt;/ul&gt;




&lt;h2&gt;
  
  
  Closing Thought
&lt;/h2&gt;

&lt;p&gt;This isn’t about replacing standard algebra.&lt;/p&gt;

&lt;p&gt;It’s about understanding how representation shapes computation.&lt;/p&gt;

&lt;p&gt;Curious how others think about this — especially what happens at larger tree depths.&lt;/p&gt;

</description>
      <category>python</category>
      <category>opensource</category>
      <category>computerscience</category>
      <category>machinelearning</category>
    </item>
  </channel>
</rss>
