Logarithm of 2x2 Matrix: A General Guide

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SUMMARY

The discussion focuses on calculating the logarithm of a 2x2 matrix with non-zero entries. Two primary methods are highlighted: diagonalization using eigen-decomposition and operator expansion via the Taylor series of the logarithm. For diagonalizable matrices, the logarithm can be computed through the exponential of a diagonal matrix, while non-diagonalizable matrices require the Jordan Normal Form for more complex calculations. The discussion emphasizes the relationship between logarithmic and exponential functions in matrix operations.

PREREQUISITES
  • Understanding of eigen-decomposition in linear algebra
  • Familiarity with Taylor series expansions
  • Knowledge of Jordan Normal Form for matrices
  • Basic concepts of matrix exponentiation
NEXT STEPS
  • Study the process of diagonalizing matrices in linear algebra
  • Learn about Taylor series and their applications in matrix functions
  • Research Jordan Normal Form and its significance in matrix theory
  • Explore matrix exponentiation techniques and their computational implications
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Mathematicians, students of linear algebra, and anyone involved in advanced matrix computations will benefit from this discussion.

jhendren
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How do you take the log of a 2x2 matrix in general where all entries are non-zero
 
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jhendren said:
How do you take the log of a 2x2 matrix in general where all entries are non-zero

Hey jhendren and welcome to the forums.

Have you tried either (a) diagonalizing the matrix or (b) using an operator expansion based on the Taylor series of the logarithm?

The first one is based on the eigen-decomposition and the second one is based on the operator algebra results for functions of a linear operator.
 
If y= ln(x) then x= e^y. So to define the logarithm is to define the exponential and vice-versa. And it is easier to work with the exponential. Its Taylor series is \sum_{n=0}^\infty x^n/n!.

One can show that if matrix x is "diagonalizable", that is, if there exist a matrix P such that x= PDP^{-1} where D is a diagonal matrix, then that is \sum_{n= 0}^\infty (PDP^{-1})^n/n!= P\left(\sum_{n=0}^\infty D^n\right)P^{-1}. And D^n is just the diagonal matrix with the nth powers of the diagonal elements of D on it diagonal. That reduces to e^x= Pe^DP^{-1} where, now, e^D is the diagonal matrix having the exponentials of the diagonal elements of D on its diagonal.

If x is not diagonalizable, it can still be written in "Jordan Normal Form" but the exponential of that is trickier.

If, for example,
D= \begin{bmatrix}a & 0 \\ 0 & b\end{bmatrix}
then
e^D= \begin{bmatrix}e^a & 0 \\ 0 & e^b\end{bmatrix}.

If A is the "Jordan Normal Form", written as
A= \begin{bmatrix}a & 1 \\ 0 & a\end{bmatrix}
then it is easy to show that
A^n= \begin{bmatrix}a^n & na^{n-1} & 0 & a^n\end{bmatrix}
so that
e^A= \begin{bmatrix}\sum a^n/n! & sum na^{n-1}/n!\\ 0 \sum a^n/n!\end{bmatrix}= \begin{bmatrix}\sum a^n/n! & sum a^{n-1}{n!} \\ 0 & a^n/n! \end{bmatrix}
e^A= \begin{bmatrix}e^a & e^a \\ 0 & e^a\end{bmatrix}
 
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