Gradients vs. Partial Derivatives

In summary, partial derivatives are limits and the gradient is an operator used to calculate the matrix of partial derivatives for a function of multiple variables.
  • #1
shanepitts
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What is the difference between partial derivatives and gradients, if there is any?

I'm asking because I need to derive a function " f (T,P) " for air convection; where T is temperature and P is pressure and both are variables in this case.

Thanks
 
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  • #2
A gradient is the matrix containing all the partial derivatives.
 
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  • #3
For a function of three variables, grad [itex]F(x,y,z)= \nabla F(x, y, z)= \frac{\partial F}{\partial x}\vec{i}+ \frac{\partial F}{\partial y}dy\vec{j}+ \frac{\partial F}{\partial z}\vec{j}[/itex]. In particular, the differential, [itex]dF= \frac{\partial F}{\partial x}dx+ \frac{\partial F}{\partial y}dy+ \frac{\partial F}{\partial z}dz[/itex], can be thought of as the dot product of [itex]\nabla F[/itex] and [itex]dx\vec{i}+ dy\vec{j}+ dz\vec{k}[/itex].
 
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shanepitts said:
What is the difference between partial derivatives and gradients, if there is any?

I'm asking because I need to derive a function " f (T,P) " for air convection; where T is temperature and P is pressure and both are variables in this case.

Thanks
partial derivatives are "limits" meanwhile the gradient is an operator.
 

Related to Gradients vs. Partial Derivatives

1. What is the difference between a gradient and a partial derivative?

A gradient is a vector that points in the direction of the steepest increase of a function at a specific point. It is the combination of all the partial derivatives of the function with respect to each variable. A partial derivative, on the other hand, measures the rate of change of a function with respect to only one variable, holding all other variables constant.

2. When would you use a gradient vs. a partial derivative?

A gradient is used to find the direction of steepest ascent or descent of a function at a specific point, which is useful in optimization problems. Partial derivatives are used to calculate the sensitivity of a function to changes in a specific variable, which is useful in analyzing the behavior of a function.

3. How are gradients and partial derivatives related?

The gradient is a generalization of the concept of a partial derivative. A gradient includes all the partial derivatives of a function with respect to each variable, while a partial derivative only considers the change in the function with respect to one variable.

4. Can you give an example of when gradients and partial derivatives are used in real-world applications?

Gradients and partial derivatives are used in many fields, such as physics, economics, and engineering. In physics, gradients are used to calculate the direction of the force acting on an object, while partial derivatives are used to analyze the behavior of a dynamic system. In economics, gradients are used to find the optimal solution in production and consumption problems, while partial derivatives are used to measure the elasticity of demand. In engineering, gradients and partial derivatives are used in optimization problems and to analyze the behavior of systems.

5. Is the gradient always perpendicular to the level curves of a function?

Yes, the gradient is always perpendicular to the level curves (contour lines) of a function. This is because the gradient represents the direction of the steepest increase, and the level curves represent points where the function has the same value. The perpendicularity of the gradient and level curves can be seen in the fact that the dot product of the gradient and the tangent vector of the level curve at a specific point is equal to zero.

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