WordGarden.ioeigenvector
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Meanings
Noun
a nonzero vector that changes only by a scalar factor under a linear transformation
Beyond the definition
Imagine a sheet being pressed or pulled in some organized way. Most directions on the sheet will shift to point somewhere new, but a few special directions may stay on the same line. They do not turn into a different direction. They only get longer, shorter, or sometimes flip. Those special directions are called eigenvectors.
This idea matters far beyond geometry. In physics, engineering, and data science, eigenvectors help show the main patterns inside a system. Their matching eigenvalues tell you how strongly each direction is stretched, shrunk, or flipped. For example, when people study vibration, eigenvectors can describe the main ways a bridge, building, or string naturally moves.
An eigenvector is a non-zero vector that keeps the same line of direction when a linear transformation is applied to it. Instead of being turned into a completely new direction, it is only scaled: it may be stretched, compressed, or reversed. The number that tells how much this happens is called the eigenvalue.
One way to picture it is to imagine a sheet being stretched and skewed. Most arrows drawn on the sheet will end up pointing in new directions. But a few special arrows may still lie on the same line after the change. Those are eigenvectors. If the arrow becomes twice as long, the eigenvalue is 2. If it flips to the opposite direction, the eigenvalue is negative.
The word appears most often in linear algebra, but it is used in many practical areas. In physics and engineering, eigenvectors help describe natural vibration patterns and stable modes of motion. In data science and machine learning, they help reveal the main directions in data, such as in principal component analysis (PCA). In computer graphics and other matrix-based systems, they help explain how a transformation acts most simply.
The term "eigen" comes from German and means something like "own" or "characteristic." That fits the idea well: these are the characteristic directions of a transformation, the ones that respond in the simplest and most revealing way.
Examples
- 1
Matrix calculation
The program calculates an eigenvector for each eigenvalue of the matrix.
- 2
Dominant eigenvector
In practice, we often care most about the dominant eigenvector.
- 3
Class exercise
After finding the eigenvector, the students normalized it before comparing their results.
See also
Similar
- characteristic vector
- proper vector
Shades of meaning
- principal direction
- mode shape
Contrast
- eigenvalue
- basis vector
Used with (collocations)
- corresponding eigenvector
- normalized eigenvector
- eigenvector of a matrix
- left eigenvector
Word family
- eigen
Explore
- linear transformation
- diagonalization
Forms and spellings
1 form open this card.
Main spelling
- eigenvector