GoKawiilBlog post walks through Monte Carlo estimation of pi using dart-throw simulation
A technical blog post explains Monte Carlo simulation methods, tracing the technique's origins to Stanislaw Ulam and John von Neumann's nuclear weapon calculations after World War II. It demonstrates the approach with a classic example: estimating pi by randomly 'throwing darts' at a square containing an inscribed quarter circle and comparing the ratio of hits inside the circle to total throws. The author notes that even with 1,000 samples the estimate remains imprecise, suggesting roughly 10 billion samples are needed for accuracy.