hook length formula
Tags: #theorem
Statement
Let
As notation, let
This was proven by Frame-Robinson-Thrall in 1953.
Proof
We give the "Hook walk" proof by Greene-Nijenhuis-Wilf (1979). The intuition is as follows:
There is a recurrence relationship that
Where a corner box is defined to be the boxes with hook length 1 (ie. there are no boxes below or to the right of it). We note that the largest number of the tableaux must be in a corner box. If the largest number is in some corner box
It then suffices to show that the RHS also satisfies the recurrence relation. In other words, we need to show
which is equivalent to showing that
We shall do so by viewing this as a probability measure. In particular, we want to show that
Consider the random process (which we shall call a Hook walk):
- Randomly select a box
(so each box has a probability of of being selected) - Repeat for
: starting from , pick in the hook of (that is not ) - Note that the above process terminates once we reach a corner box
. Output this .
Example:

We want to ask about the probability that this hook walk ends at some corner
where we take the sum over all hook walks that end at
First, we note that any hook walk that ends at

For any box
Furthermore, let the cohook be the boxes that are above and to the left of a box. Note that
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We further note that
The second line obtained by subtracting one from both sides and noticing that
Let
This in particular means that the weight of any box is
Here is a simple example of the weight of a path:

Lemma: Define a lattice path to be a Hook walk that is connected. We claim that
We proof via induction on
Now we can apply this lemma to prove the same formula for a general hook walk:
For every box, we mark down the rows and columns that it occupies. This creates a subgrid, and within this subgrid, we have a lattice path. We may then apply the lemma to get
So in general, we have the formula for the probability that a hook walk will end at
We claim that this is equal to
Thus, we have shown that the quantity is a probability measure, and so if we take the sum over all possible corners, we must get 1.