# Understanding and Implementing Cross Product in MATLAB

This article aims to introduce readers to the concept of cross product in MATLAB. It will provide an in-depth explanation about what it is, its applications, and how to effectively use this operation …

Updated October 3, 2023

This article aims to introduce readers to the concept of cross product in MATLAB. It will provide an in-depth explanation about what it is, its applications, and how to effectively use this operation within your MATLAB code. We will also include several code samples that demonstrate different ways to implement a cross product to help you gain a better understanding of this mathematical tool.

## Introduction

The cross product in MATLAB is a crucial concept for engineers, scientists, and researchers who work with vector algebra. It helps to understand various properties of vectors and their relationships to each other. In this article, we will look at the theory behind the cross product, its applications, and some practical examples of how you can perform it within MATLAB.

What is Cross Product?

The term “cross product” refers to a specific kind of product between two vectors. It has no immediate counterpart in linear algebra operations but rather resides in the realm of vector calculus, which primarily deals with vector spaces, functions, and differentiation and integration over manifolds. A cross product between two three-dimensional vectors generates a third vector that is perpendicular to both of them.

Properties of Cross Product

Some important properties of the cross product include:

1. The resultant vector is always orthogonal (perpendicular) to both input vectors, as illustrated in Figure 1.
2. It is not commutative, meaning that A × B and B × A are generally different for non-commutative vector spaces like R3.
3. It is anti-symmetric, which means that if you interchange the order of your vectors or change their sign, the result changes in such a way that it remains invariant under these actions: (A × B) = -(B × A).
4. The magnitude of the cross product between two vectors is given by the volume of the parallelepiped determined by those two vectors and the unit vector normal to them. This concept may also be referred to as the “parallelogram law” due to its visual similarity with a parallelogram.

Figure 1: Cross Product Resulting in an Orthogonal Vector

Applications of Cross Product

Cross products are useful for various applications, particularly in computer graphics and engineering fields like robotics. Here are some common use cases where cross product plays a vital role:

1. Calculate the normal vector to a surface given two non-parallel vectors that are tangent to it: Use the cross product of the two vectors to obtain a vector that is perpendicular to both, resulting in a unit normal vector pointing outward from the surface at the point where the two vectors intersect.
2. Calculate the moment of inertia of an object: The moment of inertia can be used for assessing the resistance of an object to rotation or change in angular velocity. The cross product between the mass and the radius vector is useful in computing the angular momentum of a rotating system.
3. Determine the orientation of an aircraft during flight: By understanding the relationship between the body axes, velocity, and gravitational forces on an aircraft, we can use cross products to derive its attitude quaternion, which helps determine the current orientation.
4. Constructing a vector field representation for analyzing fluid flow, electric fields, or magnetic fields: Vector calculus provides useful tools like divergence, gradient, curl, and the dot product for this purpose. The cross product is essential in computing the curl of a vector field, which indicates the vorticity within the field.
5. Robotics manipulation tasks: In robotics, using the concept of a cross product can help control robotic arms by understanding their positioning, orientation, and movement relative to other objects in the environment.

Implementing Cross Product in MATLAB

MATLAB provides several functions that you may use to calculate the cross product between vectors. Here are three common methods for performing a cross product operation:

1. The built-in `cross` function is designed specifically for calculating cross products between two 3D vectors (represented as column vectors). You can easily input your vector data and apply this function to obtain the result. For example, if we have vectors A = [1 2 3] and B = [4 5 6], you could find their cross product with:
``````C = cross(A,B)
``````

The output vector C would be [7 -10 6]. Note that if the vectors A and B are not of equal size (i.e., not all containing three elements), MATLAB will throw an error.

1. The `mtimes` function in MATLAB can also be used to find a cross product by using customized multiplication rules defined for a particular operation. To implement the cross product with this method, you would need to define your own mtimes rule as follows:
``````function C = mtimes(A, B)
% A and B are 3-dimensional column vectors
C = [B(2) * A(3) - A(2) * B(3), A(3) * B(1) - A(1) * B(3), A(1) * B(2) - A(2) * B(1)]
end
``````

Now, you can use the custom mtimes function to calculate the cross product:

``````C = mtimes(A,B)
``````
1. The `crossprod` function works similarly to the built-in `cross` function but operates on 2D vectors rather than 3D ones. If you have vectors A and B as before, but now both contain only two elements each (e.g., [1 2] and [4 5]), you can use `crossprod` like this:
``````C = crossprod(A,B)
``````

The result C will be [6 -3]. Note that if the length of either A or B is not equal to 2, MATLAB will throw an error.

Conclusion

This article has provided a comprehensive understanding of the cross product in MATLAB, its applications in various fields, and how you can effectively implement this concept within your code using different built-in functions or custom methods. Understanding and utilizing the cross product is crucial for scientists, engineers, and researchers who work with vector algebra and vector calculus to solve complex problems related to fluid dynamics, computer graphics, robotics, and more.