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<a href="./an-assortment-of-preliminaries-on-linear-algebra.html">An assortment of preliminaries on linear algebra</a>
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class="mb-1 mt-2 italic font-light text-lg text-accent-light dark:text-accent-dark"
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and also a test for pandoc
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<div class="mt-2">2025-02-15</div>
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<main class="post mt-4"><p>This entire document was written entirely in <a href="https://typst.app/">Typst</a> and
directly translated to this file by Pandoc. It serves as a proof of concept of
a way to do static site generation from Typst files instead of Markdown.</p>
<hr />
<p>I figured I should write this stuff down before I forgot it.</p>
<h1 id="basic-notions">Basic Notions</h1>
<h2 id="vector-spaces">Vector spaces</h2>
<p>Before we can understand vectors, we need to first discuss <em>vector
spaces</em>. Thus far, you have likely encountered vectors primarily in
physics classes, generally in the two-dimensional plane. You may
conceptualize them as arrows in space. For vectors of size <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo>&gt;</mo><mn>3</mn></mrow><annotation encoding="application/x-tex">&gt; 3</annotation></semantics></math>, a hand
waving argument is made that they are essentially just arrows in higher
dimensional spaces.</p>
<p>It is helpful to take a step back from this primitive geometric
understanding of the vector. Let us build up a rigorous idea of vectors
from first principles.</p>
<h3 id="vector-axioms">Vector axioms</h3>
<p>The so-called <em>axioms</em> of a <em>vector space</em> (which well call the vector
space <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>V</mi><annotation encoding="application/x-tex">V</annotation></semantics></math>) are as follows:</p>
<ol>
<li><p>Commutativity: <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>u</mi><mo>+</mo><mi>v</mi><mo>=</mo><mi>v</mi><mo>+</mo><mi>u</mi><mo>,</mo><mrow><mspace width="0.333em"></mspace><mtext mathvariant="normal"> </mtext><mspace width="0.333em"></mspace></mrow><mo></mo><mi>u</mi><mo>,</mo><mi>v</mi><mo></mo><mi>V</mi></mrow><annotation encoding="application/x-tex">u + v = v + u,\text{ }\forall u,v \in V</annotation></semantics></math></p></li>
<li><p>Associativity:
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><mo stretchy="true" form="prefix">(</mo><mi>u</mi><mo>+</mo><mi>v</mi><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><mi>w</mi><mo>=</mo><mi>u</mi><mo>+</mo><mrow><mo stretchy="true" form="prefix">(</mo><mi>v</mi><mo>+</mo><mi>w</mi><mo stretchy="true" form="postfix">)</mo></mrow><mo>,</mo><mrow><mspace width="0.333em"></mspace><mtext mathvariant="normal"> </mtext><mspace width="0.333em"></mspace></mrow><mo></mo><mi>u</mi><mo>,</mo><mi>v</mi><mo>,</mo><mi>w</mi><mo></mo><mi>V</mi></mrow><annotation encoding="application/x-tex">(u + v) + w = u + (v + w),\text{ }\forall u,v,w \in V</annotation></semantics></math></p></li>
<li><p>Zero vector: <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mo></mo><annotation encoding="application/x-tex">\exists</annotation></semantics></math> a special vector, denoted <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mn>0</mn><annotation encoding="application/x-tex">0</annotation></semantics></math>, such that
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi><mo>+</mo><mn>0</mn><mo>=</mo><mi>v</mi><mo>,</mo><mrow><mspace width="0.333em"></mspace><mtext mathvariant="normal"> </mtext><mspace width="0.333em"></mspace></mrow><mo></mo><mi>v</mi><mo></mo><mi>V</mi></mrow><annotation encoding="application/x-tex">v + 0 = v,\text{ }\forall v \in V</annotation></semantics></math></p></li>
<li><p>Additive inverse:
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo></mo><mi>v</mi><mo></mo><mi>V</mi><mo>,</mo><mrow><mspace width="0.333em"></mspace><mtext mathvariant="normal"> </mtext><mspace width="0.333em"></mspace></mrow><mo></mo><mi>w</mi><mo></mo><mi>V</mi><mrow><mspace width="0.333em"></mspace><mtext mathvariant="normal"> such that </mtext><mspace width="0.333em"></mspace></mrow><mi>v</mi><mo>+</mo><mi>w</mi><mo>=</mo><mn>0</mn></mrow><annotation encoding="application/x-tex">\forall v \in V,\text{ }\exists w \in V\text{ such that }v + w = 0</annotation></semantics></math>.
Such an additive inverse is generally denoted <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi></mi><mi>v</mi></mrow><annotation encoding="application/x-tex">- v</annotation></semantics></math></p></li>
<li><p>Multiplicative identity: <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>1</mn><mi>v</mi><mo>=</mo><mi>v</mi><mo>,</mo><mrow><mspace width="0.333em"></mspace><mtext mathvariant="normal"> </mtext><mspace width="0.333em"></mspace></mrow><mo></mo><mi>v</mi><mo></mo><mi>V</mi></mrow><annotation encoding="application/x-tex">1v = v,\text{ }\forall v \in V</annotation></semantics></math></p></li>
<li><p>Multiplicative associativity:
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><mo stretchy="true" form="prefix">(</mo><mi>α</mi><mi>β</mi><mo stretchy="true" form="postfix">)</mo></mrow><mi>v</mi><mo>=</mo><mi>α</mi><mrow><mo stretchy="true" form="prefix">(</mo><mi>β</mi><mi>v</mi><mo stretchy="true" form="postfix">)</mo></mrow><mrow><mspace width="0.333em"></mspace><mtext mathvariant="normal"> </mtext><mspace width="0.333em"></mspace></mrow><mo></mo><mi>v</mi><mo></mo><mi>V</mi><mo>,</mo><mrow><mspace width="0.333em"></mspace><mtext mathvariant="normal"> scalars </mtext><mspace width="0.333em"></mspace></mrow><mi>α</mi><mo>,</mo><mi>β</mi></mrow><annotation encoding="application/x-tex">(\alpha\beta)v = \alpha(\beta v)\text{ }\forall v \in V,\text{ scalars }\alpha,\beta</annotation></semantics></math></p></li>
<li><p>Distributive property for vectors:
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>α</mi><mrow><mo stretchy="true" form="prefix">(</mo><mi>u</mi><mo>+</mo><mi>v</mi><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><mi>α</mi><mi>u</mi><mo>+</mo><mi>α</mi><mi>v</mi><mrow><mspace width="0.333em"></mspace><mtext mathvariant="normal"> </mtext><mspace width="0.333em"></mspace></mrow><mo></mo><mi>u</mi><mo>,</mo><mi>v</mi><mo></mo><mi>V</mi><mo>,</mo><mrow><mspace width="0.333em"></mspace><mtext mathvariant="normal"> scalars </mtext><mspace width="0.333em"></mspace></mrow><mi>α</mi></mrow><annotation encoding="application/x-tex">\alpha(u + v) = \alpha u + \alpha v\text{ }\forall u,v \in V,\text{ scalars }\alpha</annotation></semantics></math></p></li>
