Quick Differential Form Question

In summary, the conversation discusses the concept of differential forms and the question of whether ##ydx=0## when working with multiple variables. It is mentioned that while ##ydx## is not automatically zero, the system (##x\equiv 0 \wedge ydx=0##) has a solution that can get lost if divided by ##x^{2}##. The idea of considering this system first and then the case where ##x \not\equiv 0## is also mentioned. It is noted that not all operations on an equation or system will preserve the solution set.
  • #1
Drakkith
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I've been going through my book learning about differential equations of multiple variables and I have a quick question about differential forms.

If you are working a problem and get to the point where you're left with a differential form like ##(y)dx##, does that mean that the change in the function as ##x## changes is zero, such that ##(y)dx=0##?

For example, one of the example problems in my book is:$$(2x^2+y)dx+(x^2y-x)dy=0$$
It says that if you multiply the function by the integrating factor ##u(x)=x^{-2}## you get $$(2+yx^{-2})dx+(y-x^{-1})dy=0$$ and you end up losing the solution ##x≡0##.

I understand that plugging 0 into the original equation yields ##(y)dx+(0)dy=0##, but I'm not sure why 0 is a solution.
 
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  • #2
##ydx## isn't automatically zero, but the system ( ##x\equiv 0 \wedge ydx=0## ) has a solution which will get lost if we divide by ##x^{2}##. So as always in these cases, consider this system first and in the next case ##x \not\equiv 0\,##.
 
  • #3
fresh_42 said:
##ydx## isn't automatically zero, but the system ( ##x\equiv 0 \wedge ydx=0## ) has a solution which will get lost if we divide by ##x^{2}##.

I'm sorry but I don't know what that bit in the parentheses means.

fresh_42 said:
So as always in these cases, consider this system first and in the next case ##x \not\equiv 0\,##.

What do you mean by "consider this system first"?
 
  • #4
I meant ##x \equiv 0## is a possibility at first. In this case we conclude ##ydx=0## which can be integrated and leads to a solution with ##x \equiv 0 ## and ##y = \text{ anything }##. From this point on we can assume ##x \not\equiv 0## and consider this remaining case.
 
  • #5
Ah okay. Thanks fresh.
 
  • #6
As a general comment not every operation on your equation/system will preserve the solution set. Remember, e.g., when you have a system of linear equations that anything other than switching rows, non-zero scaling and adding a multiple of one row to another, will change the solution .
 
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1. What is a quick differential form?

A quick differential form is a mathematical concept used in calculus and differential geometry to describe the change in a quantity over a small region. It is represented using symbols and equations, and is often used in physics and engineering to model real-world phenomena.

2. How is a quick differential form different from a regular differential form?

A quick differential form is a simplified version of a regular differential form, which is a more general concept used in advanced mathematics. Quick differential forms are typically used for quick calculations and approximations, while regular differential forms are used for more precise and rigorous calculations.

3. What is the purpose of using quick differential forms?

The purpose of using quick differential forms is to make calculations easier and more efficient. They allow for quick approximations and simplifications, which can be useful in situations where precise calculations are not necessary or feasible.

4. Can quick differential forms be used in multiple dimensions?

Yes, quick differential forms can be used in multiple dimensions. They can be applied to any system or phenomenon that involves changes in quantities over a small region, regardless of the number of dimensions involved.

5. Are there any limitations to using quick differential forms?

One limitation of quick differential forms is that they are not as precise as regular differential forms. They may also not be suitable for complex or nonlinear systems, as they rely on linear approximations. Additionally, they may not be applicable in certain areas of mathematics, such as topology.

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