Proof of det(kA)=k^n det(A) for all n and k

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In summary, the determinant of kA is the product of all the eigenvalues of the matrix kA, representing the scaling factor of the matrix. This is related to det(A) by a simple formula where det(kA) is equal to k raised to the power of the matrix's dimension multiplied by det(A). The proof of this relationship is applicable to all square matrices with a constant scaling factor. It can also be extended to matrices with complex numbers, as long as they follow the same rules as real numbers. This proof has practical applications in solving linear equations, calculating areas and volumes, and determining matrix invertibility. It is also used in various scientific and engineering fields such as quantum mechanics, circuit analysis, and computer graphics.
  • #1
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why is det(kA)=k^ndet(A)?
[show that it is true for all n and all k]
 
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  • #2
Well, what do you know about determinants? What thoughts have you already had on this problem?
 
  • #3
As Hurkly suggested, use the definition of the determinant, and the answer should arise easily.
 
  • #4
In particular, how may "k"s are there in the matrix kA? What is the determinant of kI where I is the identity matrix?
 

1. What is the definition of "det(kA)"?

The determinant of kA is the product of all the eigenvalues of the matrix kA. In other words, it is a scalar value that represents the scaling factor of the matrix kA.

2. How is "det(kA)" related to "det(A)"?

The relationship between det(kA) and det(A) is that det(kA) is equal to k raised to the power of n, where n is the dimension of the matrix, multiplied by det(A). In other words, the determinant of a scaled matrix is equal to the scaling factor raised to the power of the matrix's dimension, multiplied by the determinant of the original matrix.

3. Is the proof of det(kA)=k^n det(A) applicable to all matrices?

Yes, the proof of det(kA)=k^n det(A) is applicable to all matrices, as long as the matrix is square and the scaling factor k is a constant.

4. Can this proof be extended to matrices with complex numbers?

Yes, this proof can be extended to matrices with complex numbers, as long as the complex numbers are treated as scalars and follow the same rules of multiplication and addition as real numbers.

5. How can this proof be used in practical applications?

This proof can be used in various practical applications, such as in solving systems of linear equations, calculating the area of a parallelogram or the volume of a parallelepiped, and in determining the invertibility of a matrix. It is also used in various fields of science and engineering, such as quantum mechanics, circuit analysis, and computer graphics.

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