Jacobi's formula


In matrix calculus, Jacobi's formula expresses the derivative of the determinant of a matrix A in terms of the adjugate of A and the derivative of A.
If is a differentiable map from the real numbers to matrices,
where is the trace of the matrix.
As a special case,
Equivalently, if stands for the differential of, the general formula is
It is named after the mathematician Carl Gustav Jacob Jacobi.

Derivation

Via Matrix Computation

We first prove a preliminary lemma:
Lemma. Let A and B be a pair of square matrices of the same dimension n. Then
Proof. The product AB of the pair of matrices has components
Replacing the matrix A by its transpose AT is equivalent to permuting the indices of its components:
The result follows by taking the trace of both sides:
Theorem. For any differentiable map A from the real numbers to n × n matrices,
Proof. Laplace's formula for the determinant of a matrix A can be stated as
Notice that the summation is performed over some arbitrary row i of the matrix.
The determinant of A can be considered to be a function of the elements of A:
so that, by the chain rule, its differential is
This summation is performed over all n×n elements of the matrix.
To find ∂F/∂Aij consider that on the right hand side of Laplace's formula, the index i can be chosen at will.. In particular, it can be chosen to match the first index of ∂ / ∂Aij:
Thus, by the product rule,
Now, if an element of a matrix Aij and a cofactor adjTik of element Aik lie on the same row, then the cofactor will not be a function of Aij, because the cofactor of Aik is expressed in terms of elements not in its own row. Thus,
so
All the elements of A are independent of each other, i.e.
where δ is the Kronecker delta, so
Therefore,
and applying the Lemma yields

Via Chain Rule

Lemma 1., where is the differential of.
This equation means that the differential of, evaluated at the identity matrix, is equal to the trace. The differential is a linear operator that maps an n × n matrix to a real number.
Proof. Using the definition of a directional derivative together with one of its basic properties for differentiable functions, we have
is a polynomial in of order n. It is closely related to the characteristic polynomial of. The constant term is 1, while the linear term in is.
Lemma 2. For an invertible matrix A, we have:.
Proof. Consider the following function of X:
We calculate the differential of and evaluate it at using Lemma 1, the equation above, and the chain rule:
Theorem.
Proof. If is invertible, by Lemma 2, with
using the equation relating the adjugate of to. Now, the formula holds for all matrices, since the set of invertible linear matrices is dense in the space of matrices.

Corollary

The following is a useful relation connecting the trace to the determinant of the associated matrix exponential:
This statement is clear for diagonal matrices, and a proof of the general claim follows.
For any invertible matrix, in the previous section [|"Via Chain Rule"], we showed that
Considering in this equation yields:
The desired result follows as the solution to this ordinary differential equation.

Applications

Several forms of the formula underlie the Faddeev–LeVerrier algorithm for computing the characteristic polynomial, and explicit applications of the Cayley–Hamilton theorem. For example, starting from the following equation, which was proved above:
and using, we get:
where adj denotes the adjugate matrix.

Remarks