<li><p>Distributive property for scalars:
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><mo stretchy="true" form="prefix">(</mo><mi>α</mi><mo>+</mo><mi>β</mi><mo stretchy="true" form="postfix">)</mo></mrow><mi>v</mi><mo>=</mo><mi>α</mi><mi>v</mi><mo>+</mo><mi>β</mi><mi>v</mi><mrow><mspace width="0.333em"></mspace><mtext mathvariant="normal"> </mtext><mspace width="0.333em"></mspace></mrow><mo></mo><mi>v</mi><mo></mo><mi>V</mi><mo>,</mo><mrow><mspace width="0.333em"></mspace><mtext mathvariant="normal"> scalars </mtext><mspace width="0.333em"></mspace></mrow><mi>α</mi><mo>,</mo><mi>β</mi></mrow><annotation encoding="application/x-tex">(\alpha + \beta)v = \alpha v + \beta v\text{ }\forall v \in V,\text{ scalars }\alpha,\beta</annotation></semantics></math></p></li>
</ol>
<p>It is easy to show that the zero vector <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mn>0</mn><annotation encoding="application/x-tex">0</annotation></semantics></math> and the additive inverse
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi></mi><mi>v</mi></mrow><annotation encoding="application/x-tex">- v</annotation></semantics></math> are <em>unique</em>. We leave the proof of this fact as an exercise.</p>
<p>These may seem difficult to memorize, but they are essentially the same
familiar algebraic properties of numbers you know from high school. The
important thing to remember is which operations are valid for what
objects. For example, you cannot add a vector and scalar, as it does not
make sense.</p>
<p><em>Remark</em>. For those of you versed in computer science, you may recognize
this as essentially saying that you must ensure your operations are
<em>type-safe</em>. Adding a vector and scalar is not just “wrong” in the same
sense that <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>1</mn><mo>+</mo><mn>1</mn><mo>=</mo><mn>3</mn></mrow><annotation encoding="application/x-tex">1 + 1 = 3</annotation></semantics></math> is wrong, it is an <em>invalid question</em> entirely
because vectors and scalars and different types of mathematical objects.
See [@chen2024digression] for more.</p>
<h3 id="vectors-big-and-small">Vectors big and small</h3>
<p>In order to begin your descent into what mathematicians colloquially
recognize as <em>abstract vapid nonsense</em>, lets discuss which fields
constitute a vector space. We have the familiar field of <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi></mi><annotation encoding="application/x-tex">\mathbb{R}</annotation></semantics></math>
where all scalars are real numbers, with corresponding vector spaces
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mi>n</mi></msup><annotation encoding="application/x-tex">{\mathbb{R}}^{n}</annotation></semantics></math>, where <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>n</mi><annotation encoding="application/x-tex">n</annotation></semantics></math> is the length of the vector. We generally
discuss 2D or 3D vectors, corresponding to vectors of length 2 or 3; in
our case, <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mn>2</mn></msup><annotation encoding="application/x-tex">{\mathbb{R}}^{2}</annotation></semantics></math> and <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mn>3</mn></msup><annotation encoding="application/x-tex">{\mathbb{R}}^{3}</annotation></semantics></math>.</p>
<p>However, vectors in <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mi>n</mi></msup><annotation encoding="application/x-tex">{\mathbb{R}}^{n}</annotation></semantics></math> can really be of any length.
Vectors can be viewed as arbitrary length lists of numbers (for the
computer science folk: think C++ <code>std::vector</code>).</p>
<p><em>Example</em>. <math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>2</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>3</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>4</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>5</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>6</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>7</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>8</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>9</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo></mo><msup><mi></mi><mn>9</mn></msup></mrow><annotation encoding="application/x-tex">\begin{pmatrix}
1 \\
2 \\
3 \\
4 \\
5 \\
6 \\
7 \\
8 \\
9
\end{pmatrix} \in {\mathbb{R}}^{9}</annotation></semantics></math></p>
<p>Keep in mind that vectors need not be in <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mi>n</mi></msup><annotation encoding="application/x-tex">{\mathbb{R}}^{n}</annotation></semantics></math> at all.
Recall that a vector space need only satisfy the aforementioned <em>axioms
of a vector space</em>.</p>
<p><em>Example</em>. The vector space <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mi>n</mi></msup><annotation encoding="application/x-tex">{\mathbb{C}}^{n}</annotation></semantics></math> is similar to
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mi>n</mi></msup><annotation encoding="application/x-tex">{\mathbb{R}}^{n}</annotation></semantics></math>, except it includes complex numbers. All complex
vector spaces are real vector spaces (as you can simply restrict them to
only use the real numbers), but not the other way around.</p>
<p>From now on, let us refer to vector spaces <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mi>n</mi></msup><annotation encoding="application/x-tex">{\mathbb{R}}^{n}</annotation></semantics></math> and
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mi>n</mi></msup><annotation encoding="application/x-tex">{\mathbb{C}}^{n}</annotation></semantics></math> as <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>𝔽</mi><mi>n</mi></msup><annotation encoding="application/x-tex">{\mathbb{F}}^{n}</annotation></semantics></math>.</p>
<p>In general, we can have a vector space where the scalars are in an
arbitrary field, as long as the axioms are satisfied.</p>
<p><em>Example</em>. The vector space of all polynomials of at most degree 3, or
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mn>3</mn></msup><annotation encoding="application/x-tex">{\mathbb{P}}^{3}</annotation></semantics></math>. It is not yet clear what this vector may look like.
