Do Commuting Linear Operators A and B Satisfy the Exponential Property?

In summary, for the equation e^A*e^B=e^(A+B) to be true, A and B must commute (AB=BA). It is also necessary for A and B to be the same size and square in order for A+B to exist and have eigenvectors and values. However, it is unclear if A and B being the same size and square is also necessary for the equation to hold true.
  • #1
frederick
2
0
If A & B are linear operators, and AY=aY & BY=bY, what is the relationship between A & B such that e^A*e^B=e^(A+B)?? --where e^x=1+x+x^2/2+x^3/3!+...+x^n/n!
 
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  • #2
e^A e^B = e^(A+B) is true when A and B commute (AB=BA). Or are you asking when e^A e^B Y=e^(A+B) Y, where Y is an eigenvector of A and B? That is always true.
 
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  • #3
e^A*e^B=e^(A+B)??

A and B commute is sufficient - I don't know if it's necessary.
 
  • #4
I'm not quite sure what the question is asking here...

I definitely did pick up that A and B must be the same size for A+B to exist (and must be square to have eigenvectors and values). Also, you need AB=BA (I think?). Someone else should verify this
 

Related to Do Commuting Linear Operators A and B Satisfy the Exponential Property?

1. What are linear operators?

Linear operators are mathematical functions that operate on vectors to produce new vectors. They are used to represent transformations in mathematics and physics, and are important in the study of linear algebra.

2. What are eigenvalues?

Eigenvalues are special numbers associated with linear operators. They represent the scaling factor by which a vector is multiplied when it is transformed by the operator. They are also used to determine the behavior of a system under the influence of the operator.

3. How do you find eigenvalues?

To find eigenvalues, you need to solve the characteristic equation of the linear operator. This equation is formed by setting the determinant of the operator's matrix representation equal to 0. The solutions to this equation are the eigenvalues of the operator.

4. Why are eigenvalues important?

Eigenvalues are important because they provide insight into the behavior of systems and operators. They can be used to determine stability, convergence, and other properties of a system. They also play a crucial role in many applications of linear algebra, such as in quantum mechanics and signal processing.

5. How are eigenvalues used in data analysis?

In data analysis, eigenvalues are used to reduce the dimensionality of data while retaining the most important information. This is done through techniques such as principal component analysis, where the eigenvalues are used to determine the most significant features of the data. Eigenvalues are also used in clustering and classification algorithms to identify patterns and relationships in data.

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