Taylor expansion for matrix logarithm

In summary, the paper states that for positive hermitian matrices A and B, the Taylor expansion of log(A+tB) at t=0 is given by the formula \log(A+tB)=\log(A) + t\int_0^\infty \frac{1}{B+zI}A \frac{1}{B+zI} dz + \mathcal{O}(t^2). However, a source or proof is not provided and the derivation of this identity is not readily available.
  • #1
Backpacker
9
0
A paper I'm reading states the that: for positive hermitian matrices A and B, the Taylor expansion of [itex]\log(A+tB)[/itex] at t=0 is

[itex]\log(A+tB)=\log(A) + t\int_0^\infty \frac{1}{B+zI}A \frac{1}{B+zI} dz + \mathcal{O}(t^2).[/itex]

However, there is no source or proof given, and I cannot seem to find a derivation of this identity anywhere! Any help would be appreciated. Thanks.
 
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  • #2
Backpacker said:
A paper I'm reading states the that: for positive hermitian matrices A and B, the Taylor expansion of [itex]\log(A+tB)[/itex] at t=0 is

[itex]\log(A+tB)=\log(A) + t\int_0^\infty \frac{1}{B+zI}A \frac{1}{B+zI} dz + \mathcal{O}(t^2).[/itex]

However, there is no source or proof given, and I cannot seem to find a derivation of this identity anywhere! Any help would be appreciated. Thanks.

Welcome to PF, Backpacker! :smile:

I don't recognize your formula, but:

$$\log(A+tB)=\log(A(I+tA^{-1}B)= \log A + \log(I+tA^{-1}B) = \log A + tA^{-1}B + \mathcal{O}(t^2)$$
 
  • #4
I like Serena said:
$$\log(A(I+tA^{-1}B)= \log A + \log(I+tA^{-1}B) $$
This doesn't seem quite right, unless ## A ## and ## B ## commute.
 

Related to Taylor expansion for matrix logarithm

1. What is the purpose of Taylor expansion for matrix logarithm?

The Taylor expansion for matrix logarithm is used to approximate the logarithm of a matrix, which is a valuable tool in many areas of mathematics and science. It allows for easier calculations and analysis of matrix operations.

2. How does Taylor expansion for matrix logarithm work?

Taylor expansion is a mathematical method for approximating a function by expanding it into an infinite series of terms. In the case of matrix logarithm, this involves using the Taylor series expansion to approximate the logarithm of a matrix by adding up a series of terms involving powers of the matrix.

3. What are the benefits of using Taylor expansion for matrix logarithm?

One of the main benefits of using Taylor expansion for matrix logarithm is that it allows for easier computation and analysis of matrix operations. It also provides a way to approximate the logarithm of a matrix even if the exact value cannot be found.

4. Are there any limitations or drawbacks to using Taylor expansion for matrix logarithm?

One limitation of Taylor expansion for matrix logarithm is that it is only an approximation and may not give the exact value of the logarithm of a matrix. Additionally, the series may not converge for certain matrices, leading to inaccurate results.

5. How is Taylor expansion for matrix logarithm used in practical applications?

Taylor expansion for matrix logarithm is used in various areas of mathematics, physics, and engineering. It is commonly used in numerical methods for solving differential equations and in analyzing the stability of dynamical systems. It is also used in machine learning and data analysis to approximate the logarithm of matrices in large datasets.

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