## Lindström–Gessel–Viennot Lemma

Let us switch gears and describe a beautiful combinatorial result. Suppose is a graph which is directed, has no cycles, and there are only finitely many paths from a vertex to another. Given sets of *n* vertices:

the lemma computes the “weighted sum” of non-intersecting paths from to .

To be specific, suppose each edge of the graph has a weight which takes values in a fixed ring. Given a directed path from to let be the product of the edges along the path . Now write for the sum of over all

Next given above, we compute the determinant of:

On the other hand, consider a collection of paths where each for some permutation Furthermore we want the paths to be pairwise non-intersecting, i.e. no two paths contain a common vertex (not even at the endpoints). Now we can state the desired result.

Lindström–Gessel–Viennot (LGV) Lemma. We have:over all tuples of paths described above.

## Proof of the LGV Lemma

First expand the determinant of ; each term is of the form:

Expanding each , the above term is a sum of terms of the form

summed over all *n*-tuples This is close to the desired result but here, the may intersect. Hence, we wish to show that the sum over all for which some and intersect, vanishes.

Let be the collection of all such paths; for each we:

- let be the first vertex occurring as an intersection between and (), after taking a total ordering for the set of vertices;
- let be the smallest index such that contains ;
- let be the largest index such that contains (note that );

and get a triplet Now let be the same tuple of paths but with the tails of and switched after

This gives a map , which is an involution since the corresponding triplet for is still However and have opposite signs. Denoting by we have and so:

So the sum is zero. ♦

## Jacobi-Trudi Identities

Here is our first application of the LGV lemma; all computations are in the formal ring

Theorem. Let be the transpose of . Then is the determinant of either of these matrices.where is chosen to be and in the respective cases.

**Note**

One remembers the structure of the matrices by writing as the subscripts for the diagonal entries, then incrementing to the right. We take for all Observe that since , there is no harm increasing by appending zeros to the partition.

**Proof**

We can obtain the second identity from the first by applying , so let us show the first. Before we begin, observe that the Schur polynomial can be written as:

where Indeed, this follows from the proposition here.

We will use the LGV lemma: let be large; we take the following graph.

- The vertices are lattice points in .
- The starting and ending vertices are given by:

- The edges are of one unit, directed either eastwards or southwards. The southward edges are weighted 1 while the eastward edges on are labelled for

For example if , here is an example of paths connecting

Let us compute the LHS of the LGV lemma. The set of paths from to sums up to the complete symmetric polynomial . Thus the LHS is the desired determinant expression.

On the other hand, let us consider the collection of non-intersecting paths from to . For a path to exist, must be the identity. Each collection of non-intersecting paths corresponds to a *reverse* SSYT of shape (i.e. the rows are weakly decreasing and columns are strictly decreasing). E.g. the above diagram gives:

Hence, the RHS in the LGV lemma equals the sum of over all reverse SSYT of shape This is equal to the sum over all SSYT of shape (we take to be the minimum and maximum elements of the table respectively and replace each with thus obtaining an SSYT). Thus the sum is ♦