Metric and Covariant Derivative

In summary, the convention that is used for the metric and the covariant derivative is 'mostly minus'.
  • #1
TriTertButoxy
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I've seen read a lot of books where they use different sign conventions for the metric and the covariant derivative. I'd like to ask the physics community the following questions:

I've seen both, the (+, -, -, -) and (-, +, +, +), conventions used for the metric, and I've also seen both, [itex]D_\mu = \partial_\mu + i g T^a A_\mu^a[/itex] and [itex]D_\mu = \partial_\mu - i g T^a A_\mu^a[/itex], in the literature.

1. Which convention, for the metric and the covariant, do you use? and,

2. Why? Do you find one more convenient over the other? or were you brought up to believe in one convention, and has it stuck with you ever since?
 
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  • #2
Interesting!
I use the 'mostly minus' metric: (+, -, -, -), and use the 'plus' covariant derivative. Essentially I use this convention since I was trained to use this one first. But, I've found that the (+, -, -, -) convention is nicer for me in particle physics since the pole structure in the propagators are more transparent.

In the mostly minus metric, the on-shell condition is [itex]p^2 = m^2[/itex], where as in the mostly plus metric, the on-shell condition is [itex]p^2 = -m^2[/itex].
 
  • #3
I've learned to use both the (+---) and (-+++) conventions. It's not easy at first switching between the two, but after awhile you get used to it. For me it's not preference, but necessity because different books are written in different conventions and I'm not going to not read a book just because of a sign convention.

There are other conventions that differ from book to book, such as normalization of spinors, normalization of creation and annihilation operators, and normalization of Fock states. Again, I ended up learning all of them. What's nice is that most of the time there are only two different conventions. If there were a bunch then it'd be confusing.
 

FAQ: Metric and Covariant Derivative

What is the difference between metric and covariant derivative?

The metric derivative is a generalization of the derivative to curved spaces, where the metric tensor is used to define the distance between points. The covariant derivative is a generalization of the derivative to curved spaces in which the basis vectors are allowed to vary from point to point.

Why is the covariant derivative useful?

The covariant derivative is useful because it allows us to define a derivative that is independent of the coordinate system used to describe the space. This makes it easier to work with vector fields and tensors in curved spaces.

How is the covariant derivative related to the metric tensor?

The covariant derivative is defined using the metric tensor, as it is used to lower the indices of the derivative so that it is compatible with the basis vectors of the space. The metric tensor also plays a role in defining the Christoffel symbols, which are used in the covariant derivative.

Can the covariant derivative be extended to higher dimensions?

Yes, the covariant derivative can be extended to higher dimensions, and is an important tool in differential geometry. In higher dimensions, the covariant derivative is defined using the connection, which is a generalization of the Christoffel symbols.

What are some practical applications of the metric and covariant derivative?

The metric and covariant derivative are used in many areas of physics, including general relativity, electromagnetism, and fluid mechanics. They are also used in computer graphics and computer vision to analyze images and shapes in curved spaces. In addition, they have applications in machine learning and optimization algorithms.

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