Proving e^Ae^B=e^{A+B} for Commuting Matrices

In summary, if A and B are two matrices that do not commute, then e^{A+B} does not equal e^Ae^B, but if they do commute, then the relation holds. This can be shown through series expansion by observing the additional term [A,B] that appears when A and B do not commute.
  • #1
kreil
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Homework Statement


Show, by series expansion, that if A and B are two matrices which do not commute, then [itex]e^{A+B} \ne e^Ae^B[/itex], but if they do commute then the relation holds.


Homework Equations


[tex]e^A=1+A[/tex]
[tex]e^B=1+B[/tex]
[tex]e^{A+B}=1+(A+B)[/tex]


The Attempt at a Solution


Assuming that the first 2 terms in the expansion is sufficient to use here (is it?), I got the following:

[tex]e^Ae^B=(1+A)(1+B)=1+A+B+AB[/tex]

This would be equal if the AB term were not tacked on the end...does this term somehow become zero when the two matrices commute? If I'm on the wrong track please let me know.

Josh
 
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  • #2
I think I figured it out after a little thought...

[tex]e^Ae^B=(1+A)(1+B)=1+A+B+AB-BA=1+A+B+[A,B][/tex]

So if A and B commute, [A,B]=0 and the relation holds, else [A,B] does not equal zero and [itex]e^{A+B} \ne e^Ae^B[/itex]
 
  • #3
ua,

The statement you are trying to prove is a well-known property of commuting matrices. It states that if A and B are two matrices that commute, meaning AB=BA, then the exponential of their sum is equal to the product of their exponentials. In other words, e^Ae^B=e^{A+B}. This can be easily shown using the definition of the exponential function for matrices, which is usually given as a power series:

e^X=I+X+X^2/2!+X^3/3!+...

Where I is the identity matrix. Using this definition, we can expand the left-hand side of the equation e^Ae^B and get:

e^Ae^B=(I+A+A^2/2!+...)(I+B+B^2/2!+...)

Multiplying this out, we get:

e^Ae^B=I+(A+B)+(A^2+B^2+A*B)/2!+...

We can see that the terms involving A and B are grouped together and all the terms involving their products are divided by the same factorial. This is because A and B commute, so their products will also commute and can be combined. This is not the case when A and B do not commute, as you can see by expanding e^{A+B} using the same method.

So to answer your question, the AB term does not become zero when A and B commute, but it can be combined with other terms to give the desired result. This property of commuting matrices is important in many areas of mathematics, including linear algebra and differential equations. It allows us to simplify calculations and make certain problems easier to solve.
 

Related to Proving e^Ae^B=e^{A+B} for Commuting Matrices

1. How do you define "commuting matrices" in this context?

In linear algebra, two matrices A and B are considered commuting if their product AB is equal to their product BA. In other words, the order in which the matrices are multiplied does not affect the result.

2. What is the significance of proving e^Ae^B=e^{A+B} for commuting matrices?

This proof is important because it allows us to simplify the calculation of exponential functions involving commuting matrices. It also has applications in various fields such as quantum mechanics and differential equations.

3. Can you briefly explain the concept of matrix exponentiation?

Matrix exponentiation is the process of raising a matrix to a power. It is similar to raising a number to a power, except that in this case, the "number" is a matrix and the operation is defined differently. In general, the exponential of a matrix A is defined as the infinite power series: e^A = I + A + (A^2)/2! + (A^3)/3! + ...

4. What are some examples of commuting matrices?

Some examples of commuting matrices are diagonal matrices, symmetric matrices, and matrices with all zero entries except for the main diagonal. Additionally, any two matrices that share a common eigenvector will also commute.

5. Is the proof of e^Ae^B=e^{A+B} applicable to non-commuting matrices?

No, this proof is only applicable to commuting matrices. In fact, the equation e^Ae^B=e^{A+B} is not true for non-commuting matrices in general. However, there are some special cases where it may hold, such as when A and B share a common eigenvector or when they are 2x2 matrices with certain properties.

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