Cant quite see this grad relation

In summary, the conversation discusses the concept of parallel vectors in relation to the gradient of a function. The book states that if the gradient is equal to zero, then the partial derivatives of the function are parallel. However, one person questions how this can be true and provides an example to illustrate their confusion. The conversation also includes a discussion about the placement of the conversation on a forum, with the responder moving it to the appropriate section in Calculus.
  • #1
ognik
643
2
Book states: $\nabla f\left(u, v\right) =0 = \frac{\partial f}{\partial u}\nabla u + \frac{\partial f}{\partial v} \nabla v, \therefore \nabla u$ and $ \nabla v $ are parallel

1. I know $d f\left(u, v\right) = \frac{\partial f}{\partial u}du + \frac{\partial f}{\partial v} dv$, but how can we just replace the d<...> by $\nabla <... >$ like that? seems a little circular?

2. Can't anyway see how that makes them parallel?
I get $ =\frac{\partial f}{\partial u}\left( \pd{u}{x}, \pd{u}{y},\d{u}{z}\right) + \frac{\partial f}{\partial v}\left( \pd{v}{x}, \pd{v}{y},\d{v}{z}\right)
= \left( \pd{f}{x}, \pd{f}{y},\d{f}{z}\right) + \left( \pd{f}{x}, \pd{f}{y},\d{f}{z}\right)$ so both tterms are equal and parallel, but why does that make the $\nabla$ parts parallel?
 
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  • #2
ognik said:
Book states: $\nabla f\left(u, v\right) =0 = \frac{\partial f}{\partial u}\nabla u + \frac{\partial f}{\partial v} \nabla v, \therefore \nabla u$ and $ \nabla v $ are parallel

1. I know $d f\left(u, v\right) = \frac{\partial f}{\partial u}du + \frac{\partial f}{\partial v} dv$, but how can we just replace the d<...> by $\nabla <... >$ like that? seems a little circular?

It's a generalization for multiple dimensions.
The chain rule for multiple dimensions says:
$$\d f x = \pd f u \pd u x + \pd f v \pd v x$$

2. Can't anyway see how that makes them parallel?
I get $ =\frac{\partial f}{\partial u}\left( \pd{u}{x}, \pd{u}{y},\d{u}{z}\right) + \frac{\partial f}{\partial v}\left( \pd{v}{x}, \pd{v}{y},\d{v}{z}\right)
= \left( \pd{f}{x}, \pd{f}{y},\d{f}{z}\right) + \left( \pd{f}{x}, \pd{f}{y},\d{f}{z}\right)$ so both tterms are equal and parallel, but why does that make the $\nabla$ parts parallel?

Are they really parallel?
And does $\pd f u \pd u x = \pd f x$ hold?

Let's pick an example.
Suppose we pick $f(u,v)=u^2+v^2-1, \quad u(x,y)=x+y, \quad v(x,y)=x-y$
How would that work out?Oh, and I've moved your thread to Calculus, which is where Partial Derivatives and Multi-variable Calculus belongs.
Please check the descriptions of the forums on the main page.
 
  • #3
I like Serena said:
It's a generalization for multiple dimensions.
The chain rule for multiple dimensions says:
$$\d f x = \pd f u \pd u x + \pd f v \pd v x$$.
So $ \pd{f}{x}, \pd{f}{y} = \nabla f = \left( \pd{f}{u}\pd{u}{x}+\pd{f}{v}\pd{v}{x}, \pd{f}{u}\pd{u}{y}+\pd{f}{v}\pd{v}{y} \right) = \pd{f}{u} \left( \pd{u}{x},\pd{u}{y} \right) + \pd{f}{v}\left( \pd{v}{x},\pd{v}{y} \right) ...$?

I like Serena said:
Are they really parallel?.
I couldn't see why they should be, but the book says if $\nabla f = 0$, then they are, I can't see this is a general case?

I like Serena said:
And does $\pd f u \pd u x = \pd f x$ hold?.
didn't understand why you asked, its missing the $\pd{f}{v}...$ part?

I like Serena said:
Oh, and I've moved your thread to Calculus, which is where Partial Derivatives and Multi-variable Calculus belongs.
Please check the descriptions of the forums on the main page.
Thanks, I was honestly undecided 'cos in my book this is a section on vectors, just looking at grad, curl etc...
 
  • #4
ognik said:
So $ \pd{f}{x}, \pd{f}{y} = \nabla f = \left( \pd{f}{u}\pd{u}{x}+\pd{f}{v}\pd{v}{x}, \pd{f}{u}\pd{u}{y}+\pd{f}{v}\pd{v}{y} \right) = \pd{f}{u} \left( \pd{u}{x},\pd{u}{y} \right) + \pd{f}{v}\left( \pd{v}{x},\pd{v}{y} \right) ...$?
Correct.

I couldn't see why they should be, but the book says if $\nabla f = 0$, then they are, I can't see this is a general case?
I actually overlooked that it was given that $\nabla f = 0$.
In that case they have to be parallel, since the only way 2 vectors can sum up to zero is if they are equal and opposite.
Since the partial derivatives are only scalars, that implies that one vector must be a multiple of the other. That is, parallel.

didn't understand why you asked, its missing the $\pd{f}{v}...$ part?
It's not true, which should become clear if we work out the example I posted.

Thanks, I was honestly undecided 'cos in my book this is a section on vectors, just looking at grad, curl etc...
If you look at the descriptions of the forums, it should be clear where it should go, regardless of the section in your book.
 

FAQ: Cant quite see this grad relation

What is a "grad relation" in science?

A "grad relation" refers to a relationship or connection between two or more variables that have a continuous or gradual change. It is often used in fields such as physics, mathematics, and engineering to describe the relationship between quantities like time, distance, and temperature.

How is a "grad relation" different from a "linear relation"?

A "grad relation" is different from a "linear relation" in that a linear relation has a constant rate of change, whereas a grad relation has a variable or changing rate of change. In other words, in a linear relation, the dependent variable changes by a fixed amount for each unit change in the independent variable, while in a grad relation, the dependent variable changes by a varying amount for each unit change in the independent variable.

Can you give an example of a "grad relation" in real life?

One example of a "grad relation" in real life is the relationship between distance and time when driving a car at a constant speed. As the time increases, the distance traveled also increases, but the rate of change of distance (speed) stays the same. However, when driving in city traffic, the rate of change of distance may vary due to traffic lights and congestion, making it a grad relation.

How do scientists study and analyze "grad relations"?

Scientists study and analyze "grad relations" by using mathematical tools and techniques such as calculus and graphs. They plot the data points on a graph and use mathematical models to describe and analyze the relationship between the variables. They also use differential equations to understand how the variables change over time.

Are there any practical applications of understanding "grad relations"?

Yes, there are many practical applications of understanding "grad relations." For example, in engineering, understanding the relationship between force and displacement can help in designing structures and machines. In physics, understanding the relationship between velocity and acceleration can help in predicting the motion of objects. In economics, understanding the relationship between supply and demand can help in making business decisions. Overall, understanding "grad relations" helps us better understand and predict the behavior of various phenomena in the natural world.

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