What is the matrix representation of a 90-degree rotation around the y-axis in 3D?
Conditions
- Rotation is 90 degrees around the y-axis.
- Working in a right-handed 3D coordinate system.
Reasoning, step by step
- Determine the new position of after a 90-degree rotation around the y-axis, which is .
- Determine the new position of , which remains on the axis of rotation at .
- Determine the new position of , which moves to the positive x-axis at .
- Place these three coordinate vectors as the columns of the 3x3 matrix.
Example
The script notes: 'Under this transformation, the vector moves down to the negative z-axis at coordinates . The vector remains stationary on the y-axis at ... Meanwhile, the vector swings over to the positive x-axis at . These resulting coordinate triplets become the respective columns of the rotation matrix.'
Common misconceptions
- Assuming rotates to the positive z-axis instead of the negative z-axis.
- Placing the coordinates of the rotated vectors as rows instead of columns.
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In this context, denotes the transformation obtained by applying B first and then applying A to the result. The notation follows the convention where the rightmost transformation acts first on the input vector.
Conditions: A and B are treated as transformations on the same space, here three-dimensional space.; The output of B must be an input acceptable to A.
The missing middle column is . This is obtained by applying the transformation A to the middle column of B, which is .
Conditions: A and B are the specific 3x3 matrices shown in the video.; The method of column-wise composition is used.
During a 90-degree rotation around the y-axis, moves to the negative z-axis at , remains stationary on the y-axis at , and swings to the positive x-axis at .
Conditions: Rotation angle is exactly 90 degrees; Axis of rotation is the y-axis; Right-handed coordinate system convention assumed for sign determination
transformation matrix maps the standard basis vectors to its own columns. Specifically, the first column of the matrix is the image of the vector , and the second column is the image of the vector .
Conditions: The matrix is .; Working in standard Cartesian coordinates.
The determinant scales the area of any measurable planar figure, not just squares. The absolute value of the determinant acts as a uniform area scaling factor for all regions under the linear transformation.
Conditions: The transformation is linear.; The figure is measurable and has finite area.; Use ordinary Euclidean area in standard orthonormal coordinates.
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