Understanding the Square Root Loop and Its Construction on S^1 and RP^1

In summary, the square root loop \sigma : S^1 \longrightarrow RP^1 ; z=\cos 2\pi t +i\sin 2\pi t \longrightarrow [\cos \pi t, \sin \pi t] is a homeomorphism due to the antipodal equivalence relation, which identifies antipodal points on the circle. The proof can be constructed by showing that \sigma is a bijection and then constructing a continuous inverse using the quotient topology. This can be done by considering the projection map and using the fact that the quotient space has the property of uniqueness for continuous functions.
  • #1
madness
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My notes claim that the square root loop [tex] \sigma : S^1 \longrightarrow RP^1 ; z=\cos 2\pi t +i\sin 2\pi t \longrightarrow [\cos \pi t, \sin \pi t] [/tex] is a homeomorphism, where [x,y] is an equivalence class given by the antipodal equivalence relation on the circle. However, this map doesn't even seem to be a bijection. The proof simply says "by construction". Can anyone help?
 
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  • #2
I'm assuming [x,y] refers to the equivalence class of the point [itex](x,y)[/itex] under the antipodal equivalence relation.

madness said:
However, this map doesn't even seem to be a bijection.
Why don't you think it's a bijection? Are you doubting it's injective or surjective? The map is indeed a bijection so it would be helpful if you could point out why you doubt this.

The proof simply says "by construction". Can anyone help?
The two simplest approaches I can think of is:
1) Show that \sigma is a bijective first. Then show that it's open and continuous by the usual set-theoretic arguments involving the image and pre-image of open sets (or just basis elements).
2) Show that \sigma is continuous, and construct a continuous inverse.

Personally I prefer (2), and using a couple of facts about quotient topologies it's a pretty simple construction (construct a map [itex]S^1 \to S^1[/itex] that sends [itex]\cos(\pi t)+i\sin(\pi t) \mapsto \cos(2\pi t) + i\sin(2\pi t)[/itex] and then factor it through [itex]RP^1[/itex]).
 
  • #3
Well the notes switch between using homogeneous coordinates where all (non-zero) points on a line are identified and using the antipodal equivalence relation, but they are the same for practical purposes.
Well I'm having trouble seeing how the inverse maps to just 1 element on the circle. Taking the inverse projection of an element [z] in RP1 gives {z,-z} in S1. I can see conceptually that the change from 2pi to pi makes it 1 to 1 but still find it difficult to formalise mathematically.
 
  • #4
madness said:
Well I'm having trouble seeing how the inverse maps to just 1 element on the circle. Taking the inverse projection of an element [z] in RP1 gives {z,-z} in S1.
That would be the case if [itex]\sigma[/itex] sent x to [x], but it does not. To see why this doesn't give any problems suppose [itex]\sigma(\cos(2\pi t_1)+i\sin(2\pi t_1)) = \sigma(\cos(2\pi t_2) + i\sin(2\pi t_2))[/itex] with [itex]t_1,t_2 \in [0,1)[/itex] and show that you must get [itex]t_1=t_2[/itex].


To conceptually visualize why this works consider the map [itex]f : S^1 \to S^1[/itex] defined by [itex]f(\cos(2\pi t) + i \sin(2\pi t)) = \cos(\pi t) + i \sin (\pi t)[/itex]. This sends the point at an angle v to the point at an angle v/2. Thus the image of the whole sphere lies entirely in the first and second quadrant. If you think of it as a movement around the circle parameterized by t, then you can think of f as slowing down the movement speed to 50% so we only get half the way around so we never get two antipodal points, but we get a representative for every pair of antipodal points.
 
  • #5
By the projection i meant the projection p: S1 -> RP1; z->[z] for the antipodal equivalence relation. And yes I do understand this conceptually but it seems I'll need to use the inverse of this projection to construct the inverse for the square root loop.
 
  • #6
You probably know this, but let me just re-iterate one important result. Given a topological space X, and an equivalence relation ~ on X we can construct the quotient space X/~. This quotient space posses the property:
- Let [itex]g : X \to Y[/itex] be a continuous function with the property that g(x)=g(y) if x~y. Then there exists a unique continuous function [itex]g' : (X/\sim) \to Y[/itex] such that [itex]g' \circ p = g[/itex] where [itex]p : X \to X/\sim[/itex] is the projection map.
This property is the key to constructing the inverse. As you say it's kind of hard since you somehow have to invert the projection and then show that in the end we end up with a well-defined function. With this property this is taken care of automatically.

Let ~ be the antipodal equivalence relation. Now basically what you do is that you construct the inverse map you want, but for a moment ignore that we are working in [itex]RP^1[/itex] and instead consider working in [itex]S^1[/itex]. So you define [itex]\tau : S^1 \to S^1[/itex] by
[tex]\tau(\cos(\pi t) + i \sin(\pi t)) = \cos(2\pi t) + i\sin(2\pi t)[/tex]
You can now show that if x~y, then [itex]\tau(x)=\tau(y)[/itex] (HINT: x~y iff x and y differ by a multiple of pi, which in turns becomes a multiple of 2pi, which disappears).

Thus by the previous result we get an induced map [itex]\tau' : (S^1/\sim) \to S^1[/itex] and since [itex](S^1/\sim) = RP^1[/itex] you can check that [itex]\tau'[/itex] is the correct inverse.
 

FAQ: Understanding the Square Root Loop and Its Construction on S^1 and RP^1

What is the Square Root Loop on S1 and RP1?

The Square Root Loop on S1 and RP1 is a mathematical concept that describes the movement of a point on a circle or a half-circle as it undergoes a square root transformation. It is also known as the "square root parametrization" or "square root map".

How is the Square Root Loop constructed on S1 and RP1?

The Square Root Loop is constructed by taking a point on the circle or half-circle and applying the square root transformation, which involves taking the square root of the distance from the origin to the point. This process is repeated for each new point on the circle or half-circle, resulting in a looping pattern.

What is the significance of understanding the Square Root Loop on S1 and RP1?

The Square Root Loop has various applications in mathematics and physics, including in the study of dynamical systems, chaos theory, and geometric transformations. It also has connections to other mathematical concepts, such as the Mandelbrot set and Julia sets.

Can the Square Root Loop be visualized?

Yes, the Square Root Loop can be visualized using a graph or by plotting points on a circle or half-circle. It is often represented as a looping pattern or fractal shape.

Are there any real-world applications of the Square Root Loop?

The Square Root Loop has been used in various fields, including in computer graphics, image processing, and cryptography. It also has applications in understanding complex systems and patterns in nature, such as the growth of plants and the formation of coastlines.

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