Inverse of diagonal dominant matrices

In summary, the conversation discusses how to show that ##n \times n## complex matrices, satisfying the condition ##\forall 1 \le i \le n, \sum_{k \neq i} |a_{ik}| < |a_{ii}|##, are invertible. The approach is to prove that the column vectors are linearly independent, which would imply that the matrix has rank ##n## and is invertible. This is done by considering complex coefficients ##\lambda_1, ..., \lambda_n## and showing that they must all be equal to zero, thus proving the linear independence of the column vectors. Overall, the proof is concise and to the point, leaving no room for further
  • #1
geoffrey159
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Homework Statement


Show that ##n\times n ## complex matrices such that ##\forall 1\le i \le n,\quad \sum_{k\neq i} |a_{ik}| < |a_{ii}|##, are invertible

Homework Equations

The Attempt at a Solution



If I show that the column vectors are linearly independent, then the matrix has rank ##n## and is invertible.

Let ##\lambda_1, ..., \lambda_n## be complex coefficients such that ##\sum_{k = 1}^n \lambda_k a_{ik} = 0## for all ##1 \le i \le n##. There must be ##\lambda_i## such that ## |\lambda_j| \le |\lambda_i| ## for all ##j\neq i##. If ##\lambda_i \neq 0##, then ## |a_{ii} | = \frac{1}{|\lambda_i|} | \sum_{k\neq i} \lambda_k a_{ik} | \le \frac{|\lambda_i|}{|\lambda_i|} \sum_{k\neq i} |a_{ik}| < |a_{ii}|##
This is absurd so ##\lambda_i = 0## and all the other lambda's are zero because ##\lambda_i## dominates in module all the other lambda's. So the column vectors are linearly independant.

Is it Ok ?
 
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  • #2
Yes, your proof is concise and to the point - nothing to add.
 
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  • #3
Thank you
 

FAQ: Inverse of diagonal dominant matrices

1. What is the definition of an inverse of a diagonal dominant matrix?

An inverse of a diagonal dominant matrix is a matrix that when multiplied by the original diagonal dominant matrix results in an identity matrix. In other words, the inverse undoes the effects of the original matrix.

2. How do you determine if a matrix is diagonal dominant?

A matrix is diagonal dominant if the absolute value of each element on the main diagonal is greater than the sum of the absolute values of the other elements in the same row. In other words, the diagonal elements must be larger than the sum of the non-diagonal elements in the same row.

3. Can a matrix be both diagonal dominant and singular?

Yes, a matrix can be both diagonal dominant and singular. A matrix is considered singular if its determinant is equal to 0. Diagonal dominance only looks at the magnitude of the elements, not their values. So, it is possible for a matrix to have dominant diagonal elements but still have a determinant of 0.

4. What are the applications of inverse of diagonal dominant matrices?

The inverse of diagonal dominant matrices has various applications in fields such as engineering, physics, and economics. It is commonly used to solve systems of linear equations, which are prevalent in these fields. It is also used in numerical analysis and optimization problems.

5. Is the inverse of a diagonal dominant matrix always unique?

No, the inverse of a diagonal dominant matrix is not always unique. This is because there can be multiple diagonal dominant matrices with the same inverse. However, if a matrix is both diagonal dominant and symmetric, then its inverse is unique.

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