Good treatment of Affine Geometry?

In summary, someone looking for a concise, clear treatment of affine geometry should read Bishop and Crittenden, "Geometry of Manifolds", Chapter 5: Connections, Chapter 6: Affine Connections, or Lovelock and Rund, "Tensors, Differential Forms and Variational Principles", Dover 1989, Chapter 3: Tensor Analysis on Manifolds.
  • #1
Matterwave
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Hey guys, I'm looking for a good treatment (good = concise, and clear) of affine geometry. Connections, parallel transport, etc. I'm looking for this from a mathematical P.O.V. Most of the differential geometry books I have deal only with the exterior forms, and general manifolds without this added structure. The GR books I have deal with this, but always with an assumed symmetric connection (no torsion), and they tend to go at it from a physicist's point of view.

I'm not looking for anything too rigorous (by too rigorous, I mean, like at the level of a tome for professional mathematicians, I'm not looking to read 600+ pages about this material), but rigorous enough so that I'll have a good foot hold in this topic.

Any suggestions? Thanks.
 
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  • #2
I would suggest Bishop and Crittenden, "Geometry of Manifolds", Chapter 5: Connections, Chapter 6: Affine Connections.

Another option is Lovelock and Rund, "Tensors, Differential Forms and Variational Principles", Dover 1989, Chapter 3: Tensor Analysis on Manifolds.

Personally I prefer the first one.
 
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  • #3
Matterwave said:
I'm not looking for anything too rigorous (by too rigorous, I mean, like at the level of a tome for professional mathematicians, I'm not looking to read 600+ pages about this material), but rigorous enough so that I'll have a good foot hold in this topic.
Any suggestions? Thanks.

These are fairly advanced topics (second or third year graduate work), so I'm not sure what you can say about them without being "too rigorous". However, John Lee's Riemannian Manifolds: An Introduction to Curvature is only 224 pages long, and he's an excellent writer. This is definitely a math book, though.

Another great book between physics and math is Arnol'd's Mathematical Methods of Classical Mechanics. Appendix I begins by talking about parallel transport.
 
  • #4
A not-so-rigorous text can be good old Schouten, "Tensor Analysis for Physicists", Chapter V, some 20 pages.
 
  • #5
By not so rigorous, I just mean I didn't want to read like several hundred pages of exposition with every caveat and potential exception explored. For example, I'm perfectly fine in assuming that partial derivatives commute without having to explicitly show that the function I'm acting them on has to fit certain criteria (continuous in a small epsilon disk around where I'm taking those derivatives I believe...so you can't have some connical section of discontinuity or something?). That's all I'm sayin. Thanks for the recommendations, I'll take a look.
 

1. What is affine geometry?

Affine geometry is a branch of mathematics that studies geometric properties and transformations of objects that are preserved under parallel lines. It is based on the concept of affine transformation, which is a type of mapping that preserves straight lines and ratios of distances between points.

2. How is affine geometry different from Euclidean geometry?

Affine geometry differs from Euclidean geometry in that it does not require the notion of distance or angles to be defined. Instead, it focuses on the relationships between points and parallel lines, and how they are transformed under affine transformations. In Euclidean geometry, distance and angles play a significant role in defining geometric properties.

3. What are some applications of affine geometry?

Affine geometry has many practical applications, such as computer graphics, computer vision, and image processing. It is also used in physics, engineering, and architecture to model and analyze objects that undergo affine transformations, such as rotations, translations, and shears.

4. How is affine geometry relevant to machine learning?

Affine geometry has become increasingly relevant in machine learning, specifically in the field of deep learning. Affine transformations are used to preprocess data, such as images, before training a neural network. They can also be used to implement data augmentation techniques, which help improve the performance of machine learning models.

5. What are some key properties of affine geometry?

Some key properties of affine geometry include the preservation of parallel lines, ratios of distances, and collinearity under affine transformations. Another important property is that affine transformations can be represented by matrices, making them easy to manipulate and analyze mathematically.

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