Chapter 4: Problem 12
How are the components of a vector related to its magnitude?
Short Answer
Expert verified
The magnitude of a vector is found by taking the square root of the sum of the squares of its components.
Step by step solution
01
Understanding the Problem
To find the relationship between the components of a vector and its magnitude, we first need to understand what a vector is. A vector is an object that has both a magnitude, or length, and a direction. It can be represented in a coordinate system by components along each axis.
02
Defining the Vector Components
Consider a vector \( \vec{v} \) in a 2D space, composed of components \( v_x \) and \( v_y \) along the x and y axes, respectively. This vector can be written as \( \vec{v} = (v_x, v_y) \).
03
Applying the Pythagorean Theorem
The magnitude of a vector \( \vec{v} = (v_x, v_y) \) in 2D can be found using the Pythagorean Theorem. This theorem relates the components of the vector to its magnitude: it states that the magnitude \( |\vec{v}| \) is given by \( |\vec{v}| = \sqrt{v_x^2 + v_y^2} \).
04
Generalizing to 3D
For a vector in 3D space, \( \vec{v} = (v_x, v_y, v_z) \), the magnitude is found using a similar extension of the Pythagorean Theorem: \( |\vec{v}| = \sqrt{v_x^2 + v_y^2 + v_z^2} \). This shows how each component contributes to the overall length of the vector.
05
Summarizing the Relationship
The components of a vector are directly related to its magnitude by forming a squared sum under a square root. This means each component contributes to increasing the magnitude of the vector.
Unlock Step-by-Step Solutions & Ace Your Exams!
-
Full Textbook Solutions
Get detailed explanations and key concepts
-
Unlimited Al creation
Al flashcards, explanations, exams and more...
-
Ads-free access
To over 500 millions flashcards
-
Money-back guarantee
We refund you if you fail your exam.
Over 30 million students worldwide already upgrade their learning with Vaia!
Key Concepts
These are the key concepts you need to understand to accurately answer the question.
Vector Components
When we talk about vector components, we refer to the building blocks of a vector in a coordinate system. Imagine a vector as a line pointing towards a direction. This line can be broken down into parts that line up along the coordinate axes.
In a 2D space, these axes are usually the x and y-axes. A vector can thus be expressed in terms of its components as \( \vec{v} = (v_x, v_y) \), where \( v_x \) and \( v_y \) are the projections on the x-axis and y-axis respectively. These projections, or components, define how much of your vector lies in each axis.
This idea extends to 3D space as well, where a vector can be written as \( \vec{v} = (v_x, v_y, v_z) \), adding a z-component to capture depth or height. Here's how these work in practice:
In a 2D space, these axes are usually the x and y-axes. A vector can thus be expressed in terms of its components as \( \vec{v} = (v_x, v_y) \), where \( v_x \) and \( v_y \) are the projections on the x-axis and y-axis respectively. These projections, or components, define how much of your vector lies in each axis.
This idea extends to 3D space as well, where a vector can be written as \( \vec{v} = (v_x, v_y, v_z) \), adding a z-component to capture depth or height. Here's how these work in practice:
- 2D Vector Example: If a person walks diagonally on a flat plane (like a piece of paper), we can describe their movement using components along the x (east-west) and y (north-south) directions.
- 3D Vector Example: A bird flying would have components that express its movement forward, sideways, and upward.
Pythagorean Theorem
The Pythagorean Theorem is a powerful tool that helps us measure the distance or magnitude of a vector, especially in geometric contexts.
When dealing with 2D vectors, the theorem states that the square of the hypotenuse (in this case, the vector's magnitude) is equal to the sum of the squares of the other two sides (the vector's components). For a vector \( \vec{v} = (v_x, v_y) \), this converts to the formula \( |\vec{v}| = \sqrt{v_x^2 + v_y^2} \).
Let's break it down:
When dealing with 2D vectors, the theorem states that the square of the hypotenuse (in this case, the vector's magnitude) is equal to the sum of the squares of the other two sides (the vector's components). For a vector \( \vec{v} = (v_x, v_y) \), this converts to the formula \( |\vec{v}| = \sqrt{v_x^2 + v_y^2} \).
Let's break it down:
- Measurement: This formula ensures we can calculate a single value representing the vector's "length" from its components.
- Visual Aid: If you draw a vector as a right triangle, its components are the other sides, and the vector itself is the hypotenuse.
- Intuition: Each component contributes to the vector's magnitude because they act like small vectors combined into a bigger one.
3D Vectors
Much like 2D vectors, 3D vectors have components, but they also consider the third dimension—often representing depth or height. This is crucial when describing anything that moves or exists in our three-dimensional world.
A vector in 3D can be represented as \( \vec{v} = (v_x, v_y, v_z) \), where each component corresponds to an axis in space. Calculating its magnitude involves extending the Pythagorean Theorem:
\[ |\vec{v}| = \sqrt{v_x^2 + v_y^2 + v_z^2} \]
Here's why this is important:
A vector in 3D can be represented as \( \vec{v} = (v_x, v_y, v_z) \), where each component corresponds to an axis in space. Calculating its magnitude involves extending the Pythagorean Theorem:
\[ |\vec{v}| = \sqrt{v_x^2 + v_y^2 + v_z^2} \]
Here's why this is important:
- Real World Applications: Whether engineering a building by calculating stress in beams or tracking a plane’s flight path, this magnitude provides critical insights.
- Visualization: Visualizing these vectors can help in understanding the spatial orientation and distance of complex 3D objects.
- Unified Approach: Understanding 3D vectors' magnitude reinforces the relation between a vector's direction and length through its components.