Just to be sure about the Jacobian matrix and determinant....

In summary, the conversation discusses the equations of a sphere in a spherical coordinate system and the process of changing basis from the local (o,a,r)-space to the global (x,y,z)-space using the Jacobian matrix. The determinant of the Jacobian matrix, which represents the volume spanned by the parallelpiped of column vectors in (x,y,z)-space, is often used in integration. The conversation also mentions the possibility of using the determinant of the un-transposed Jacobian matrix and discusses the interpretation of the row vectors of the Jacobian matrix as gradients in the "gradient space" of (x,y,z)-space.
  • #1
rabbed
243
3
Ok, I've got these functions to get the x (right), y (up) and z (forward) coordinates to plot with my computer program:

x = r*Math.cos(a)*Math.sin(o)
y = r*Math.sin(a)
z = -r*Math.cos(a)*Math.cos(o)

It's the equations of a sphere where I've placed the origin (o,a,r) = (0,0,0) of the source (spherical) coordinate system at (x,y,z) = (0,0,-r) in the destination space. From the origin in (a,o,r)-space, Longitude (o) increases in the positive x-direction before heading off into positive z-direction, latitude (a) increases in the positive y-direction and the radius (r) stays fixed.

To learn about the Jacobian matrix, I first write down the definition:

[ dx/do dx/da dx/dr ]
[ dy/do dy/da dy/dr ] =
[ dz/do dz/da dz/dr ]

[ r*cos(a)*cos(o) -r*sin(a)*sin(o) cos(a)*sin(o) ]
[ 0 r*cos(a) sin(a) ]
[ r*cos(a)*sin(o) r*sin(a)*cos(o) -cos(a)*cos(o) ]

Now, for a point of derivation on the sphere, drawing the column vectors from that point gives me three basis vectors (not neccessarily orthogonal or with unit length) to the local (o,a,r)-space. Multiplying these vectors respectively with do, da, dr and summing these up gives me a vector in (x,y,z)-space which I draw from the point.

This process is the equivalent of a change of basis for a vector (do,da,dr) in the local (o,a,r)-space to the global (x,y,z)-space, right?

It would then make sense if the Jacobian (as in the determinant), used in integration etc. is the absolute value of the _transpose_ Jacobian matrix determinant. It would give me the volume spanned by the parallelpiped of column vectors in the Jacobian matrix (or rows in the transposed matrix) in (x,y,z)-space, corresponding to a 1-sided cube in the (o,a,r)-space.

Is this correct (many seems to take the determinant of the non-transposed matrix, even with the same definition I've used above)?

Does it make any sense to draw the row vectors of the Jacobian matrix?

Interpreting the multiplication of the matrix and a unit vector as a change of basis for a unit vector in local (o,a,r)-space to a "gradient space" in global (x,y,z)-space by projecting the unit vector onto the row vectors (gradients) of the matrix. Since the "gradient space" represents change in (x,y,z)-space divided by change in (a,o,r)-space, the multiplication results in a (x,y,z)-space vector.

Is there any other intuitive explanation that can be used for the row vectors?
Is there any use for a determinant of an un-transposed Jacobian matrix?

Rgds
Rabbed
 
Last edited:
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  • #2
Sorry, I can't seem to edit my post..
At all places where it says (a,o,r)-space, I mean (o,a,r)-space since the Jacobian matrix columns were created by derivating with respect to o, a and r in that order..
 

1. What is the Jacobian matrix and determinant?

The Jacobian matrix and determinant are mathematical concepts used in multivariate calculus to represent the rate of change of a system of variables with respect to each other. It is often used in vector calculus, differential equations, and physics.

2. How is the Jacobian matrix and determinant calculated?

The Jacobian matrix is calculated by taking the partial derivatives of each variable in the system and arranging them in a matrix. The determinant of the Jacobian matrix is then found by taking the determinant of this matrix.

3. What is the significance of the Jacobian matrix and determinant?

The Jacobian matrix and determinant are important because they provide information on the behavior of a system of variables. They can help determine whether the system is stable, whether it has critical points, and how it will evolve over time.

4. How is the Jacobian matrix and determinant used in real-world applications?

The Jacobian matrix and determinant have numerous applications in fields such as physics, economics, and engineering. They are used to solve problems involving optimization, stability analysis, and modeling of complex systems.

5. What are some common errors when working with the Jacobian matrix and determinant?

Some common errors when working with the Jacobian matrix and determinant include miscalculations, incorrect variable order, and forgetting to account for all variables in the system. It is important to double check all calculations and to carefully consider all variables in the system to avoid these errors.

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