Michael Simkin, a genius cum postdoctoral fellow at the Center of Mathematical Sciences and Applications has presented the solution of a long-awaited query. It’s all about the queen! (In the game of chess). Simkin has been trying to resolve the n-queens problem for almost five years. The Harvard- pro is a real chess freak, striving to improve his game.

The n-queens issue enquires: how many arrangements are possible where the queens are far enough apart so none of them can take any of the others With a certain number of queens (n)? The question, in fact, has challenged the players since the 1840s.

In July 2021, the Mathematician from Harvard University in Massachusetts calculated that there are about (0.143n)n ways the queens can be placed so none are attacking each other on the n-by-n chessboard.

Although Simkin’s equation does not deliver the exact answer to the challenge, it is yet the closest figure to the actual number. The digits 0.143 represent an average of uncertainty in the variable’s possible outcome. The figure is multiplied by the value of n and then raised to the power of n to get the answer.

This calculated equation is helpful when the game is played on an extremely large chessboard with one million queens. Here, 0.143 would be multiplied by one million and the answer is 143,000. The figure would be raised to the power of one million, meaning 143,000 is multiplied by itself one million times. The final answer would give you a figure with five million digits.

The statistician observed the arrangement that how large numbers of queens would be distributed on the massive chessboards. He perceived their positions as well as concentrations in the middle or on the edges. The mastermind then applied his mathematical concepts and algorithms to rule out the final equation.

Simkin commented, “If you were to tell me I want you to put your queens in a such-and-such way on the board, then I would be able to analyze the algorithm and tell you how many solutions there are that match this constraint, In formal terms, it reduces the problem to an optimization problem”.