Odd Determinant: Explaining a Strange Phenomenon

In summary, an odd determinant is a square matrix whose determinant is an odd number, calculated by finding the determinant using the standard method and determining if the resulting number is odd or even. It is significant in mathematics for explaining patterns and has various real-life applications in fields such as physics, engineering, and economics. An odd determinant can also be negative, determined by the number of row exchanges needed to convert the matrix to row-echelon form.
  • #1
TTob
21
0
I don't understand this :

let A is n x n matrix whose entries are precisely the numbers 1, 2, . . . , n^2.
Put odd numbers into the diagonal of A, only even numbers above the diagonal and arrange the entries under the diagonal arbitrarily. Then det(A) is odd.

What is the explanation ?
 
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  • #2
What have you tried? In particular, have you tried seeing what happens for n= 2 and 3?
 
  • #3
for n=2 we have det(A) = -5. so what ?
 

Related to Odd Determinant: Explaining a Strange Phenomenon

1. What is an odd determinant?

An odd determinant is a mathematical term used to describe a square matrix whose determinant is an odd number.

2. How is an odd determinant calculated?

An odd determinant is calculated by finding the determinant of a square matrix using the standard method of expanding the matrix and then determining if the resulting number is odd or even.

3. What is the significance of an odd determinant?

An odd determinant is significant because it can help explain certain patterns or phenomena in mathematics, such as the number of solutions to a system of equations or the number of possible arrangements in a puzzle.

4. Can an odd determinant ever be negative?

Yes, an odd determinant can be negative. The sign of an odd determinant is determined by the number of row exchanges needed to convert the matrix to row-echelon form, which can result in a negative value.

5. Are there any real-life applications of odd determinants?

Yes, odd determinants have various applications in fields such as physics, engineering, and economics. For example, in physics, they can be used to calculate the energy levels of quantum systems, and in economics, they can help determine the stability of a market equilibrium.

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