Determinant Relationship: det(A) and det(-A) for n x n Matrices

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In summary, the relationship between det(A) and det(-A) is that for odd n, det(-A) = - det(A) and for even n, the two are equal. This can be shown mathematically by multiplying each row of A by a scalar and using the formula det(A*B) = det(A)*det(B). Alternatively, for a square matrix A, if we let B be obtained from A by multiplying it by the scalar k, then det(B) = k*det(A). When k = -1, this formula holds true for all n, and explains the difference in results for odd and even n.
  • #1
johndoe3344
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For an n x n matrix A, what is the relationship between det(A) and det(-A)?

I tried it with a 1x1 matrix, and det (-A) = - det (A)
I tried it with a 2x2 matrix, and det(A) = det(-A)
I tried it with a 3x3 matrix, and the results were the same as that with a 1x1.

This leads me to believe that for all odd n's, det(-A) = - det(A) and that for all even n's the two are the same.

Is this the case? And if so, how would I show that in a more mathematical manner that just intuition?
 
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  • #2
Let A be an nxn matrix. What happens if we multiply a row/column of A with a scalar [itex]\lambda[/itex]? What happens if we do this to all the rows/columns? How does it affect the first relation?
 
  • #3
Why are we multiplying each individual row/column by a scalar?

When we multiply the matrix by a scalar, doesn't this automatically distribute the scalar to every single entry of the matrix?

I guess what I'm confused at is this:

Suppose we let the square matrix B be obtained from matrix A by multiplying the matrix A by the scalar k. Then det(B) = k*det(A). Then if we let k = -1, as in my original question, then won't det(-A) = det(A) for all n?

But obviously this isn't the case. What am I doing wrong?
 
  • #4
johndoe3344 said:
Suppose we let the square matrix B be obtained from matrix A by multiplying the matrix A by the scalar k. Then det(B) = k*det(A).
Not so. You're thinking of the case when B is obtained by multiplying a single row of A by k.
 
  • #5
So since multiplying each row of a scalar by the constant gives us det(B) = k*det(A)...

If we multiply each row of a n x n matrix by the same constant, i.e. n times, then the formula would be for the case of k = -1:

det(B) = [(-1)^n]*det(A)

Which would explain the difference for odd n, and the same for even n.

Is this correct?
 
  • #6
Yes, that's correct.

There's an another way to see this if you know that det(A*B) = det(A)*det(B): If we let I be the nxn identity matrix, then det(-1*I) = (-1)^n, so that det(-A) = det(-1*I * A) = det(-1*I) det(A) = (-1)^n det(A). Of course this can be generalized to any k.
 

1. What are determinants in science?

Determinants are mathematical quantities used in various scientific fields, such as physics, biology, and chemistry. They represent the relationships between different variables and help to understand and predict the behavior of complex systems.

2. How do determinants impact scientific research?

Determinants play a crucial role in scientific research as they provide a framework for analyzing and understanding complex phenomena. They allow scientists to identify key factors and relationships that influence a system and make predictions about its behavior.

3. What are the different types of determinants?

There are several types of determinants, including linear, quadratic, and multivariate determinants. Each type has its own formula and application in various scientific fields.

4. How are determinants calculated?

The calculation of determinants depends on the type and size of the matrix or set of variables being analyzed. For example, the determinant of a 2x2 matrix can be found by multiplying the elements in the diagonal and subtracting the product of the elements in the other diagonal. For more complex matrices, there are specific formulas and methods for determining the determinant.

5. Can determinants be negative?

Yes, determinants can be negative. The sign of a determinant depends on the arrangement of the elements in a matrix. For example, a 2x2 matrix with a negative determinant means that the matrix is inverted, while a positive determinant indicates a non-inverted matrix.

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