Basics of Field Extensions .... .... Ireland and Rosen, Ch 12

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In summary, Ireland and Rosen explain that the norm of an element in L/K is the determinant of a matrix with the element as the row vector and the basis as the column vectors. The norm of an element in L/K is the same as the product of the element and its square.
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I am reading Kenneth Ireland and Michael Rosen's book, "A Classical Introduction to Modern Number Theory" ... ...

I am currently focused on Chapter 12: Algebraic Number Theory ... ... I need some help in order to follow a basic result in Section 1: Algebraic Preliminaries ...

The start of Section 1 reads as follows:

View attachment 6509
QUESTION 1


In the above text by Ireland and Rosen, we read the following:"... ... Suppose \(\displaystyle \alpha_1, \alpha_2, \ ... \ ... \ , \alpha_n\) is a basis for \(\displaystyle L/K\) and \(\displaystyle \alpha \in L\).Then \(\displaystyle \alpha \alpha_i = \sum_j a_{ ij } \alpha_j\) with \(\displaystyle a_{ ij } \in K\) ... ... "

My question is ... ... how do Ireland and Rosen get \(\displaystyle \alpha \alpha_i = \sum_j a_{ ij } \alpha_j\) ... ... ?

My thoughts are as follows ...Given \(\displaystyle L/K\), we have that \(\displaystyle L\) is a vector space over \(\displaystyle K\).

... we then let \(\displaystyle \alpha_1, \alpha_2, \ ... \ ... \ , \alpha_n\) be a basis for \(\displaystyle L\) as a vector space over \(\displaystyle K\)

( I take it that that is what I&R mean by "... ... Suppose \(\displaystyle \alpha_1, \alpha_2, \ ... \ ... \ , \alpha_n \)is a basis for \(\displaystyle L/K\)")... we then let \(\displaystyle \alpha \in L\) ... ... then there exist \(\displaystyle a_1, a_2, \ ... \ ... \ , a_n \in K\) such that \(\displaystyle \alpha = a_1 \alpha_1 + a_2 \alpha_2 + \ ... \ ... \ a_n \alpha_n\) so that \(\displaystyle \alpha \alpha_i = ( a_1 \alpha_1 + a_2 \alpha_2 + \ ... \ ... \ a_n \alpha_n ) \alpha_i\) ... ... ... (1)... BUT ...

Ireland and Rosen write (see above)\(\displaystyle \alpha \alpha_i = \sum_j a_{ ij } \alpha_j\)\(\displaystyle = a_{ i1 } \alpha_1 + a_{ i2 } \alpha_2 + \ ... \ ... \ + a_{ in } \alpha_n\) ... ... ... (2)My question is ... how do we get expression (1) equal to (2) ... ...
QUESTION 2In the above text by Ireland and Rosen, we read the following:"... ...The norm of \(\displaystyle \alpha, N_{ L/K } ( \alpha )\) is \(\displaystyle text{ det} (a_{ ij } )\) ... ... I cannot fully understand the process involved in forming the norm ... can someone please explain ... preferably via a simple example ...
Hope someone can help ... Peter
 
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  • #2
Hi Peter,

It appears you've missed something key here, which is that $L$ is a field. So all the products $\alpha \alpha_i$ belong to $L$. As $L$ is spanned by the $\alpha_j$, each product $\alpha \alpha_i$ is $K$-linear combination of the $\alpha_j$, which is displayed in the formulae

$$\alpha\alpha_i = \sum_{j} a_{ij} \alpha_j, \quad a_{ij}\in K$$
 
  • #3
To answer your second question, consider $$L = \Bbb Q(\sqrt{2}) = \{a + b\sqrt{2} : a,b\in \Bbb Q\}\quad \text{and}\quad K = \Bbb Q$$ Set $\alpha = 3 + 2\sqrt{2}$. The numbers $1, \sqrt{2}$ form a basis for $L/K$. Further,

$\alpha \cdot 1 = 3 + 2\sqrt{2}$
$\alpha \cdot \sqrt{2} = 4 + 3\sqrt{2}$

Hence, the matrix $(a_{ij})$ of $\alpha$ with respect to the ordered basis $\{1,\sqrt{2}\}$ is given by

$$\begin{pmatrix}3 & 2\\ 4 & 3\end{pmatrix}$$

The determinant of this matrix is $3(3) - 4(2) = 1$, so the norm of $\alpha$, $N_{L/K}(\alpha)$, equals $1$.

As an exercise, show that in general, the norm of an element $a + b\sqrt{2}$ in $Q(\sqrt{2})$ is $a^2 - 2b^2$.
 
  • #4
Euge said:
Hi Peter,

It appears you've missed something key here, which is that $L$ is a field. So all the products $\alpha \alpha_i$ belong to $L$. As $L$ is spanned by the $\alpha_j$, each product $\alpha \alpha_i$ is $K$-linear combination of the $\alpha_j$, which is displayed in the formulae

$$\alpha\alpha_i = \sum_{j} a_{ij} \alpha_j, \quad a_{ij}\in K$$
Thanks Euge ... yes ... should have known!

Obvious now, of course ... :(

Peter
 
  • #5
Euge said:
To answer your second question, consider $$L = \Bbb Q(\sqrt{2}) = \{a + b\sqrt{2} : a,b\in \Bbb Q\}\quad \text{and}\quad K = \Bbb Q$$ Set $\alpha = 3 + 2\sqrt{2}$. The numbers $1, \sqrt{2}$ form a basis for $L/K$. Further,

$\alpha \cdot 1 = 3 + 2\sqrt{2}$
$\alpha \cdot \sqrt{2} = 4 + 3\sqrt{2}$

Hence, the matrix $(a_{ij})$ of $\alpha$ with respect to the ordered basis $\{1,\sqrt{2}\}$ is given by

$$\begin{pmatrix}3 & 2\\ 4 & 3\end{pmatrix}$$

The determinant of this matrix is $3(3) - 4(2) = 1$, so the norm of $\alpha$, $N_{L/K}(\alpha)$, equals $1$.

As an exercise, show that in general, the norm of an element $a + b\sqrt{2}$ in $Q(\sqrt{2})$ is $a^2 - 2b^2$.
Thanks Euge ... wonderfully clear and helpful example ...

Peter
 

1. What is a field extension?

A field extension is a mathematical concept that involves extending a smaller field (such as the rational numbers) to a larger field (such as the real numbers) by adding new elements.

2. How are field extensions related to algebraic equations?

Field extensions are closely related to algebraic equations because they allow us to find solutions to equations that cannot be solved within the smaller field. For example, the equation x² = 2 has no solution in the rational numbers, but can be solved in the real numbers, which is a field extension of the rational numbers.

3. Can field extensions be finite or infinite?

Field extensions can be either finite or infinite. A finite field extension contains a finite number of elements, while an infinite field extension contains an infinite number of elements.

4. How are field extensions used in cryptography?

Field extensions play an important role in cryptography, specifically in the creation of public key encryption systems. In these systems, field extensions are used to create mathematical structures that are difficult to break, providing secure communication over public channels.

5. Are there any real-world applications of field extensions?

Field extensions have numerous real-world applications, such as in physics, chemistry, and computer science. They are used to model and solve problems involving complex numbers, matrices, and vector spaces, among others.

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