Implicit differentiation in multiple variables

In summary, the conversation discusses using implicit differentiation in the context of multiple variables to find the partial derivatives of θ with respect to a, b, and c. The suggestion is to solve for cosθ and then use the chain rule to express the partial derivatives in terms of the partial derivatives of cosθ. A trig identity can also be used to rewrite the sin function in terms of cosθ.
  • #1
groovy958
1
0
So, as the title may have given away, I'm trying to figure out implicit differentiation in the multiple variable context. I thought a good practice would be the law of cosines, aka
c^2 = a^2 + b^2 - 2abcosθ.
So I'm trying to find ∂θ/∂a, ∂θ/db, ∂θ/dc.
I tried solving for θ and then taking partials, but that seems like the wrong way to do it. Any suggestions?
 
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  • #2
Solve for ##\cos\theta## and use the chain rule to express, say, ##\partial \theta/\partial a## in terms of ##\partial (\cos \theta)/\partial a##. You can use a trig identity to rewrite the sin function in terms of the original cos.
 

Related to Implicit differentiation in multiple variables

1. What is implicit differentiation in multiple variables?

Implicit differentiation in multiple variables is a mathematical technique used to find the derivative of a function with more than one independent variable. It is a generalization of the standard implicit differentiation method, which is used for functions with only one independent variable.

2. How is implicit differentiation in multiple variables different from single variable implicit differentiation?

The basic principles of implicit differentiation are the same in both cases. However, in multiple variables, the chain rule and partial derivatives are used to find the derivative with respect to each independent variable. This results in a system of equations that can be solved simultaneously to find the final derivative.

3. What are the applications of implicit differentiation in multiple variables?

Implicit differentiation in multiple variables is commonly used in physics, engineering, and economics to model complex systems with multiple variables. It is also used in optimization problems where the goal is to find the maximum or minimum value of a function with multiple variables.

4. Can implicit differentiation be used for any function with multiple variables?

Yes, implicit differentiation can be applied to any function with multiple variables, as long as the function is differentiable. However, some functions may require more advanced techniques, such as the implicit function theorem, to find the derivative.

5. How can implicit differentiation in multiple variables be visualized?

One way to visualize implicit differentiation in multiple variables is to graph the function in three-dimensional space. The derivative at a specific point can then be represented by the slope of the tangent plane to the graph at that point. This can help in understanding the behavior of the function and its derivatives in multiple dimensions.

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