How to calculate this determinate

  • Thread starter jdstokes
  • Start date
In summary, the conversation discusses the function f_n(x_1,x_2,\ldots,x_n), which is defined as a matrix with entries based on the input values x_1, x_2, ..., x_n. Part (b) shows that this function can be written as a polynomial in x_1 with coefficients g_0, g_1, ..., g_{n-1}. Part (c) is still being worked on, but suggests that f_n(x_1,x_2,\ldots,x_n) can be factored into multiples of (x_i-x_1) for i from 2 to n. Two potential approaches for proving this are suggested: finding the coefficients in terms of f_{n
  • #1
jdstokes
523
1
Let [itex]n[/itex] be a positive integer, and define the function

[itex]f_n(x_1,x_2,\ldots, x_n) = \left(
\begin{array}{ccccc}
1 & 1 & 1 & \ldots & 1 \\
x_1 & x_2 & x_3 & \ldots & x_n \\
x_1^2 & x_2^2 & x_3^2 & \ldots & x_n^2 \\
\vdots & \vdots & \vdots & \ddots & \vdots \\
x_1^{n-1} & x_2^{n-1} & x_3^{n-1} & \ldots & x_n^{n-1}
\end{array}
\right)[/itex]

(b) By considering the first column expansion of the determinant, show that

[itex]f_n(x_1,x_2,\ldots,x_2) = g_0 + g_1x_1 + g_2x_1^2 + \cdots + g_{n-1}x_1^{n-1}[/itex], and, in particular, [itex]g_{n-1}=(-1)^{n-1}f_{n-1}(x_2,x_3,\ldots,x_n)[/itex]

(c) Show that [itex]f_n(x_1,x_2,\ldots,x_2)[/itex] has [itex]x_i-x_1[/itex] as a factor, for all values of [itex]i[/itex] from 2 to [itex]n[/itex].

I think I've sorted part (b) out. I don't have a clue about how to proceed in part (c).

Thanks.

James
 
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  • #2
Why do you have

[tex]f_n(x_1,x_2,\ldots,\mathbf{x_2}) = g_0 + g_1x_1 + g_2x_1^2 + \cdots + g_{n-1}x_1^{n-1}[/tex]

Do you mean

[tex]f_n(x_1,x_2,\ldots,\mathbf{x_n}) = g_0 + g_1x_1 + g_2x_1^2 + \cdots + g_{n-1}x_1^{n-1}[/tex]

I'm not exactly sure if this will work, but write [itex]f_n[/itex] as a polynomial in [itex]x_1[/itex] with coefficients [itex]g_0,\, \dots ,\, g_{n-1}[/itex]. You should be able to write these coefficients (or, at least one of them) in terms of [itex]f_{n-1}[/itex], which you can in turn write as a polynomial in [itex]x_2[/itex]. You'll get something with [itex]x_1[/itex] and [itex]x_2[/itex] in there, and hopefully you'll be able to factor it to get the desired results. You should end up with new coefficients for which you can do something similar, working in all the [itex]x_i[/itex] and then hopefully being able to factor.

Alternatively, treat [itex]f_n(x_1,\, \dots ,\, x_n)[/itex] as the single-variable polynomial [itex]f_{n-x_2,\dots ,x_n}(x_1)[/itex]. If [itex]f_n[/itex] is supposed to factor as it suggests in part c), then so should this new polynomial. But this polynomial is of degree n-1, and the problem suggests that you can pull out n-1 factors, so if what you are supposed to prove is correct, then the new polynomial should be a constant multiplied by the product of those factors. This doesn't seem exactly right because your coefficients are matrices, but the roots you're finding are whatever [itex]x_1[/itex] is, but you may want to try this approach. Take the product of those factors, and multiply it by [itex]g_{n-1}[/itex] and see if you end up with [itex]f_n[/itex].
 
  • #3


To calculate the determinant of the given function, we can use the Laplace expansion method. This involves expanding the determinant along one row or column and using cofactors to solve for the determinant. In this case, we will use the first column expansion.

First, we can see that the determinant is a polynomial in x_1, with degree n-1. This means it can be written as g_0 + g_1x_1 + g_2x_1^2 + \cdots + g_{n-1}x_1^{n-1}. We can also see that the coefficients of this polynomial are determined by the cofactors of the first column.

Using the Laplace expansion, we can write the determinant as:

f_n(x_1,x_2,\ldots,x_n) = x_1 \cdot \left(
\begin{array}{ccccc}
x_2 & x_3 & x_4 & \ldots & x_n \\
x_2^2 & x_3^2 & x_4^2 & \ldots & x_n^2 \\
\vdots & \vdots & \vdots & \ddots & \vdots \\
x_2^{n-1} & x_3^{n-1} & x_4^{n-1} & \ldots & x_n^{n-1}
\end{array}
\right)

Now, we can see that this is just the determinant of f_{n-1}(x_2,x_3,\ldots,x_n), with x_1 as a common factor. This means that g_{n-1} is equal to (-1)^{n-1} times the determinant of f_{n-1}(x_2,x_3,\ldots,x_n).

For part (c), we can use the same method of Laplace expansion to show that x_i-x_1 is a factor of f_n(x_1,x_2,\ldots,x_n). Expanding along the i-th column, we get:

f_n(x_1,x_2,\ldots,x_n) = (x_i-x_1) \cdot \left(
\begin{array}{ccccc}
1 & 1 & 1 & \ldots & 1 \\
x_1 & x_2 & x_3 & \ldots &
 

1. How do I calculate a determinate using the matrix method?

The matrix method for calculating a determinate involves finding the sum of the products of the elements in each row or column. You can use this method for any square matrix.

2. What is the difference between a minor and a cofactor when calculating a determinate?

A minor is the determinate of a smaller matrix formed by removing a row and a column from the original matrix. A cofactor is the minor multiplied by either positive or negative 1 depending on its position in the original matrix.

3. Can I use a calculator to find the determinate of a matrix?

Yes, most calculators have a function specifically for calculating determinants. However, it is important to understand the matrix method so you can verify the calculator's results.

4. What is the significance of a determinate in linear algebra?

The determinate of a matrix is important because it can tell us whether the matrix is invertible or not. If the determinate is equal to 0, the matrix is not invertible and has no inverse. Additionally, the determinate can also give us information about the solutions of a system of linear equations.

5. How can I use the properties of determinants to simplify my calculations?

There are several properties of determinants that can make calculations easier, such as the fact that the determinate of a triangular matrix is equal to the product of its diagonal elements. Also, swapping two rows or columns in a matrix does not change the determinate. By using these properties, you can simplify the matrix and make it easier to calculate the determinate.

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