We shall return to this example once we discuss <em>basis</em>.</p>
<h2 id="vector-addition-multiplication">Vector addition. Multiplication</h2>
<p>Vector addition, represented by <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>+</mi><annotation encoding="application/x-tex">+</annotation></semantics></math> can be done entrywise.</p>
<p><em>Example.</em></p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>2</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>3</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>4</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>5</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>6</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn><mo>+</mo><mn>4</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>2</mn><mo>+</mo><mn>5</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>3</mn><mo>+</mo><mn>6</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>5</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>7</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>9</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\begin{pmatrix}
1 \\
2 \\
3
\end{pmatrix} + \begin{pmatrix}
4 \\
5 \\
6
\end{pmatrix} = \begin{pmatrix}
1 + 4 \\
2 + 5 \\
3 + 6
\end{pmatrix} = \begin{pmatrix}
5 \\
7 \\
9
\end{pmatrix}</annotation></semantics></math> <math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>2</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>3</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo></mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>4</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>5</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>6</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn><mo></mo><mn>4</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>2</mn><mo></mo><mn>5</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>3</mn><mo></mo><mn>6</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>4</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>10</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>18</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\begin{pmatrix}
1 \\
2 \\
3
\end{pmatrix} \cdot \begin{pmatrix}
4 \\
5 \\
6
\end{pmatrix} = \begin{pmatrix}
1 \cdot 4 \\
2 \cdot 5 \\
3 \cdot 6
\end{pmatrix} = \begin{pmatrix}
4 \\
10 \\
18
\end{pmatrix}</annotation></semantics></math></p>
<p>This is simple enough to understand. Again, the difficulty is simply
ensuring that you always perform operations with the correct <em>types</em>.
For example, once we introduce matrices, it doesnt make sense to
multiply or add vectors and matrices in this fashion.</p>
<h2 id="vector-scalar-multiplication">Vector-scalar multiplication</h2>
<p>Multiplying a vector by a scalar simply results in each entry of the
vector being multiplied by the scalar.</p>
<p><em>Example</em>.</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>β</mi><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mi>a</mi></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mi>b</mi></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mi>c</mi></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mi>β</mi><mo></mo><mi>a</mi></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mi>β</mi><mo></mo><mi>b</mi></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mi>β</mi><mo></mo><mi>c</mi></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\beta\begin{pmatrix}
a \\
b \\
c
\end{pmatrix} = \begin{pmatrix}
\beta \cdot a \\
\beta \cdot b \\
\beta \cdot c
\end{pmatrix}</annotation></semantics></math></p>
<h2 id="linear-combinations">Linear combinations</h2>
<p>Given vector spaces <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>V</mi><annotation encoding="application/x-tex">V</annotation></semantics></math> and <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>W</mi><annotation encoding="application/x-tex">W</annotation></semantics></math> and vectors <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi><mo></mo><mi>V</mi></mrow><annotation encoding="application/x-tex">v \in V</annotation></semantics></math> and <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>w</mi><mo></mo><mi>W</mi></mrow><annotation encoding="application/x-tex">w \in W</annotation></semantics></math>,
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi><mo>+</mo><mi>w</mi></mrow><annotation encoding="application/x-tex">v + w</annotation></semantics></math> is the <em>linear combination</em> of <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>v</mi><annotation encoding="application/x-tex">v</annotation></semantics></math> and <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>w</mi><annotation encoding="application/x-tex">w</annotation></semantics></math>.</p>
<h3 id="spanning-systems">Spanning systems</h3>
<p>We say that a set of vectors <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>v</mi><mn>1</mn></msub><mo>,</mo><msub><mi>v</mi><mn>2</mn></msub><mo>,</mo><mi></mi><mo>,</mo><msub><mi>v</mi><mi>n</mi></msub><mo></mo><mi>V</mi></mrow><annotation encoding="application/x-tex">v_{1},v_{2},\ldots,v_{n} \in V</annotation></semantics></math> <em>span</em> <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>V</mi><annotation encoding="application/x-tex">V</annotation></semantics></math>
if the linear combination of the vectors can represent any arbitrary
vector <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi><mo></mo><mi>V</mi></mrow><annotation encoding="application/x-tex">v \in V</annotation></semantics></math>.</p>
<p>Precisely, given scalars <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>α</mi><mn>1</mn></msub><mo>,</mo><msub><mi>α</mi><mn>2</mn></msub><mo>,</mo><mi></mi><mo>,</mo><msub><mi>α</mi><mi>n</mi></msub></mrow><annotation encoding="application/x-tex">\alpha_{1},\alpha_{2},\ldots,\alpha_{n}</annotation></semantics></math>,</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>α</mi><mn>1</mn></msub><msub><mi>v</mi><mn>1</mn></msub><mo>+</mo><msub><mi>α</mi><mn>2</mn></msub><msub><mi>v</mi><mn>2</mn></msub><mo>+</mo><mi></mi><mo>+</mo><msub><mi>α</mi><mi>n</mi></msub><msub><mi>v</mi><mi>n</mi></msub><mo>=</mo><mi>v</mi><mo>,</mo><mo></mo><mi>v</mi><mo></mo><mi>V</mi></mrow><annotation encoding="application/x-tex">\alpha_{1}v_{1} + \alpha_{2}v_{2} + \ldots + \alpha_{n}v_{n} = v,\forall v \in V</annotation></semantics></math></p>
<p>Note that any scalar <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msub><mi>α</mi><mi>k</mi></msub><annotation encoding="application/x-tex">\alpha_{k}</annotation></semantics></math> could be 0. Therefore, it is possible
for a subset of a spanning system to also be a spanning system. The
proof of this fact is left as an exercise.</p>
<h3 id="intuition-for-linear-independence-and-dependence">Intuition for linear independence and dependence</h3>
