Jacobian matrix determinant vanishes

AI Thread Summary
The discussion centers on the implications of a vanishing determinant in a Jacobian matrix during coordinate transformations. A zero determinant indicates that the transformation is not invertible, suggesting it may not be a good transformation. The transformation in question involves Euler angles applied to a solid cube's initial position. It is noted that the determinants of standard rotation matrices are always 1, implying a potential calculation error in the Jacobian. The conclusion emphasizes the importance of verifying calculations to ensure the validity of the transformation.
Demon117
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What exactly does it mean when the determinant of a Jacobian matrix vanishes? Does that imply that the coordinate transformation is not a good one?

How do you know if you coordinate transformation is a good one or a bad one?
 
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Let me explain further. This is the particular transformation I am looking at:

\left(<br /> \begin{array}{c}<br /> x(t) \\<br /> y(t) \\<br /> z(t)<br /> \end{array}<br /> \right)= R_{z}(\gamma) R_{x}(\beta) R_{z}(\alpha)\left(<br /> \begin{array}{c}<br /> x_o \\<br /> y_o \\<br /> z_o<br /> \end{array}<br /> \right),

here, the vector (x_{o},y_{o},z_{o}) is just the initial positions of small pieces of a solid cube, and the angles \alpha(t),\beta(t),\gamma(t) are the Euler angles (all functions of time).

When I expand this out, and form the Jacobian matrix, it's determinant vanishes.
 
Probably there is a mistake in your calculation. In the standard forms, the determinant of Rx , Ry and Rz all are 1.0 , for any angles. So is the determinant of their product.
 
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