Vector Perspectives
Vectors can be understood physically as free-floating arrows defined by magnitude and direction, or computationally as fixed lists of numerical data. Linear algebra bridges these by treating numerical lists as geometric objects.
3Blue1Brown · YouTube · 9:51
This segment introduces the concept of a vector in linear algebra by contrasting three perspectives: the physics student's view (arrows in space), the computer science student's view (ordered lists of numbers), and the mathematician's abstract view. It establishes the standard geometric representation of vectors anchored at the origin of a coordinate system. The video then defines the two fundamental operations on vectors: addition, demonstrated via the tip-to-tail method and component-wise arithmetic, and scalar multiplication, explained as scaling (stretching, shrinking, or reversing) a vector.
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Linear algebra is built upon the foundation of vectors. To understand them fully, we must look through three distinct lenses. First, the physicist sees a vector as an arrow in space defined solely by its length and direction; it can be moved anywhere without changing its identity. Second, the computer scientist views a vector simply as an ordered list of numbers, like coordinates for a house's size and price. Third, the mathematician generalizes this to any object that supports sensible addition and scalar multiplication. For our purposes, we will primarily use the geometric view: arrows rooted at the origin of a coordinate system.
In a 2D plane with x and y axes intersecting at the origin, a vector's coordinates tell us how to travel from the origin to the vector's tip. The first number dictates horizontal movement (right is positive, left is negative), and the second dictates vertical movement (up is positive, down is negative). We write these pairs vertically in brackets to distinguish them from points. This logic extends to 3D space by adding a z-axis, where a vector is represented by a triplet of numbers corresponding to movements along the x, y, and z axes respectively.
The two most critical operations are vector addition and scalar multiplication. Adding two vectors geometrically involves placing the tail of the second vector at the head of the first; the sum is the vector drawn from the start to the finish. Numerically, this corresponds to adding their respective components ( and ). Scalar multiplication acts as 'scaling.' Multiplying by a number greater than 1 stretches the vector, a fraction shrinks it, and a negative number flips its direction while adjusting its length. Component-wise, you simply multiply each entry by the scalar. More precisely, length is multiplied by |c|: only 0<|c|<1 shortens it, negative c reverses it, and yields the zero vector. Column notation is a convention; bracket orientation alone is not a mathematical distinction between a point and a vector.
Vectors can be understood physically as free-floating arrows defined by magnitude and direction, or computationally as fixed lists of numerical data. Linear algebra bridges these by treating numerical lists as geometric objects.
Rooting a free vector at the origin is a convenient representative. Its displacement remains unchanged by translation. Vector coordinates depend on the chosen basis; coordinates of points additionally depend on the origin.
Defined geometrically by the 'tip-to-tail' method. Algebraically, it is performed by summing corresponding components of the input vectors.
The scalar c multiplies length by |c|. Positive c preserves direction, negative c reverses it, and zero gives the zero vector, whose direction is undefined.
The reviewed perspectives card and summaries connect vectors as displacements with ordered components, then explain tip-to-tail addition and scalar multiplication. Translating a free vector preserves displacement, while coordinates depend on the chosen basis. Multiplication by scales length by ; gives the zero vector with no direction.
The mathematician generalizes the concept to any object that supports sensible addition and scalar multiplication operations.
Conditions: Abstract linear algebra context
Multiplying by a negative number flips the vector's direction while adjusting its length based on the absolute value of the scalar.
Conditions: Scalar ; Non-zero initial vector
The length is multiplied by the absolute value of the scalar . Specifically, shortens the vector, stretches it, and yields the zero vector.
Conditions: Scalar multiplication operation; Considering magnitude/length changes
Geometrically, adding two vectors involves placing the tail of the second vector at the head of the first; the sum is the vector drawn from the start of the first to the finish of the second.
Conditions: Two vectors available for addition; Euclidean geometric representation
In a 2D plane, the first component dictates horizontal movement (right positive, left negative) and the second dictates vertical movement (up positive, down negative) from the origin to the tip.
Conditions: Standard Cartesian coordinate system; Vector anchored at the origin
The computer scientist views a vector simply as an ordered list of numbers, such as coordinates for a house's size and price.
Conditions: Viewing vectors through the lens of computer science
The physicist sees a vector as an arrow in space defined solely by its length and direction; it can be moved anywhere without changing its identity.
Conditions: Viewing vectors through the lens of physics
Numerically, vector addition corresponds to adding their respective components independently ( for the x-coordinate and for the y-coordinate).
Conditions: Vectors represented as column arrays; Same dimensionality for both vectors