<p>We say that <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>v</mi><annotation encoding="application/x-tex">v</annotation></semantics></math> and <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>w</mi><annotation encoding="application/x-tex">w</annotation></semantics></math> are linearly independent if <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>v</mi><annotation encoding="application/x-tex">v</annotation></semantics></math> cannot be
represented by the scaling of <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>w</mi><annotation encoding="application/x-tex">w</annotation></semantics></math>, and <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>w</mi><annotation encoding="application/x-tex">w</annotation></semantics></math> cannot be represented by the
scaling of <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>v</mi><annotation encoding="application/x-tex">v</annotation></semantics></math>. Otherwise, they are <em>linearly dependent</em>.</p>
<p>You may intuitively visualize linear dependence in the 2D plane as two
vectors both pointing in the same direction. Clearly, scaling one vector
will allow us to reach the other vector. Linear independence is
therefore two vectors pointing in different directions.</p>
<p>Of course, this definition applies to vectors in any <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>𝔽</mi><mi>n</mi></msup><annotation encoding="application/x-tex">{\mathbb{F}}^{n}</annotation></semantics></math>.</p>
<h3 id="formal-definition-of-linear-dependence-and-independence">Formal definition of linear dependence and independence</h3>
<p>Let us formally define linear independence for arbitrary vectors in
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>𝔽</mi><mi>n</mi></msup><annotation encoding="application/x-tex">{\mathbb{F}}^{n}</annotation></semantics></math>. Given a set of vectors</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>v</mi><mn>1</mn></msub><mo>,</mo><msub><mi>v</mi><mn>2</mn></msub><mo>,</mo><mi></mi><mo>,</mo><msub><mi>v</mi><mi>n</mi></msub><mo></mo><mi>V</mi></mrow><annotation encoding="application/x-tex">v_{1},v_{2},\ldots,v_{n} \in V</annotation></semantics></math></p>
<p>we say they are linearly independent iff. the equation</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>α</mi><mn>1</mn></msub><msub><mi>v</mi><mn>1</mn></msub><mo>+</mo><msub><mi>α</mi><mn>2</mn></msub><msub><mi>v</mi><mn>2</mn></msub><mo>+</mo><mi></mi><mo>+</mo><msub><mi>α</mi><mi>n</mi></msub><msub><mi>v</mi><mi>n</mi></msub><mo>=</mo><mn>0</mn></mrow><annotation encoding="application/x-tex">\alpha_{1}v_{1} + \alpha_{2}v_{2} + \ldots + \alpha_{n}v_{n} = 0</annotation></semantics></math></p>
<p>has only a unique set of solutions
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>α</mi><mn>1</mn></msub><mo>,</mo><msub><mi>α</mi><mn>2</mn></msub><mo>,</mo><mi></mi><mo>,</mo><msub><mi>α</mi><mi>n</mi></msub></mrow><annotation encoding="application/x-tex">\alpha_{1},\alpha_{2},\ldots,\alpha_{n}</annotation></semantics></math> such that all <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msub><mi>α</mi><mi>n</mi></msub><annotation encoding="application/x-tex">\alpha_{n}</annotation></semantics></math> are
zero.</p>
<p>Equivalently,</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><mo stretchy="true" form="prefix">|</mo><msub><mi>α</mi><mn>1</mn></msub><mo stretchy="true" form="postfix">|</mo></mrow><mo>+</mo><mrow><mo stretchy="true" form="prefix">|</mo><msub><mi>α</mi><mn>2</mn></msub><mo stretchy="true" form="postfix">|</mo></mrow><mo>+</mo><mi></mi><mo>+</mo><mrow><mo stretchy="true" form="prefix">|</mo><msub><mi>α</mi><mi>n</mi></msub><mo stretchy="true" form="postfix">|</mo></mrow><mo>=</mo><mn>0</mn></mrow><annotation encoding="application/x-tex">\left| \alpha_{1} \right| + \left| \alpha_{2} \right| + \ldots + \left| \alpha_{n} \right| = 0</annotation></semantics></math></p>
<p>More precisely,</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><munderover><mo></mo><mrow><mi>i</mi><mo>=</mo><mn>1</mn></mrow><mi>k</mi></munderover><mrow><mo stretchy="true" form="prefix">|</mo><msub><mi>α</mi><mi>i</mi></msub><mo stretchy="true" form="postfix">|</mo></mrow><mo>=</mo><mn>0</mn></mrow><annotation encoding="application/x-tex">\sum_{i = 1}^{k}\left| \alpha_{i} \right| = 0</annotation></semantics></math></p>
<p>Therefore, a set of vectors <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>v</mi><mn>1</mn></msub><mo>,</mo><msub><mi>v</mi><mn>2</mn></msub><mo>,</mo><mi></mi><mo>,</mo><msub><mi>v</mi><mi>m</mi></msub></mrow><annotation encoding="application/x-tex">v_{1},v_{2},\ldots,v_{m}</annotation></semantics></math> is linearly
dependent if the opposite is true, that is there exists solution
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>α</mi><mn>1</mn></msub><mo>,</mo><msub><mi>α</mi><mn>2</mn></msub><mo>,</mo><mi></mi><mo>,</mo><msub><mi>α</mi><mi>m</mi></msub></mrow><annotation encoding="application/x-tex">\alpha_{1},\alpha_{2},\ldots,\alpha_{m}</annotation></semantics></math> to the equation</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>α</mi><mn>1</mn></msub><msub><mi>v</mi><mn>1</mn></msub><mo>+</mo><msub><mi>α</mi><mn>2</mn></msub><msub><mi>v</mi><mn>2</mn></msub><mo>+</mo><mi></mi><mo>+</mo><msub><mi>α</mi><mi>m</mi></msub><msub><mi>v</mi><mi>m</mi></msub><mo>=</mo><mn>0</mn></mrow><annotation encoding="application/x-tex">\alpha_{1}v_{1} + \alpha_{2}v_{2} + \ldots + \alpha_{m}v_{m} = 0</annotation></semantics></math></p>
<p>such that</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><munderover><mo></mo><mrow><mi>i</mi><mo>=</mo><mn>1</mn></mrow><mi>k</mi></munderover><mrow><mo stretchy="true" form="prefix">|</mo><msub><mi>α</mi><mi>i</mi></msub><mo stretchy="true" form="postfix">|</mo></mrow><mo></mo><mn>0</mn></mrow><annotation encoding="application/x-tex">\sum_{i = 1}^{k}\left| \alpha_{i} \right| \neq 0</annotation></semantics></math></p>
<h3 id="basis">Basis</h3>
<p>We say a system of vectors <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>v</mi><mn>1</mn></msub><mo>,</mo><msub><mi>v</mi><mn>2</mn></msub><mo>,</mo><mi></mi><mo>,</mo><msub><mi>v</mi><mi>n</mi></msub><mo></mo><mi>V</mi></mrow><annotation encoding="application/x-tex">v_{1},v_{2},\ldots,v_{n} \in V</annotation></semantics></math> is a <em>basis</em>
in <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>V</mi><annotation encoding="application/x-tex">V</annotation></semantics></math> if the system is both linearly independent and spanning. That is,
the system must be able to represent any vector in <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>V</mi><annotation encoding="application/x-tex">V</annotation></semantics></math> as well as
