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Buffon's needle problem to estimate pi, explained 

Dr. Bevin Maultsby
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In this video, we explore Buffon's Needle problem, a fun exercise that blends probability, geometry, and calculus. Our focus is on estimating the value of pi using the concept of the average value of a function. We begin by explaining the problem, initially posed by Georges-Louis Leclerc, Comte de Buffon, which involves dropping needles onto a floor marked with parallel lines and determining the probability that a needle will cross one of the lines. This probability, as we demonstrate, is linked to the value of pi.
We simplify the experiment by considering all needles as if they fell between a single pair of lines, reducing our problem's complexity. We then introduce a unique approach by "throwing" the lines at a stationary needle rather than the traditional method of dropping needles. This simplification allows us to focus solely on the needle's rotation angle, eliminating the need to consider its vertical position.
Our calculation begins with the assumption that the needle's length L is less than or equal to the distance between the lines D, leading us to express the probability of a line crossing the needle in terms of L, D, and the sine of the needle's angle to the horizontal (angle theta). We calculate the average value of this probability function across all possible angles, utilizing basic single variable calculus.
We extend our discussion to a second case where the needle's length exceeds the distance between the lines to create a piecewise-defined probability function.
We illustrate our theoretical findings with MATLAB simulations, showcasing how these experiments can approximate pi.
#mathematics #math #Probability #Calculus #Geometry #piapproximation #matlabsimulation

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5 сен 2024

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Комментарии : 3   
@thomashowe1920
@thomashowe1920 6 месяцев назад
I very much appreciate your explanations of how the simplifications you made don’t change the experiment. It took a bit to work through that. If you were to run your Matlab simulation many times, would it be your expectation that the average of those samples would approach pi? Possibly with a variance related to the number of “throws” in the individual simulations?
@bevinmaultsby
@bevinmaultsby 6 месяцев назад
Hi Thomas, I'm glad you appreciated it. Basically: the answer to both questions is yes. If I ran a Matlab simulation of Buffon's Needle Problem multiple times, I would expect the average result to get closer to π. The more "throws" you include in each simulation, the more accurate the average would be, thanks to the law of large numbers. Also, a higher number of throws would reduce the variance, meaning the estimates will not only get closer to π but will also be more consistent. The convergence is very slow though. I just ran the simulation (with L=D/2) 2000 times, and it wasn't until about 1000 needles were thrown that the numbers were showing an estimate consistently close to pi. (The end result was pretty good: 638 crossings for an estimate of about 3.13.) The convergence is also not monotone--it can get worse for awhile before it gets better.
@thomashowe1920
@thomashowe1920 6 месяцев назад
Thank you for the time you spent on that informative reply.
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