Geometrical interpretation of gradient

Click For Summary
SUMMARY

The discussion centers on the geometrical interpretation of the gradient operator as presented in 'Introduction to Electrodynamics' by Griffiths. The gradient, denoted as ∇T, represents the direction of the steepest ascent of a scalar field T, with its magnitude indicating the rate of increase in that direction. The conversation highlights the relationship between infinitesimal changes in coordinates (dx, dy, dz) and their impact on the direction of the vector dℓ, emphasizing that these infinitesimals can have different relative magnitudes despite being small. The participants clarify the physical significance of the gradient's magnitude and its implications in understanding directional derivatives.

PREREQUISITES
  • Understanding of vector calculus, specifically the gradient operator.
  • Familiarity with partial derivatives and their applications in physics.
  • Knowledge of scalar fields and their geometric interpretations.
  • Basic concepts of infinitesimals and their treatment in mathematical analysis.
NEXT STEPS
  • Study the properties of the gradient operator in vector calculus.
  • Explore the concept of directional derivatives and their applications in optimization.
  • Learn about the implications of infinitesimals in calculus and their rigorous definitions.
  • Investigate the relationship between gradients and contour lines in multivariable functions.
USEFUL FOR

Students and professionals in physics, mathematics, and engineering who seek to deepen their understanding of vector calculus and its applications in analyzing scalar fields and their gradients.

binei
Messages
3
Reaction score
0
In 'Introduction to Electrodynamics' by Griffiths, in the section of explaining the Gradient operator, it is stated a theorem of partial derivatives is:
$$ dT = (\delta T / \delta x) \delta x + (\delta T / \delta y) \delta y + (\delta T / \delta z) \delta z $$
Further he goes onto say:
$$ dT = (\dfrac{\delta T} {\delta x} {\bf x} + \dfrac{\delta T}{\delta y} {\bf y} +\dfrac{\delta T}{\delta z} {\bf z} ) . (dx {\bf x} + dy {\bf y} + dz{\bf z} )$$
$$ = \triangledown T . d{\bf l}$$

Further, in the geometrical interpretation of the gradient it is said that:
$$dT =\triangledown T . d{\bf l} = |\triangledown T||d {\bf l}|\cos \theta$$

My question is:
1. The magnitude dT is greatest when \theta = 0 , i.e. when \bf l is in same direction of \triangledown T . Since now d{\bf l} = (dx {\bf x} + dy {\bf y} + dz{\bf z} ) , to vary the direction of d{\bf l} , the relative magnitudes of dx, dy, dz need to be different. Am I correct?

2. Does the magnitude of the vector \triangledown T have any physical significance, given that it gives the length of the vector at some point (x,y,z)?
 
Physics news on Phys.org
1. Yes. The direction of ##\nabla T## is the direction in which ##T## grows the fastest for a fixed ##|d\vec \ell|##.

2. It is the rate at which the quantity increases when you go in the direction that it is pointing in.
 
Last edited:
  • Like
Likes   Reactions: binei
Thank you for the answer. I however found it strange that the magnitudes of these dx, dy, dz are relatively different, when they themselves are all infinitesimally small quantities...
 
binei said:
Thank you for the answer. I however found it strange that the magnitudes of these dx, dy, dz are relatively different, when they themselves are all infinitesimally small quantities...
What do you find strange about this?
 
Another physical interpretation is the derivative of T in the direction normal to the contours of constant T.
 
  • Like
Likes   Reactions: binei
Chestermiller said:
What do you find strange about this?
For example in a 2-dimensional case, we have the vector d{\bf l} = dx {\bf i} + dy {\bf j}. The angle or direction of this vector can be said to be tan\theta = dy/dx radians w.r.t x-axis. But both dx, dy are infinitesimally small quantities. Perhaps introducing limits, we can say \theta = 1, as both dy, dx \rightarrow 0. But how do we get other angles?
 
binei said:
For example in a 2-dimensional case, we have the vector d{\bf l} = dx {\bf i} + dy {\bf j}. The angle or direction of this vector can be said to be tan\theta = dy/dx radians w.r.t x-axis. But both dx, dy are infinitesimally small quantities. Perhaps introducing limits, we can say \theta = 1, as both dy, dx \rightarrow 0. But how do we get other angles?
$$dy=\sin{\theta} dl$$
$$dx=\cos{\theta} dl$$

In 3D,
$$dy=\sin{\theta} \sin{\phi}dl$$
$$dx=\cos{\theta}\sin{\phi} dl$$
$$dz=\cos{\phi}dl$$
 
  • Like
Likes   Reactions: binei
binei said:
Thank you for the answer. I however found it strange that the magnitudes of these dx, dy, dz are relatively different, when they themselves are all infinitesimally small quantities...

You can't reason with infinitesimal quantities in the same way that you reason with finite quantities. In fact, you can't reason with infinitesimal quantities in a logically consistent manner at all unless you use some very complicated definitions and axioms for them (e.g. https://en.wikipedia.org/wiki/Non-standard_analysis ), which are quite different than the approach taken in physics texts.

Infinitesimals in physics texts are treated in an intuitive manner. To help your intuition, consider that the infinitesimal formulation of the derivative of a real valued function of one real variable is "dy/dx". So there you have an example where a ratio between two infinitesimal quantities can be different than 1. Reasoning with infinitesimals is an attempt to deduce results that logically require reasoning about limits without actually doing the labor of thinking about limits.
 
  • Like
Likes   Reactions: binei

Similar threads

  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 14 ·
Replies
14
Views
2K
  • · Replies 18 ·
Replies
18
Views
3K
  • · Replies 2 ·
Replies
2
Views
3K
  • · Replies 13 ·
Replies
13
Views
2K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 22 ·
Replies
22
Views
3K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 12 ·
Replies
12
Views
3K
  • · Replies 4 ·
Replies
4
Views
4K