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Customizing Markdown: Interactive Vector Math

Inner Product Space Header

Welcome to a demonstration of how we can transform standard Markdown into a rich, textbook-quality learning experience. Instead of just static text, we use custom Astro components to create interactive notes, figures, and callouts.

Let’s explore Inner Product Spaces to see these components in action.

Section 1.1 Introduction

1. Vector Visualization

When we talk about vectors in R2\mathbb{R}^2, we often visualize them as arrows starting from the origin (0,0)(0,0).

ℹ️ Definition

A Vector vv in the plane can be represented as a coordinate pair (a,b)(a, b), which corresponds to an arrow from the origin to the point (a,b)(a, b).

v=ai^+bj^v = a\hat{i} + b\hat{j}

Here is a visual representation of two vectors, (1,2)(1, 2) and (1,1)(-1, -1).

Vector Grid Visualization
Figure 1.2: Visualization of vectors (1, 2) and (-1, -1) on the Cartesian plane.

Notice how clearly the grid helps in identifying the components. This isn’t just an image; it’s a styled CaptionedFigure component that ensures consistent alignment and caption styling across the site.

2. Vector Addition

How do we add vectors? Geometrically, we follow the Parallelogram Law.

💡 The Parallelogram Law

If you have two vectors vv and ww, their sum v+wv + w is the diagonal of the parallelogram formed by vv and ww.

Parallelogram Rule
Visualizing vector addition v + w using the parallelogram rule.

numerical Example

Let’s try precise addition. If we have:

  • v=(1,2)v = (1, 2)
  • w=(2,1)w = (2, 1)

Then v+w=(1+2,2+1)=(3,3)v + w = (1+2, 2+1) = (3, 3).

Vector Addition Grid
Figure 1.4: Visualization of vector addition (1,2) + (2,1) = (3,3).
⚠️ Common Mistake

Remember that vector addition is component-wise. You cannot simply add the magnitudes together! v+wv+w|v + w| \neq |v| + |w| (unless they are collinear)

3. Quick Concept Review

We can also use interactive cards to summarize key concepts for the student.

🧠

Inner Product

A generalized way to multiply vectors that gives us a scalar. It allows us to define angles and lengths.

📐

Orthogonality

Two vectors are orthogonal (perpendicular) if their inner product is zero. v,w=0\langle v, w \rangle = 0


How this page is built

This entire page is written in Markdown (MDX).

  • The blue boxes are <Callout> components.
  • The images are <CaptionedFigure> components.
  • The cards above are <ConceptCard> components.

This allows us to write educational content as easily as writing a document, while keeping the output beautiful and distinct.