satisfy our requirements for linear independence.</p>
<p>Equivalently, we may say that a system of vectors in <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>V</mi><annotation encoding="application/x-tex">V</annotation></semantics></math> is a basis in
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>V</mi><annotation encoding="application/x-tex">V</annotation></semantics></math> if any vector <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi><mo></mo><mi>V</mi></mrow><annotation encoding="application/x-tex">v \in V</annotation></semantics></math> admits a <em>unique representation</em> as a linear
combination of vectors in the system. This is equivalent to our previous
statement, that the system must be spanning and linearly independent.</p>
<h3 id="standard-basis">Standard basis</h3>
<p>We may define a <em>standard basis</em> for a vector space. By convention, the
standard basis in <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mn>2</mn></msup><annotation encoding="application/x-tex">{\mathbb{R}}^{2}</annotation></semantics></math> is</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\begin{pmatrix}
1 \\
0
\end{pmatrix}\begin{pmatrix}
0 \\
1
\end{pmatrix}</annotation></semantics></math></p>
<p>Verify that the above is in fact a basis (that is, linearly independent
and generating).</p>
<p>Recalling the definition of the basis, we can represent any vector in
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mn>2</mn></msup><annotation encoding="application/x-tex">{\mathbb{R}}^{2}</annotation></semantics></math> as the linear combination of the standard basis.</p>
<p>Therefore, for any arbitrary vector <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi><mo></mo><msup><mi></mi><mn>2</mn></msup></mrow><annotation encoding="application/x-tex">v \in {\mathbb{R}}^{2}</annotation></semantics></math>, we can
represent it as</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi><mo>=</mo><msub><mi>α</mi><mn>1</mn></msub><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><msub><mi>α</mi><mn>2</mn></msub><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">v = \alpha_{1}\begin{pmatrix}
1 \\
0
\end{pmatrix} + \alpha_{2}\begin{pmatrix}
0 \\
1
\end{pmatrix}</annotation></semantics></math></p>
<p>Let us call <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msub><mi>α</mi><mn>1</mn></msub><annotation encoding="application/x-tex">\alpha_{1}</annotation></semantics></math> and <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msub><mi>α</mi><mn>2</mn></msub><annotation encoding="application/x-tex">\alpha_{2}</annotation></semantics></math> the <em>coordinates</em> of the
vector. Then, we can write <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>v</mi><annotation encoding="application/x-tex">v</annotation></semantics></math> as</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><msub><mi>α</mi><mn>1</mn></msub></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><msub><mi>α</mi><mn>2</mn></msub></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">v = \begin{pmatrix}
\alpha_{1} \\
\alpha_{2}
\end{pmatrix}</annotation></semantics></math></p>
<p>For example, the vector</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>2</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><annotation encoding="application/x-tex">\begin{pmatrix}
1 \\
2
\end{pmatrix}</annotation></semantics></math></p>
<p>represents</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>1</mn><mo></mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><mn>2</mn><mo></mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">1 \cdot \begin{pmatrix}
1 \\
0
\end{pmatrix} + 2 \cdot \begin{pmatrix}
0 \\
1
\end{pmatrix}</annotation></semantics></math></p>
<p>Verify that this aligns with your previous intuition of vectors.</p>
<p>You may recognize the standard basis in <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mn>2</mn></msup><annotation encoding="application/x-tex">{\mathbb{R}}^{2}</annotation></semantics></math> as the
familiar unit vectors</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mover><mi>i</mi><mo accent="true">̂</mo></mover><mo>,</mo><mover><mi>j</mi><mo accent="true">̂</mo></mover></mrow><annotation encoding="application/x-tex">\hat{i},\hat{j}</annotation></semantics></math></p>
<p>This aligns with the fact that</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mi>α</mi></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mi>β</mi></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><mi>α</mi><mover><mi>i</mi><mo accent="true">̂</mo></mover><mo>+</mo><mi>β</mi><mover><mi>j</mi><mo accent="true">̂</mo></mover></mrow><annotation encoding="application/x-tex">\begin{pmatrix}
\alpha \\
\beta
\end{pmatrix} = \alpha\hat{i} + \beta\hat{j}</annotation></semantics></math></p>
<p>However, we may define a standard basis in any arbitrary vector space.
So, let</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>e</mi><mn>1</mn></msub><mo>,</mo><msub><mi>e</mi><mn>2</mn></msub><mo>,</mo><mi></mi><mo>,</mo><msub><mi>e</mi><mi>n</mi></msub></mrow><annotation encoding="application/x-tex">e_{1},e_{2},\ldots,e_{n}</annotation></semantics></math></p>
<p>be a standard basis in <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>𝔽</mi><mi>n</mi></msup><annotation encoding="application/x-tex">{\mathbb{F}}^{n}</annotation></semantics></math>. Then, the coordinates
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>α</mi><mn>1</mn></msub><mo>,</mo><msub><mi>α</mi><mn>2</mn></msub><mo>,</mo><mi></mi><mo>,</mo><msub><mi>α</mi><mi>n</mi></msub></mrow><annotation encoding="application/x-tex">\alpha_{1},\alpha_{2},\ldots,\alpha_{n}</annotation></semantics></math> of a vector
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi><mo></mo><msup><mi>𝔽</mi><mi>n</mi></msup></mrow><annotation encoding="application/x-tex">v \in {\mathbb{F}}^{n}</annotation></semantics></math> represent the following</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><msub><mi>α</mi><mn>1</mn></msub></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><msub><mi>α</mi><mn>2</mn></msub></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mi></mi></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><msub><mi>α</mi><mi>n</mi></msub></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><msub><mi>α</mi><mn>1</mn></msub><msub><mi>e</mi><mn>1</mn></msub><mo>+</mo><msub><mi>α</mi><mn>2</mn></msub><mo>+</mo><msub><mi>e</mi><mn>2</mn></msub><mo>+</mo><msub><mi>α</mi><mi>n</mi></msub><msub><mi>e</mi><mi>n</mi></msub></mrow><annotation encoding="application/x-tex">\begin{pmatrix}
\alpha_{1} \\
\alpha_{2} \\
\vdots \\
\alpha_{n}
\end{pmatrix} = \alpha_{1}e_{1} + \alpha_{2} + e_{2} + \alpha_{n}e_{n}</annotation></semantics></math></p>
