Tensors, metrics, differential geometry, and all that

In summary, the conversation discusses the difficulty of finding resources to learn general relativity, particularly in bridging the gap between undergraduate math and the math needed for GR. The speaker is frustrated and seeking recommendations for books and advice on what math topics to focus on. Several book recommendations are mentioned, including "Relativity: Special, General and Comological" by Wolfgang Rindler, "Introducing Einstein's Relativity" by Ray de'Inverno, and "A First Course in General Relativity" by Bernard Schutz. Another book, "Hartle," is also suggested as a physics-focused approach to learning GR. Finally, the speaker mentions that they have access to an academic library to find these resources.
  • #1
disknoir
19
0
I'm looking to learn general relativity, but I'm having a hard time. Frankly, I can't find any textbooks that I can understand.

There seems to be a gap between the maths I did at uni, and the maths of general relativity.

I've done vector calculus, differential equations, linear algebra and complex analysis etc, but I just can't seem to find any resources to bridge the gap.

While at uni, I mostly used the k.a. stroud engineering mathematics books.

Do I need to re-visit some of this from a more rigorous angle? I'm getting quite frustrated, as I no-longer have a tutor or class mates to discuss things with.

I'm starting a course in general relativity in February, and really want to get a head start.

I'd like to know what maths I need to learn to fill in the gaps in my knowledge, and in what order I should learn them.

Advice/book recommendations would be great.
Thanks
 
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  • #2
My favorite GR introductory books are Wolfgang Rindler's "Relativity: Special, General and Comological" and Ray de'Inverno's "Introducing Einstein's Relativity". Ray de'Inverno's book provides you lots of exercises on tensor calculus. Most of his exercises are straightforward, easy-to-do, but can help you to build up skills. Bernard Schutz's "A First Course in General Relativity" is also nice: many undergraduate GR books shun to discuss "differential forms" , but Bernard Schutz does not omit this.
 
  • #3
Thanks.

Luckily, I have access to an academic library; I'll have a look for them.
 
  • #5
for your interest in learning about general relativity! It's a fascinating and challenging field of study, and it's understandable that you're feeling frustrated with the lack of accessible resources for learning about the mathematical foundations of the theory.

First, let me assure you that you are on the right track with your background in vector calculus, differential equations, linear algebra, and complex analysis. These are all essential tools for understanding general relativity.

However, as you have noticed, there is a significant leap from the standard mathematics used in undergraduate courses to the mathematics used in general relativity. This is because general relativity is built upon the framework of differential geometry, which is a more advanced and abstract branch of mathematics.

To fill in the gaps in your knowledge, I would recommend starting with a textbook on differential geometry, such as "Introduction to Smooth Manifolds" by John M. Lee or "Differential Geometry of Curves and Surfaces" by Manfredo P. do Carmo. These books will introduce you to the concepts of tensors, metrics, and differential geometry, which are crucial for understanding general relativity.

It may also be helpful to revisit some of the mathematics you learned in your undergraduate courses from a more rigorous perspective. This will give you a deeper understanding of the concepts and prepare you for the more abstract mathematics of general relativity.

In terms of the order in which to learn these topics, it may be best to start with differential geometry and then move on to more specific topics in general relativity, such as the Einstein field equations and the Schwarzschild solution.

Additionally, there are many online resources available, such as lecture notes and video lectures, that can supplement your textbook learning and provide a platform for discussing and clarifying concepts with others.

I would also recommend reaching out to your future course instructor or a mentor in the field for personalized recommendations and guidance.

Don't get discouraged if it takes time and effort to fully grasp the mathematical foundations of general relativity. It is a complex subject, but with determination and perseverance, you can achieve a solid understanding and excel in your course. Best of luck in your studies!
 

1. What are tensors and what are they used for?

Tensors are mathematical objects that describe geometric quantities such as vectors and matrices in a way that is independent of any particular coordinate system. They are used in physics and engineering to represent physical quantities and to solve problems involving multi-dimensional spaces.

2. How do metrics relate to tensors?

Metrics are a special type of tensor that describes the distance, angle, and other geometric properties of a space. They are used in differential geometry to define the curvature and other properties of a space, and they play a crucial role in the theory of relativity.

3. What is differential geometry and why is it important?

Differential geometry is a branch of mathematics that studies the properties and behavior of spaces that are smooth and continuously varying. It is used in physics and engineering to describe the geometry of curved spaces, such as the surface of a sphere or the fabric of spacetime.

4. How are tensors and differential geometry used in machine learning?

Tensors and differential geometry are used in machine learning to model complex data sets and make predictions based on that data. Tensors can be used to represent multi-dimensional data, while differential geometry can be used to analyze the relationships between different data points and make more accurate predictions.

5. What are some real-world applications of tensors and differential geometry?

Tensors and differential geometry have many practical applications, including in physics, engineering, computer graphics, and machine learning. For example, they are used in the design of structures such as bridges and buildings, in the development of computer vision algorithms, and in the analysis of data from satellites and other sensors.

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