# A story of balls, randomness and PDEs

## TL;DR

This paper introduces a novel PDE-based method to solve complex probability problems involving balls and random removals, providing explicit formulas and demonstrating the approach's versatility over traditional inductive solutions.

## Contribution

It presents a systematic PDE approach to derive probability distributions in a complex ball removal problem, offering a new algorithmic and analytical framework.

## Key findings

- Derived explicit probability formulas for remaining balls.
- Solved the problem using a PDE approach with boundary conditions.
- Validated the method by reproducing known results.

## Abstract

Several differential equations usually appearing in mathematical physics are solved through a power series expansion, which reduces in solving difference equations. In this paper a probability problem is presented whose solution follows a completely reversed but systematic approach. Hence, this work is about illustrating how complex probability problems could be tackled with the more powerful techniques of a better studied and well understood field, that of differential equations. The problem is defined as follows: Inside a box containing r red and w white balls random removals occur. The balls are removed successively according to the three following rules. Rule I: If a white ball is chosen it is immediately discarded. If a red ball is chosen, it is placed back into the box and a new ball is randomly chosen. The second ball is then removed irrespective of the color. Rule II: Once one ball is removed, the game continues from Rule I. Rule III: The game ends once all the red balls are removed. The question posed is the determination of the probability that k white balls remain where k = 0, 1, 2, ..., w. Ending the game once all the white balls are removed, a second question is the determination of the probability that k red balls remain where k = 0, 1, 2, ..., r. While inductive solutions are possible, the current approach demonstrates a different and algorithmic route. In particular, the law of total probability yields a recursion that is transformed into a linear inhomogeneous 2D PDE, with suitable boundary conditions. The PDE solutions, which are found analytically, provide the generating functionals of the required probabilities as a function of r, w and k. Using the functionals, the probability formulas for any r, w and k are finally obtained in a closed form. Reproducing existing results of the literature this method is quite generic and adaptable to a large class of problems.