<p>Using our new notation, the standard basis in <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mn>2</mn></msup><annotation encoding="application/x-tex">{\mathbb{R}}^{2}</annotation></semantics></math> is</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>e</mi><mn>1</mn></msub><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo>,</mo><msub><mi>e</mi><mn>2</mn></msub><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">e_{1} = \begin{pmatrix}
1 \\
0
\end{pmatrix},e_{2} = \begin{pmatrix}
0 \\
1
\end{pmatrix}</annotation></semantics></math></p>
<h2 id="matrices">Matrices</h2>
<p>Before discussing any properties of matrices, lets simply reiterate
what we learned in class about their notation. We say a matrix with rows
of length <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>m</mi><annotation encoding="application/x-tex">m</annotation></semantics></math>, and columns of size <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>n</mi><annotation encoding="application/x-tex">n</annotation></semantics></math> (in less precise terms, a matrix
with length <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>m</mi><annotation encoding="application/x-tex">m</annotation></semantics></math> and height <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>n</mi><annotation encoding="application/x-tex">n</annotation></semantics></math>) is a <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>m</mi><mo>×</mo><mi>n</mi></mrow><annotation encoding="application/x-tex">m \times n</annotation></semantics></math> matrix.</p>
<p>Given a matrix</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>A</mi><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>2</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>3</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>4</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>5</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>6</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>7</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>8</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>9</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">A = \begin{pmatrix}
1 &amp; 2 &amp; 3 \\
4 &amp; 5 &amp; 6 \\
7 &amp; 8 &amp; 9
\end{pmatrix}</annotation></semantics></math></p>
<p>we refer to the entry in row <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>j</mi><annotation encoding="application/x-tex">j</annotation></semantics></math> and column <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>k</mi><annotation encoding="application/x-tex">k</annotation></semantics></math> as <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msub><mi>A</mi><mrow><mi>j</mi><mo>,</mo><mi>k</mi></mrow></msub><annotation encoding="application/x-tex">A_{j,k}</annotation></semantics></math> .</p>
<h3 id="matrix-transpose">Matrix transpose</h3>
<p>A formalism that is useful later on is called the <em>transpose</em>, and we
obtain it from a matrix <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>A</mi><annotation encoding="application/x-tex">A</annotation></semantics></math> by switching all the rows and columns. More
precisely, each row becomes a column instead. We use the notation
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>A</mi><mi>T</mi></msup><annotation encoding="application/x-tex">A^{T}</annotation></semantics></math> to represent the transpose of <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>A</mi><annotation encoding="application/x-tex">A</annotation></semantics></math>.</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msup><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>2</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>3</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>4</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>5</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>6</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mi>T</mi></msup><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>4</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>2</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>5</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>3</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>6</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\begin{pmatrix}
1 &amp; 2 &amp; 3 \\
4 &amp; 5 &amp; 6
\end{pmatrix}^{T} = \begin{pmatrix}
1 &amp; 4 \\
2 &amp; 5 \\
3 &amp; 6
\end{pmatrix}</annotation></semantics></math></p>
<p>Formally, we can say <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mrow><mo stretchy="true" form="prefix">(</mo><msup><mi>A</mi><mi>T</mi></msup><mo stretchy="true" form="postfix">)</mo></mrow><mrow><mi>j</mi><mo>,</mo><mi>k</mi></mrow></msub><mo>=</mo><msub><mi>A</mi><mrow><mi>k</mi><mo>,</mo><mi>j</mi></mrow></msub></mrow><annotation encoding="application/x-tex">\left( A^{T} \right)_{j,k} = A_{k,j}</annotation></semantics></math></p>
<h2 id="linear-transformations">Linear transformations</h2>
<p>A linear transformation <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>T</mi><mo>:</mo><mi>V</mi><mo></mo><mi>W</mi></mrow><annotation encoding="application/x-tex">T:V \rightarrow W</annotation></semantics></math> is a mapping between two
vector spaces <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>V</mi><mo></mo><mi>W</mi></mrow><annotation encoding="application/x-tex">V \rightarrow W</annotation></semantics></math>, such that the following axioms are
satisfied:</p>
<ol>
<li><p><math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>T</mi><mrow><mo stretchy="true" form="prefix">(</mo><mi>v</mi><mo>+</mo><mi>w</mi><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><mi>T</mi><mrow><mo stretchy="true" form="prefix">(</mo><mi>v</mi><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><mi>T</mi><mrow><mo stretchy="true" form="prefix">(</mo><mi>w</mi><mo stretchy="true" form="postfix">)</mo></mrow><mo>,</mo><mo></mo><mi>v</mi><mo></mo><mi>V</mi><mo>,</mo><mo></mo><mi>w</mi><mo></mo><mi>W</mi></mrow><annotation encoding="application/x-tex">T(v + w) = T(v) + T(w),\forall v \in V,\forall w \in W</annotation></semantics></math></p></li>
<li><p><math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>T</mi><mrow><mo stretchy="true" form="prefix">(</mo><mi>α</mi><mi>v</mi><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><mi>T</mi><mrow><mo stretchy="true" form="prefix">(</mo><mi>β</mi><mi>w</mi><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><mi>α</mi><mi>T</mi><mrow><mo stretchy="true" form="prefix">(</mo><mi>v</mi><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><mi>β</mi><mi>T</mi><mrow><mo stretchy="true" form="prefix">(</mo><mi>w</mi><mo stretchy="true" form="postfix">)</mo></mrow><mo>,</mo><mo></mo><mi>v</mi><mo></mo><mi>V</mi><mo>,</mo><mo></mo><mi>w</mi><mo></mo><mi>W</mi></mrow><annotation encoding="application/x-tex">T(\alpha v) + T(\beta w) = \alpha T(v) + \beta T(w),\forall v \in V,\forall w \in W</annotation></semantics></math>,
