Last updated: September 10, 2023
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What’s The Difference Between A Dot Product And A Cross Product Of A Vector? (Explained)
Last updated: September 10, 2023
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Mathematics is a broad field that involves exploring and understanding numerical, spatial, and logical relationships. It deals with developing the intent of theories, principles, and methods for describing and analyzing quantities, shapes, patterns, and structures.
Mathematics can be divided into several sub-fields: algebra, geometry, trigonometry, calculus, statistics, etc. Each sub-field focuses on specific aspects of mathematical concepts and theories, diffusing different tools and techniques, problems, and proving theorems.
While both entail multiplying the magnitudes of two vectors, the cross product yields a vector which represents magnitude and direction, as opposed to the dot product which produces a scalar quantity that only indicates magnitude.
Mathematics plays an essential wide range, overloading science, engineering, economics, finance, technology, and many more. Its importance in our daily lives cannot be overstated, from calculating tips at a restaurant to predicting stock prices and designing buildings and bridges.
What is a Vector?
A vector is a mathematical object with both magnitude and direction of mathematics. A vector can be represented by an ordered list of numbers, called its components, or by an arrow in space, which means the direction and magnitude of the vector.
Vector can epitomize various physical quantities, such as velocity, force, or acceleration. For example, suppose you want to represent the velocity of an object in two dimensions. In that case, you can use a vector with two components: the x-component representing the horizontal speed and the y-component representing the vertical speed.
Vectors can be added, subtracted, and multiplied by scalar values. When two vectors are added, the resulting vector is the sum of their components. When a vector is increased or grown by a scalar value, the resulting vector is a new vector with an equal direction or path but a diverse magnitude.
Vectors are used in various mathematical applications, such as calculus, linear algebra, and differential equations. They are also used in physics, engineering, and computer graphics, among other fields.
Is Vector Part of Geometry?
Vector is a fundamental part of geometry. In mathematics, a vector is an entity that has both magnitude and direction.
Vectors denote physical quantities such as velocity, force, and acceleration and describe geometric objects such as points, lines, and planes.
In geometry, vectors often represent line segments, with the vector pointing from the initial to the terminal fact. Vectors can also be used to describe geometric transformations such as translations, rotations, and reflections.
Vectors are used in various mathematical applications such as calculus, linear algebra, and differential equations. Therefore, vectors play a crucial role in geometry and are a fundamental concept in many areas of mathematics and science.
What is a Dot Product?
The dot product, or the scalar product or inner product, is a mathematical operation between two vectors that results in a scalar quantity.
A dot product of two vectors, a and b, are defined as the sum of the products of their corresponding components:
- A · b = a1b1 + a2b2 + a3b3 + … + anbn
- Where a1, a2, a3, …, an and b1, b2, b3, …, bn are the components of vectors a and b, respectively.
The dot product can be used to calculate the angle between two vectors, determine whether two vectors are orthogonal (perpendicular), find the projection of a vector onto another vector, and solve systems of linear equations.
It also plays a crucial role in linear algebra, a branch of mathematics that deals with vector spaces and linear transformations.
Dot Products Matrix
In linear algebra, the dot product between two vectors can also be represented as a matrix multiplication called the dot product matrix or the symmetric matrix. This matrix is defined as follows:
Given two vectors A = [a1, a2, a3] and B = [b1, b2, b3], the dot product matrix of A is:
[ a1*a1 a1*a2 a1*a3]
[ a1*a2 a2*a2 a2*a3]
[ a1*a3 a2*a3 a3*a3]
And the dot product matrix of B is:
[ b1*b1 b1*b2 b1*b3]
[ b1*b2 b2*b2 b2*b3]
[ b1*b3 b2*b3 b3*b3]
Note that this matrix is symmetric, meaning that its transpose equals itself. Also, the dot product of A and B can be computed by taking the matrix product of the dot product matrix of A with B (or vice versa):
A. B = [ a1*a1 a1*a2 a1*a3 ] [ b1 ]
[ a1*a2 a2*a2 a2*a3] [ b2]
[ a1*a3 a2*a3 a3*a3] [ b3]
= a1*b1 + a2*b2 + a3*b3
It is equivalent to the formula we gave earlier for the dot product of two vectors. The advantage of using the dot product matrix is that it allows us to perform the dot product operation using matrix multiplication, which can be useful in certain applications, such as machine learning and signal processing.
What is a Cross-Product?
Cross-product, also known as the vector product or outer product, is a binary operation between two vectors in three-dimensional space that results in a new vector orthogonal (perpendicular) to both original vectors.
