Ο€ β‰ˆ -
Mathematical simulation

Two ways to find Ο€

An ancient geometric secret meets a modern probabilistic gamble. Choose your method and watch a constant reveal itself.

Polygon β†’ Cone
n-gon base area β†’ Ο€ as n β†’ ∞
Archimedes, 250 BCE
Current sides
3
polygon
Ο€ estimate
-
error: -
Error
-
n = 3
Sides (n) 3
Animation
Volume of pyramid = (1/3) Γ— base_area Γ— height
base_area(n) = n Β· rΒ² Β· sin(2Ο€/n) / 2 ← n-gon, r=1
As n β†’ ∞: base_area β†’ Ο€
Convergence Table
base area per number of sides
showing 3 β†’ 200
adjust the slider to begin
Shape Sides Base area (β‰ˆ Ο€) Error |Δπ|
Why does this give Ο€?
The n-gon base has area nΒ·sin(2Ο€/n)/2. As nβ†’βˆž,
sin(2Ο€/n) β†’ 2Ο€/n, so area β†’ n Β· (2Ο€/n) / 2 = Ο€.
The Dart Board
unit circle inscribed in 2Γ—2 square
Monte Carlo
Ο€ estimate
-
Darts thrown
0
Inside circle
0
ratio: -
0 darts
Speed
P(inside circle) = π·rΒ² / (2r)Β² = Ο€/4
Estimate: Ο€ β‰ˆ 4 Γ— (inside / total)
Converges as O(1/√n) - slow but elegant
Ο€ Convergence
estimate over time
waiting
throw some darts to begin
Best estimate
-
at - darts
Error
-
Why is Monte Carlo slow?
Error ∝ 1/√n - to gain 1 decimal place,
you need 100Γ— more darts. But it needs
no geometry - just randomness.