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

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Discussion Overview

The discussion centers around the relationship between the determinants of an n x n matrix A and its negation, -A. Participants explore this relationship through examples with matrices of different sizes and consider the implications of multiplying rows or columns by scalars.

Discussion Character

  • Exploratory
  • Technical explanation
  • Mathematical reasoning

Main Points Raised

  • One participant observes that for a 1x1 matrix, det(-A) = -det(A), while for a 2x2 matrix, det(A) = det(-A), leading to a conjecture that for odd n, det(-A) = -det(A) and for even n, det(-A) = det(A).
  • Another participant questions the reasoning behind multiplying rows or columns by a scalar and its effect on the determinant, suggesting confusion regarding the distribution of the scalar across the matrix entries.
  • A participant clarifies that the determinant relationship holds when multiplying a single row by a scalar, but not when multiplying the entire matrix by a scalar.
  • One participant proposes that if each row of an n x n matrix is multiplied by -1, the determinant becomes det(B) = (-1)^n * det(A), which would explain the differing results for odd and even n.
  • A later reply confirms this reasoning and introduces a generalization using the property det(A*B) = det(A)*det(B), specifically noting that det(-1*I) = (-1)^n.

Areas of Agreement / Disagreement

Participants express differing views on the determinant relationship for various matrix sizes, with some supporting the conjecture about odd and even n, while others seek clarification on the implications of scalar multiplication. The discussion remains unresolved regarding the best way to mathematically demonstrate the relationship.

Contextual Notes

Participants highlight potential confusion regarding the effects of scalar multiplication on determinants and the specific cases of odd and even n, indicating a need for careful consideration of definitions and assumptions in their reasoning.

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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Let A be an nxn matrix. What happens if we multiply a row/column of A with a scalar \lambda? What happens if we do this to all the rows/columns? How does it affect the first relation?
 
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?
 
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.
 
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?
 
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.
 

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