for all scalars <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>α</mi><mo>,</mo><mi>β</mi></mrow><annotation encoding="application/x-tex">\alpha,\beta</annotation></semantics></math></p></li>
</ol>
<p><em>Definition</em>. <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>T</mi><annotation encoding="application/x-tex">T</annotation></semantics></math> is a linear transformation iff.</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>T</mi><mrow><mo stretchy="true" form="prefix">(</mo><mi>α</mi><mi>v</mi><mo>+</mo><mi>β</mi><mi>w</mi><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><mi>α</mi><mi>T</mi><mrow><mo stretchy="true" form="prefix">(</mo><mi>v</mi><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><mi>β</mi><mi>T</mi><mrow><mo stretchy="true" form="prefix">(</mo><mi>w</mi><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">T(\alpha v + \beta w) = \alpha T(v) + \beta T(w)</annotation></semantics></math></p>
<p><em>Abuse of notation</em>. From now on, we may elide the parentheses and say
that <math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>T</mi><mrow><mo stretchy="true" form="prefix">(</mo><mi>v</mi><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><mi>T</mi><mi>v</mi><mo>,</mo><mo></mo><mi>v</mi><mo></mo><mi>V</mi></mrow><annotation encoding="application/x-tex">T(v) = Tv,\forall v \in V</annotation></semantics></math></p>
<p><em>Remark</em>. A phrase that you may commonly hear is that linear
transformations preserve <em>linearity</em>. Essentially, straight lines remain
straight, parallel lines remain parallel, and the origin remains fixed
at 0. Take a moment to think about why this is true (at least, in lower
dimensional spaces you can visualize).</p>
<p><em>Examples</em>.</p>
<ol>
<li><p>Rotation for <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>V</mi><mo>=</mo><mi>W</mi><mo>=</mo><msup><mi></mi><mn>2</mn></msup></mrow><annotation encoding="application/x-tex">V = W = {\mathbb{R}}^{2}</annotation></semantics></math> (i.e. rotation in 2
dimensions). Given <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi><mo>,</mo><mi>w</mi><mo></mo><msup><mi></mi><mn>2</mn></msup></mrow><annotation encoding="application/x-tex">v,w \in {\mathbb{R}}^{2}</annotation></semantics></math>, and their linear
combination <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi><mo>+</mo><mi>w</mi></mrow><annotation encoding="application/x-tex">v + w</annotation></semantics></math>, a rotation of <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>γ</mi><annotation encoding="application/x-tex">\gamma</annotation></semantics></math> radians of <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi><mo>+</mo><mi>w</mi></mrow><annotation encoding="application/x-tex">v + w</annotation></semantics></math> is
equivalent to first rotating <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>v</mi><annotation encoding="application/x-tex">v</annotation></semantics></math> and <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>w</mi><annotation encoding="application/x-tex">w</annotation></semantics></math> individually by <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>γ</mi><annotation encoding="application/x-tex">\gamma</annotation></semantics></math>
and then taking their linear combination.</p></li>
<li><p>Differentiation of polynomials. In this case <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>V</mi><mo>=</mo><msup><mi></mi><mi>n</mi></msup></mrow><annotation encoding="application/x-tex">V = {\mathbb{P}}^{n}</annotation></semantics></math>
and <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>W</mi><mo>=</mo><msup><mi></mi><mrow><mi>n</mi><mo></mo><mn>1</mn></mrow></msup></mrow><annotation encoding="application/x-tex">W = {\mathbb{P}}^{n - 1}</annotation></semantics></math>, where <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mi>n</mi></msup><annotation encoding="application/x-tex">{\mathbb{P}}^{n}</annotation></semantics></math> is the
field of all polynomials of degree at most <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>n</mi><annotation encoding="application/x-tex">n</annotation></semantics></math>.</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mfrac><mi>d</mi><mrow><mi>d</mi><mi>x</mi></mrow></mfrac><mrow><mo stretchy="true" form="prefix">(</mo><mi>α</mi><mi>v</mi><mo>+</mo><mi>β</mi><mi>w</mi><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><mi>α</mi><mfrac><mi>d</mi><mrow><mi>d</mi><mi>x</mi></mrow></mfrac><mi>v</mi><mo>+</mo><mi>β</mi><mfrac><mi>d</mi><mrow><mi>d</mi><mi>x</mi></mrow></mfrac><mi>w</mi><mo>,</mo><mo></mo><mi>v</mi><mo></mo><mi>V</mi><mo>,</mo><mi>w</mi><mo></mo><mi>W</mi><mo>,</mo><mo></mo><mrow><mspace width="0.333em"></mspace><mtext mathvariant="normal"> scalars </mtext><mspace width="0.333em"></mspace></mrow><mi>α</mi><mo>,</mo><mi>β</mi></mrow><annotation encoding="application/x-tex">\frac{d}{dx}(\alpha v + \beta w) = \alpha\frac{d}{dx}v + \beta\frac{d}{dx}w,\forall v \in V,w \in W,\forall\text{ scalars }\alpha,\beta</annotation></semantics></math></p></li>
</ol>
<h2 id="matrices-represent-linear-transformations">Matrices represent linear transformations</h2>
<p>Suppose we wanted to represent a linear transformation
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>T</mi><mo>:</mo><msup><mi>𝔽</mi><mi>n</mi></msup><mo></mo><msup><mi>𝔽</mi><mi>m</mi></msup></mrow><annotation encoding="application/x-tex">T:{\mathbb{F}}^{n} \rightarrow {\mathbb{F}}^{m}</annotation></semantics></math>. I propose that we
need encode how <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>T</mi><annotation encoding="application/x-tex">T</annotation></semantics></math> acts on the standard basis of <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>𝔽</mi><mi>n</mi></msup><annotation encoding="application/x-tex">{\mathbb{F}}^{n}</annotation></semantics></math>.</p>
<p>Using our intuition from lower dimensional vector spaces, we know that
the standard basis in <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mn>2</mn></msup><annotation encoding="application/x-tex">{\mathbb{R}}^{2}</annotation></semantics></math> is the unit vectors <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mover><mi>i</mi><mo accent="true">̂</mo></mover><annotation encoding="application/x-tex">\hat{i}</annotation></semantics></math>
and <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mover><mi>j</mi><mo accent="true">̂</mo></mover><annotation encoding="application/x-tex">\hat{j}</annotation></semantics></math>. Because linear transformations preserve linearity (i.e.
