Derivatives of 3D Scalar/Vector Functions
📂Mathematical PhysicsDerivatives of 3D Scalar/Vector Functions
Theorem
When the 3D scalar function f:R3→R1 is f(x(t),y(t),z(t))=f, dtdf is as follows.
dtdf=∂x∂fdtdx+∂y∂fdtdy+∂z∂fdtdz
When the 3D vector function f:R3→R3 is f(x(t),y(t),z(t))=(f1,f2,f3), dtdf is as follows.
dtdf== (dtdf1,dtdf2,dtdf3)=dtdf1x^+dtdf2y^+dtdf3z^ (∂x∂f1dtdx+∂y∂f1dtdy+∂z∂f1dtdz)x^+(∂x∂f2dtdx+∂y∂f2dtdy+∂z∂f2dtdz)y^+(∂x∂f3dtdx+∂y∂f3dtdy+∂z∂f3dtdz)z^
Explanation
When the multivariable vector function f:Rn→Rm is f=(f1,f2,…,fm), the total derivative is as follows.
f′=D1f1D1f2⋮D1fmD2f1D2f2⋮D2fm⋯⋯⋱⋯Dnf1Dnf2⋮Dnfm
Therefore, when n=3 and m=1,3, it is as follows.
f′=[D1fD2fD3f]=[∂x∂f∂y∂f∂z∂f]
f′=D1f1D1f2D1f3D2f1D2f2D2f3D3f1D3f2D3f3=∂x∂f1∂x∂f2∂x∂f3∂y∂f1∂y∂f2∂y∂f3∂z∂f1∂z∂f2∂z∂f3
Now, let’s say g(t)=(x(t),y(t),z(t)). Then
f(x(t),y(t),z(t))=f(g(t))=f∘g(t)
f(x(t),y(t),z(t))=f(g(t))=f∘g(t)
Then, by the chain rule of the total derivative,
dtdf=f(g(t))=f′(g(t))g′(t)=[∂x∂f∂y∂f∂z∂f]dtdxdtdydtdz=∂x∂fdtdx+∂y∂fdtdy+∂z∂fdtdz
dtdf=f′(g(t))g′(t)=∂x∂f1∂x∂f2∂x∂f3∂y∂f1∂y∂f2∂y∂f3∂z∂f1∂z∂f2∂z∂f3dtdxdtdydtdz=∂x∂f1dtdx+∂y∂f1dtdy+∂z∂f1dtdz∂x∂f2dtdx+∂y∂f2dtdy+∂z∂f2dtdz∂x∂f3dtdx+∂y∂f3dtdy+∂z∂f3dtdz=dtdf1dtdf2dtdf3