Veritasium
July 14, 2026
TL;DR
The Smith Chart, developed in 1937 by Phillip Smith, is a revolutionary graphical tool that solves the impedance matching problem in electrical engineering by mapping complex impedance values onto a finite circular chart using conformal geometry, enabling engineers to minimize signal reflections in transmission lines.
“It's like terrifying. It looks almost like a wormhole in some sci-fi movie.”
— Interviewee
“So much of scientific progress comes not from new discoveries, but from new forms of representation. They make hard problems easier to solve and make further innovation and discovery possible.”
— Veritasium host
“The Smith chart encodes that intuition. And because of that, it's still a popular visualization tool in modern software.”
— Veritasium host
“We stopped every reflection on this line with just a break in the circuit. A dangling piece of cable connected to nothing trimmed to the right length.”
— Veritasium host
1. The Problem: Signal Reflections in Radio Transmission
Phillip Smith at Bell Labs in the 1920s faced the challenge of transmitting radio signals across continents. When signals travel down transmission lines, they reflect at boundaries where impedance mismatches occur, losing power and creating dangerous standing wave patterns. This reflection problem is central to understanding why the Smith Chart was needed.
2. Understanding AC Waves and Impedance
Unlike DC circuits, radio frequency systems use alternating current with sinusoidal voltage and current waves. The speed, frequency, and wavelength of these waves interact with transmission line properties. The key insight is that impedance—the ratio of voltage to current—varies along a mismatched line due to reflected waves interfering with forward waves.
3. Complex Numbers and Impedance Representation
Real electrical systems involve resistance (real axis) and reactance from capacitance and inductance (imaginary axis). Impedance combines both into complex numbers, with magnitude determining voltage-current ratio and phase angle showing the timing shift between them. This two-dimensional representation is essential for the Smith Chart.
4. The Conformal Transformation Magic
Smith realized that using the reflection coefficient (ratio of reflected to forward waves) instead of impedance creates a bounded problem. By applying a conformal mathematical transformation, he warped the infinite impedance plane into a finite circle where impedance values map to specific points. This transformation preserves angles and shapes at small scales while compressing infinity into the chart's center.
5. Reading and Using the Smith Chart
The Smith Chart displays two families of circles: constant-resistance circles (getting smaller as resistance increases) and constant-reactance circles (arcing above and below the horizontal axis). Any impedance can be found at the intersection of its resistance and reactance circles. The distance from center indicates reflection coefficient magnitude.
6. Practical Impedance Matching with Transmission Line Stubs
To eliminate reflections, impedance must be matched to the characteristic impedance of the transmission line (typically 50 ohms). Engineers use the Smith Chart to find the nearest point with desired resistance, then add transmission line stubs (branches of cable with open or short circuits) cut to specific lengths that provide the needed reactance cancellation.
7. Historical Development and Adoption
Independently developed by Phillip Smith (Bell Labs, USA), Tosaku Mizuhashi (Japan), and Amiel Volpert (Soviet Union) in 1937-1939, the Smith Chart initially faced slow adoption. World War II accelerated its use when radar engineers needed reliable impedance matching tools. Post-war, Smith's version became dominant through academic and industry adoption.
8. Modern Applications and Legacy
While computers now handle calculations, the Smith Chart remains essential in RF engineering education and practice. It provides intuitive visualization of impedance matching problems and is embedded in virtually all modern RF measurement software. The chart exemplifies how new mathematical representations can unlock solutions to previously difficult problems.