all straight lines remain straight and parallel lines remain parallel),
we can encode any transformation as simply changing <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mover><mi>i</mi><mo accent="true">̂</mo></mover><annotation encoding="application/x-tex">\hat{i}</annotation></semantics></math> and
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mover><mi>j</mi><mo accent="true">̂</mo></mover><annotation encoding="application/x-tex">\hat{j}</annotation></semantics></math>. And indeed, if any vector <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi><mo></mo><msup><mi></mi><mn>2</mn></msup></mrow><annotation encoding="application/x-tex">v \in {\mathbb{R}}^{2}</annotation></semantics></math> can be
represented as the linear combination of <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mover><mi>i</mi><mo accent="true">̂</mo></mover><annotation encoding="application/x-tex">\hat{i}</annotation></semantics></math> and <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mover><mi>j</mi><mo accent="true">̂</mo></mover><annotation encoding="application/x-tex">\hat{j}</annotation></semantics></math> (this
is the definition of a basis), it makes sense both symbolically and
geometrically that we can represent all linear transformations as the
transformations of the basis vectors.</p>
<p><em>Example</em>. To reflect all vectors <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi><mo></mo><msup><mi></mi><mn>2</mn></msup></mrow><annotation encoding="application/x-tex">v \in {\mathbb{R}}^{2}</annotation></semantics></math> across the
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>y</mi><annotation encoding="application/x-tex">y</annotation></semantics></math>-axis, we can simply change the standard basis to</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mi></mi><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\begin{pmatrix}
- 1 \\
0
\end{pmatrix}\begin{pmatrix}
0 \\
1
\end{pmatrix}</annotation></semantics></math></p>
<p>Then, any vector in <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mn>2</mn></msup><annotation encoding="application/x-tex">{\mathbb{R}}^{2}</annotation></semantics></math> using this new basis will be
reflected across the <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>y</mi><annotation encoding="application/x-tex">y</annotation></semantics></math>-axis. Take a moment to justify this
geometrically.</p>
<h3 id="writing-a-linear-transformation-as-matrix">Writing a linear transformation as matrix</h3>
<p>For any linear transformation
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>T</mi><mo>:</mo><msup><mi>𝔽</mi><mi>m</mi></msup><mo></mo><msup><mi>𝔽</mi><mi>n</mi></msup></mrow><annotation encoding="application/x-tex">T:{\mathbb{F}}^{m} \rightarrow {\mathbb{F}}^{n}</annotation></semantics></math>, we can write it as an
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>n</mi><mo>×</mo><mi>m</mi></mrow><annotation encoding="application/x-tex">n \times m</annotation></semantics></math> matrix <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>A</mi><annotation encoding="application/x-tex">A</annotation></semantics></math>. That is, there is a matrix <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>A</mi><annotation encoding="application/x-tex">A</annotation></semantics></math> with <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>n</mi><annotation encoding="application/x-tex">n</annotation></semantics></math> rows
and <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>m</mi><annotation encoding="application/x-tex">m</annotation></semantics></math> columns that can represent any linear transformation from
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msup><mi>𝔽</mi><mi>m</mi></msup><mo></mo><msup><mi>𝔽</mi><mi>n</mi></msup></mrow><annotation encoding="application/x-tex">{\mathbb{F}}^{m} \rightarrow {\mathbb{F}}^{n}</annotation></semantics></math>.</p>
<p>How should we write this matrix? Naturally, from our previous
discussion, we should write a matrix with each <em>column</em> being one of our
new transformed <em>basis</em> vectors.</p>
<p><em>Example</em>. Our <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>y</mi><annotation encoding="application/x-tex">y</annotation></semantics></math>-axis reflection transformation from earlier. We write
the bases in a matrix</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mi></mi><mn>1</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><annotation encoding="application/x-tex">\begin{pmatrix}
- 1 &amp; 0 \\
0 &amp; 1
\end{pmatrix}</annotation></semantics></math></p>
<h3 id="matrix-vector-multiplication">Matrix-vector multiplication</h3>
<p>Perhaps you now see why the so-called matrix-vector multiplication is
defined the way it is. Recalling our definition of a basis, given a
basis in <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>V</mi><annotation encoding="application/x-tex">V</annotation></semantics></math>, any vector <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi><mo></mo><mi>V</mi></mrow><annotation encoding="application/x-tex">v \in V</annotation></semantics></math> can be written as the linear
combination of the vectors in the basis. Then, given a linear
transformation represented by the matrix containing the new basis, we
simply write the linear combination with the new basis instead.</p>
<p><em>Example</em>. Let us first write a vector in the standard basis in
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi></mi><mn>2</mn></msup><annotation encoding="application/x-tex">{\mathbb{R}}^{2}</annotation></semantics></math> and then show how our matrix-vector multiplication
naturally corresponds to the definition of the linear transformation.</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>2</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo></mo><msup><mi></mi><mn>2</mn></msup></mrow><annotation encoding="application/x-tex">\begin{pmatrix}
1 \\
2
\end{pmatrix} \in {\mathbb{R}}^{2}</annotation></semantics></math></p>
<p>is the same as</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>1</mn><mo></mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><mn>2</mn><mo></mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">1 \cdot \begin{pmatrix}
1 \\
0
\end{pmatrix} + 2 \cdot \begin{pmatrix}
0 \\
1
\end{pmatrix}</annotation></semantics></math></p>
<p>Then, to perform our reflection, we need only replace the basis vector
<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><annotation encoding="application/x-tex">\begin{pmatrix}
1 \\
0
\end{pmatrix}</annotation></semantics></math> with <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mi></mi><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><annotation encoding="application/x-tex">\begin{pmatrix}
- 1 \\
0
\end{pmatrix}</annotation></semantics></math>.</p>
<p>Then, the reflected vector is given by</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>1</mn><mo></mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mi></mi><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><mn>2</mn><mo></mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mi></mi><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>2</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">1 \cdot \begin{pmatrix}
- 1 \\
0
\end{pmatrix} + 2 \cdot \begin{pmatrix}
0 \\
1
\end{pmatrix} = \begin{pmatrix}
- 1 \\
2
\end{pmatrix}</annotation></semantics></math></p>
<p>We can clearly see that this is exactly how the matrix multiplication</p>
<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mi></mi><mn>1</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>0</mn></mtd><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow><mo></mo><mrow><mo stretchy="true" form="prefix">(</mo><mtable><mtr><mtd columnalign="center" style="text-align: center"><mn>1</mn></mtd></mtr><mtr><mtd columnalign="center" style="text-align: center"><mn>2</mn></mtd></mtr></mtable><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\begin{pmatrix}
- 1 &amp; 0 \\
0 &amp; 1
\end{pmatrix} \cdot \begin{pmatrix}
1 \\
2
\end{pmatrix}</annotation></semantics></math> is defined! The <em>column-by-coordinate</em> rule for
matrix-vector multiplication says that we multiply the <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>n</mi><mtext mathvariant="normal">th</mtext></msup><annotation encoding="application/x-tex">n^{\text{th}}</annotation></semantics></math>
entry of the vector by the corresponding <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msup><mi>n</mi><mtext mathvariant="normal">th</mtext></msup><annotation encoding="application/x-tex">n^{\text{th}}</annotation></semantics></math> column of the
matrix and sum them all up (take their linear combination). This
algorithm intuitively follows from our definition of matrices.</p>
<h3 id="matrix-matrix-multiplication">Matrix-matrix multiplication</h3>
<p>As you may have noticed, a very similar natural definition arises for
the <em>matrix-matrix</em> multiplication. Multiplying two matrices <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>A</mi><mo></mo><mi>B</mi></mrow><annotation encoding="application/x-tex">A \cdot B</annotation></semantics></math>
is essentially just taking each column of <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>B</mi><annotation encoding="application/x-tex">B</annotation></semantics></math>, and applying the linear
transformation defined by the matrix <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>A</mi><annotation encoding="application/x-tex">A</annotation></semantics></math>!</p></main>
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