Why does the dx cancel out in partial derivatives for conservative fields?

In summary, the conversation discusses the application of the chain rule for multivariable functions and its implications for finding line integrals. The formula for the line integral is derived and it is shown how it can be used to determine if a vector field is conservative. The concept of sensitivity is also mentioned as a way to understand the formula.
  • #1
DunWorry
40
0
Hi, I was reading something on conservative fields, in this example [itex]\phi[/itex] is a scalar potential. (Please refer to the attatched thumbnail). It's partial derivatives, but I'm not sure why the d[itex]\phi[/itex]/dx * dx, the dx should cancel out? and that should leave d[itex]\phi[/itex]. So the integral should be -3∫d[itex]\phi[/itex]. I know this is wrong, but I'm not sure why, can someone explain?

Thanks
 

Attachments

  • Untitled.png
    Untitled.png
    3.7 KB · Views: 447
Physics news on Phys.org
  • #2
You are trying to apply the "one variable" chain rule to a multivariable function. The chain rule for multivariable functions is
[tex]\frac{d\phi}{dz}= \frac{\partial \phi}{\partial x}\frac{dx}{dt}+ \frac{\partial \phi}{\partial y}\frac{dy}{dt}[/tex]
or in "differential form"
[tex]d\phi= \frac{\partial \phi}{\partial x}dx+ \frac{\partial \phi}{\partial y}dy[/tex]
 
  • Like
Likes 1 person
  • #3
It does not say ##\frac{d\phi}{dx}dx## etc, it says ##\frac{\partial \phi}{\partial x}dx## etc. and that is not the same thing. A function of three variables ##\phi(x,y,z)## changes if any of three variables changes, not just ##x##, and if all the variables change, then these changes all contribute to the change in ##\phi##.
To derive the formula, choose a path from ##a## to ##b## and parametrize it, and then evaluate the line integral using this parametrization.
 
  • #4
To answer your question, it's better to go back to the definition of a line integral. To that end we give the curve in parameter representation
[tex]C: \quad \vec{x}=\vec{x}(t), \quad t \in [t_1,t_2].[/tex]
Let further be [itex]\vec{V}(\vec{x})[/itex] a vector field. Then by definition the line integral of this field along the curve is given by
[tex]\int_C \mathrm{d} \vec{x} \cdot \vec{V}(\vec{x})=\int_{t_1}^{t_2} \mathrm{dt} \frac{\mathrm{d} \vec{x}}{\mathrm{d} t} \cdot \vec{V}[\vec{x}(t)].[/tex]

Now suppose [itex]\vec{V}=-\vec{\nabla} \phi[/itex]. Now according to the chain rule for multi-variable functions we have
[tex]\frac{\mathrm{d}}{\mathrm{d} t} \phi[\vec{x}(t)]=\frac{\mathrm{d} x}{\mathrm{d}t} \frac{\partial \phi}{\partial x}+\frac{\mathrm{d} y}{\mathrm{d}t} \frac{\partial \phi}{\partial y}+\frac{\mathrm{d} z}{\mathrm{d}t} \frac{\partial \phi}{\partial z}=\frac{\mathrm{d} \vec{x}}{\mathrm{d} t} \cdot \vec{\nabla} \phi[\vec{x}(t)]=-\frac{\mathrm{d} \vec{x}}{\mathrm{d} t} \cdot \vec{V}[\vec{x}(t).[/tex]
Plugging this into the above integral gives
[tex]\int_{C} \mathrm{d} \vec{x} \cdot \vec{V}(x)=-\int_{t_1}^{t_2} \mathrm{d} t \frac{\mathrm{d}}{\mathrm{d} t} V[\vec{x}(t)]=-[V(\vec{x}_2)-V(\vec{x}_1)],[/tex]
where [itex]\vec{x}_1=\vec{x}(t_1)[/itex] and [itex]\vec{x}_2=\vec{x}(t_2)[/itex] are the boundary points of the curve.

Note that this result implies that if the vector field is conservative, i.e., if it is the gradient of a scalar field, the line integral connecting two points is independent of the shape of the curve.
 
  • Like
Likes 1 person
  • #5
For me, the most intuitive way to think about this is to pretend that ##dx## is a rate, so that makes ##\phi_x dx = {\partial\phi \over \partial x} dx## the related rate and ##\phi_x## the x-sensitivity of ##\phi##. ##\phi##'s rate of change is the dot product of ##\phi##'s sensitivity vector (the gradient) and the variable rates of change.
 
  • Like
Likes 1 person

1. What is a partial derivative?

A partial derivative is a mathematical concept used to describe the rate of change of a multivariable function with respect to one of its variables, while holding all other variables constant. It is denoted by ∂ (pronounced "del") and is similar to a regular derivative, but with multiple variables involved.

2. How is a partial derivative calculated?

To calculate a partial derivative, we treat all other variables as constants and differentiate the function with respect to the variable in question. This is done using the standard rules of differentiation, such as the power rule and chain rule. The resulting expression is the partial derivative of the function.

3. What is a partial derivative used for?

Partial derivatives are commonly used in mathematical fields such as physics, engineering, and economics to describe rates of change in multivariable systems. They are also used in optimization problems to find the maximum or minimum values of a function.

4. Can a partial derivative be negative?

Yes, a partial derivative can be negative. This indicates that the function is decreasing in the direction of the variable in question. However, it is important to note that a partial derivative can be positive, negative, or zero depending on the specific values of the other variables involved.

5. Are there any applications of partial derivatives in real life?

Yes, there are many applications of partial derivatives in real life. For example, they are used in physics to describe the rate of change of a physical quantity with respect to time or other variables. In economics, partial derivatives are used to analyze the relationship between different variables in a market. They are also used in engineering to optimize designs and in machine learning to train models.

Similar threads

  • Calculus
Replies
2
Views
2K
Replies
14
Views
8K
Replies
4
Views
3K
  • Calculus
Replies
3
Views
2K
Replies
4
Views
1K
  • Advanced Physics Homework Help
Replies
10
Views
586
  • Calculus
Replies
5
Views
5K
Replies
8
Views
2K
Replies
14
Views
2K
Replies
1
Views
810
Back
Top