The cross-product of two vectors a and b is represented by an x b and is defined as:
A x b = |a||b| sin(theta) n
Where |a| and |b| are the extents of vectors a and b, theta is the angle between them, and n is a unit vector perpendicular to both a and b.
The right-hand rule determines the direction of n: the finger of the right hand is curved in the directive from a to b, and the thumb points in the objective of the cross-product. The cross-product has several significant applications in mathematics, physics, engineering, and computer graphics.
It is used to calculate the area of a parallelogram formed by two vectors, find the torque exerted by force at a distance from a point, and determine the direction of a magnetic field produced by a current-carrying wire—computer graphics it is used to generate 3D graphics and animations by transforming objects in space.
Cross-Products Matrix
The cross-product between two vectors in 3D space can also be represented as the cross-product matrix or the skew-symmetric matrix. This matrix is defined as follows:
Given two vectors A = [a1, a2, a3] and B = [b1, b2, b3], the cross product matrix of A is:
[ 0 -a3 a2]
[ a3 0 -a1]
[-a2 a1 0]
And the cross-product matrix of B is:
[ 0 -b3 b2]
[ b3 0 -b1]
[-b2 b1 0]
The crosswise elements of the matrix are continually zero, and the off-diagonal parts are just the negation of each other. Also, the cross product of A and B can be computed by multiplying the cross product matrix of A with B (or vice versa) and then taking the resulting vector as the cross product:
A x B = [ 0 -a3 a2] [ b]
[ a3 0 -a1] [ b2]
[-a2 a1 0] [ b3]
= [ a2*b3 – a3*b2]
[ a3*b1 – a1*b3]
[ a1*b2 – a2*b1]
It corresponds to the earlier formula for the cross-product of two vectors. The advantage of using the cross-product matrix is that it allows us to perform the cross-product operation using matrix multiplication, which can be useful in certain applications, such as computer graphics and robotics.
Difference Between a Dot and a Cross-Product of a Vector
Dot product and cross product are mathematical operations often used in vector calculus. While they may seem similar initially, they have different applications and results.
| Dot product | Cross-product |
| If we take two vectors, A and B, the dot product (denoted as A · B) is: A · B = A1B1 + A2B2 + A3B3 + … + AnBn Where A1, A2, A3, and an are the components of vector A, and B1, B2, B3, and Bn are the components of vector B. | The cross product, or the vector product, is a mathematical operation that takes two vectors and produces a third vector perpendicular to both input vectors. |
| It Is calculated by multiplying the corresponding components of the two vectors and then summing up the products. | If we take two vectors, A and B, the dot product (denoted as A · B) is: A · B = A1B1 + A2B2 + A3B3 + … + AnBn Where A1, A2, A3, and an are the components of vector A, and B1, B2, B3, and Bn are the components of vector B. |
| If we take two vectors,A and B, the dot product (denoted as A · B) is: A · B = A1B1 + A2B2 + A3B3 + … + AnBn Where A1, A2, A3, and an are the components of vector A, and B1, B2, B3, and Bn are the components of vector B. | If we have two vectors, C and D, the cross product (denoted as C x D) is: C x D = (C2D3 – C3D2) I + (C3D1 – C1D3) j + (C1D2 – C2D1) k i, j, and k are the unit vectors along the x, y, and z axes. |
| The dot product helps find the angle between two vectors and determine whether two vectors are orthogonal (perpendicular) to each other. It is also used in physics to calculate work, power, and energy. | The cross-products help determine the direction of a force or torque resulting from the interaction of two vectors. It is also used in geometry to find a triangle’s area or a parallel piped’s volume. |
Does Dot Product Come Before Cross Product?
The cross product occurs first.
Can Cross Product be Zero?
The cross product of two vectors can be zero if the vectors are parallel. In other words, if the vectors point in the same direction or precisely opposite directions, their cross-product will be zero.
Conclusion
- The dot product and cross product involve vector operation. The dot product produces a scalar quantity, while the cross-product produces a vector quantity perpendicular to both input vectors.
- The dot merchandise of two vectors, A and B, is a scalar quantity calculated by multiplying the magnitudes of the two vectors and then taking the cosine of the angle between them.
- The dot product measures the extent to which the two vectors aspect in the equal direction. The cross-product is helpful in calculating moments, determining the direction of forces in a physical system, and finding the normal vectors to surfaces in 3D space.
- Both dot and cross-products have significant applications in various fields, such as physics, engineering, computer graphics, and machine learning.
- The dot product is used to compute angles, projections, work, and power and to define orthonormal bases. The cross-product calculates areas, volumes, moments, and torques and defines perpendicular directions or frames.
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