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kent davidge
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What is the usefulness of parallel transporting a vector? Of course, you can use it to determine whether a curve is a geodesic, but aside from that, what can it be used for?
kent davidge said:What is the usefulness of parallel transporting a vector?
kent davidge said:What is the usefulness of parallel transporting a vector? Of course, you can use it to determine whether a curve is a geodesic, but aside from that, what can it be used for?
Yes; a choice of vector space ( tangent space) isomorphism. Maybe Peter Donis can expand on this.kent davidge said:@WWGD , @PeterDonis can we say that a connection is also a rule for how to transport the vectors?
That's what it is meant for.kent davidge said:@WWGD , @PeterDonis can we say that a connection is also a rule for how to transport the vectors?
kent davidge said:can we say that a connection is also a rule for how to transport the vectors?
Good description, but it may be better to give an example for e.g., the sphere or circle, some manifold with non-zero curvature, where connection is not trivial.fresh_42 said:That's what it is meant for.
I think the misunderstandings already take place at school, and I don't mean specifically you. E.g. we say ##x \longmapsto 2x## is the derivative of ##f(x)=x^2## and continue to call it: derivative, sometimes differential, slope, tangent, later covariant derivative and whatever more. And all are wrong, i.e. not precise enough. In general we consider ##D_p f(x)## which equals ##2p## in our case, and not ##2x## as used at school. Now ##D_p f(x)## is an expression which has four input parameters: location ##p##, function ##f##, differentiation ##D## and manifold ##x##. So depending on which of these is variable and which are fixed, we get completely different objects out of ##D_pf(x)##.
In your question, it is ##p## which varies. The tangents at ##p## are different from the tangents at ##q##. They don't even share the same vector space, as one has ##p##, the other one has ##q## as its origin. But tangents are e.g. velocities and we want to compare velocities at different locations. Hence we have to connect the tangent space ##T_pM## at ##p## with the tangent space ##T_qM## at ##q##. A connection is a rule for this comparison. The only one which is to some extend natural, is to take a orthogonal basis of ##T_pM## and move it along a geodesic into ##T_qM##, so the velocities at ##q## can be expressed in the coordinates which formerly have been those of ##T_pM##.
https://en.wikipedia.org/wiki/Affine_connectionWWGD said:Good description, but it may be better to give an example for e.g., the sphere or circle, some manifold with non-zero curvature, where connection is not trivial.
I had written something on the Ehresmann connection too, but I am moving soon and everything I have is packed ( I had not written it down to my PC). EDIT: More examples from one of freshmeister/heimer paysans: https://people.mpim-bonn.mpg.de/hwbllmnn/archiv/dg1cag02.pdffresh_42 said:https://en.wikipedia.org/wiki/Affine_connectionView attachment 251086
https://en.wikipedia.org/wiki/Parallel_transportView attachment 251087I had planned to use my two chapter insight about ##SU(2)##
https://www.physicsforums.com/insights/journey-manifold-su2mathbbc-part/as example and write a third chapter with explicit calculations rather than just ##\nabla_Xf##.
I wanted to answer questions like:
Why is the Ehresmann connection a connection?
What makes it different from the Levi Civita connection?
What are orthogonal frames?
I even have already a couple of pages, but as this isn't my home ground, things became a bit complicated.
Your ##D_p f(x) \equiv 2p## can be called "derivative of ##f##" only when ##p = x## and ##f(x) = x^2##. If say, ##f(x) = x^3##, then ##D_x x^3 = 2x## would have another name?fresh_42 said:##D_p f(x)## is an expression which has four input parameters: location ##p##, function ##f##, differentiation ##D## and manifold ##x##. So depending on which of these is variable and which are fixed, we get completely different objects out of ##D_pf(x)##.
Remember to define which of the basic input parameters you are considering.kent davidge said:Let's see if I got this right.
Your ##D_p f(x) \equiv 2p## can be called "derivative of ##f##" only when ##p = x## and ##f(x) = x^2##. If say, ##f(x) = x^3##, then ##D_x x^3 = 2x## would have another name?
The full specification without any variables left is, i.e. all variables have a specific value, for ##f(x)=x^2##kent davidge said:Let's see if I got this right.
Your ##D_p f(x) \equiv 2p## can be called "derivative of ##f##" only when ##p = x## and ##f(x) = x^2##. If say, ##f(x) = x^3##, then ##D_x x^3 = 2x## would have another name?
Thanks. Now I know that there is such a thing called Wiedersehen manifold. Now I'm torn between curiosity, spirit and opportunity. On a first attempt I only found the classification (basically spheres) not the definition.WWGD said:More examples from one of freshmeister/heimer paysans: https://people.mpim-bonn.mpg.de/hwbllmnn/archiv/dg1cag02.pdf
The functional expression , here f'(x)=2x is the differential, i.e., the general linear map that describes/defines the local . Or is 2xdx the differential? I know if f is differentiable with differential f'(x) then f'(x)dx is a differential form.fresh_42 said:The full specification without any variables left is, i.e. all variables have a specific value, for ##f(x)=x^2##
$$
D_pf(x) =\lim_{h\to 0}\dfrac{f(p+h)-f(p)}{h}=\left. \dfrac{d}{dx}\right|_{x=p} f(x) = f\,'(p) = 2p
$$
is a real number.
Note the ambiguity of ##x##. It is the variable of the function ##f(x)## and at the same time often the location ##p## where we evaluate the derivative, because people write ##f\,'(x) ## when they should write ##f\,'(p)\,.##
Of course ##p \longmapsto f\,'(p) ## is again a function and the domain is the same as that of ##f(x)## so there is no difference in writing ##x \longmapsto f\,'(x) ## instead. But do they mean this function, the derivative, or do they mean the function value, the slope? This isn't the same thing. If we say ##f(x)## we are used to associate the function, not its value at ##x##. But if we say slope or tangent, then this makes only sense at a certain point, hence the function value ##f\,'(p)## and not the function ##x \longmapsto f\,'(x)## itself, which is the derivative.
If you like to get more confused, have a look at:
https://www.physicsforums.com/insights/the-pantheon-of-derivatives-i/
I stretched the things a little bit to get different objects for the many terms. And I have forgotten to mention that ##D## is a derivation.WWGD said:Yes, different books have different definitions. Mine uses 2xdx as the differential 1-form.
Parallel transport is a mathematical concept used to describe the movement of objects along a curved surface or manifold. It involves the transportation of an object along a path while keeping the object's orientation constant.
Parallel transport has many applications in various fields, such as physics, engineering, and computer graphics. It is commonly used in the study of curved spaces, such as in general relativity, to describe the motion of particles and light. It is also used in navigation and robotics to calculate the movement of objects along curved paths.
Regular transport involves moving an object from one point to another without any restrictions on its orientation. In contrast, parallel transport ensures that the object maintains the same orientation throughout its movement, even on curved surfaces. This makes it a more accurate method for describing the movement of objects in curved spaces.
One of the main benefits of parallel transport is its ability to accurately describe the movement of objects in curved spaces. This makes it a valuable tool in fields like physics and engineering. Additionally, parallel transport can also be used to calculate geodesics, which are the shortest paths between two points on a curved surface.
One limitation of parallel transport is that it can only be applied to objects that can be smoothly deformed, such as vectors or tensors. It also requires a well-defined curved surface or manifold to work properly. In some cases, parallel transport may also be mathematically complex and difficult to calculate, making it challenging to use in certain applications.