Undergrad Subspaces in Axler's Famous Textbook

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SUMMARY

The discussion focuses on the conditions for a subset to qualify as a subspace in linear algebra, specifically referencing Axler's "Linear Algebra Done Right." It establishes that the set {(x1,x2,x3,x4) ∈ F4 : x3 = 5x4 + b} is a subspace of F4 if and only if b=0, as the zero vector must be included. Additionally, the set {p ∈ P(F) : p(3) = 0} is confirmed as a subspace of the polynomial space P(F) due to closure under addition and scalar multiplication. The conversation emphasizes the importance of understanding these concepts for grasping vector spaces and their properties.

PREREQUISITES
  • Understanding of vector spaces and subspaces
  • Familiarity with polynomial functions and their properties
  • Knowledge of fields, specifically real numbers (R) and complex numbers (C)
  • Basic concepts from linear algebra as presented in Axler's "Linear Algebra Done Right"
NEXT STEPS
  • Study the definition and properties of vector spaces and subspaces
  • Explore polynomial spaces and their dimensionality
  • Learn about closure properties in vector spaces
  • Investigate examples of infinite and finite dimensional subspaces
USEFUL FOR

Students of linear algebra, educators teaching vector space concepts, and anyone seeking to deepen their understanding of polynomial spaces and subspace criteria.

gibberingmouther
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Just started working through "Linear Algebra Done Right". There is something I don't understand.

Given b ∈ F, then
{(x1,x2,x3,x4) ∈ F4 : x3 = 5x4 + b}
is a subspace of F4 *if and only if* b=0

I just flat out don't understand why b has to be 0 or even what is the point of bringing this up.

and right below that is:
{p ∈ P(F) : p(3) = 0}
is a subspace of P(F).

P(F) refers to the polynomial space. F is the set of fields and it contains C (complex numbers) and R (real numbers).

Again, what is the point of bringing this up and how do we know that p is a subspace of P(F) based off of the information given?
 
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gibberingmouther said:
Just started working through "Linear Algebra Done Right". There is something I don't understand.

Given b ∈ F, then
{(x1,x2,x3,x4) ∈ F4 : x3 = 5x4 + b}
is a subspace of F4 *if and only if* b=0

I just flat out don't understand why b has to be 0 or even what is the point of bringing this up.

and right below that is:
{p ∈ P(F) : p(3) = 0}
is a subspace of P(F).

P(F) refers to the polynomial space. F is the set of fields and it contains C (complex numbers) and R (real numbers).

Again, what is the point of bringing this up and how do we know that p is a subspace of P(F) based off of the information given?
A subspace is itself a vector space again. Therefore it needs to contain ##0##. But ##0=(0,0,0,0) \in \{\,(x_1,x_2,x_3,x_4)\in \mathbb{F}^4\,;\,x_3=5x_4+b\,\}## if and only if ##b=0\,.##

I haven't looked it up, but I'm sure ##\mathbb{F}## stands for some field, not all fields, so ##\mathbb{F}\in \{\,\mathbb{R},\mathbb{C}\,\}## or (later on) any other field.
 
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gibberingmouther said:
Again, what is the point of bringing this up and how do we know that p is a subspace of P(F) based off of the information given?

Apparently "p(3) =0" indicates that x = 3 is a root of the polynomial. The sum of two such polynomials is a polynomial that satisfies that property and a scalar multiple of such a polynomial is a polynomial that satisfies that property.

From a didactic point of view, vector spaces defined as a set of polynomials are an important example because they provide an illustration that vector doesn't have to denote a physical quantity "with magnitude and direction". Presumably, students are already familiar with polynomials.

The set of polynomials (in one "indeterminate" x, with the usual definitions of "+" as an operation on polynomials and multiplication by a number as scalar multiplication ) is a good example of an infinite dimensional vector space.

The set of polynomials that have the root x = 3 is a good example of an infinite dimensional subspace.

The set of polynomials of degree at most 3 is a good example of a finite dimensional subspace.

The fact we can multiply two polynomials (by the usual definition of how to do so) illustrates that it may be possible to define operations other than "+" on two vectors. On the other hand, the axioms for a vector space do not define such operations. So some examples of vector spaces are "more than a vector space".
 
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subspaces are flat sets that pass through the origin. being flat means all exponents in the equation have degree ≤ 1 (and at least one exponent is = 1), and passing through the origin means all exponents are equal to 1, i.e. no non zero constant term.
 
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