Coordinate System Transformation: Lowering/Raising Indices Explained

In summary, Schutz uses a locally flat coordinate system to develop a simple formula for Riemann tensor components in terms of metric components like g^{ab} and g_{bu,sv}. This lets him get an even simpler formula for R_{abcd} by lowering the first index.
  • #1
GR191511
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In《Introducing Einstein's Relativity Ed 2》on page 106"lowering the first index with the metric,then it is easy to establish,for example by using geodesic coordinates..."
In 《A First Course in General Relativity - 2nd Edition》on page 159 "If we lower the index a,we get(in the locally flat coordinate system at its origin P)..."
What is the relationship between lowering or raising index and coordinate system transformation?
 
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  • #2
The only relationship is that the components of the "lowered" Riemann tensor ##R_{abcd}## have a particularly simple form in that locally flat coordinate system.
Schutz uses that locally flat coordinate system in his presentation because it enables him to develop a fairly simple formula for Riemann tensor components in terms of metric components like ##g^{ab}## and ##g_{bu,sv}##, rather than in terms of Christoffel symbols (equation 6.63).
He gets a fairly simple formula for ##R^a{}_{bcd}## in that coordinate system (equation 6.65) and then gets an even simpler formula (equation 6.67) for ##R_{abcd}##, ie by lowering the first index.
Most tensor formulas will have coordinate systems in which their component formulas are simple, and in other systems they will be horribly complex. A key challenge in GR is to choose the coordinate system in which the component formulas will be simple and easy(er) to manipulate.
 
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  • #3
andrewkirk said:
The only relationship is that the components of the "lowered" Riemann tensor ##R_{abcd}## have a particularly simple form in that locally flat coordinate system.
Schutz uses that locally flat coordinate system in his presentation because it enables him to develop a fairly simple formula for Riemann tensor components in terms of metric components like ##g^{ab}## and ##g_{bu,sv}##, rather than in terms of Christoffel symbols (equation 6.63).
He gets a fairly simple formula for ##R^a{}_{bcd}## in that coordinate system (equation 6.65) and then gets an even simpler formula (equation 6.67) for ##R_{abcd}##, ie by lowering the first index.
Most tensor formulas will have coordinate systems in which their component formulas are simple, and in other systems they will be horribly complex. A key challenge in GR is to choose the coordinate system in which the component formulas will be simple and easy(er) to manipulate.
Thank you!
 

FAQ: Coordinate System Transformation: Lowering/Raising Indices Explained

What is a coordinate system transformation?

A coordinate system transformation is the process of converting coordinates from one reference frame to another. This is often necessary when working with data or measurements collected in different coordinate systems.

What does it mean to lower or raise indices in a coordinate system transformation?

In a coordinate system transformation, lowering indices refers to converting from a higher-dimensional coordinate system to a lower-dimensional one, while raising indices refers to converting from a lower-dimensional coordinate system to a higher-dimensional one. This is done by adding or removing dimensions in the coordinate system.

When is a coordinate system transformation necessary?

A coordinate system transformation is necessary when working with data or measurements collected in different coordinate systems, or when converting between different types of coordinate systems, such as Cartesian and polar coordinates.

How is a coordinate system transformation performed?

A coordinate system transformation is performed by using mathematical equations or algorithms to convert the coordinates from one system to another. This may involve using transformation matrices, trigonometric functions, or other mathematical operations.

What are some common applications of coordinate system transformations?

Coordinate system transformations are commonly used in various fields, including engineering, physics, geology, and geography. They are often used in navigation systems, mapping and surveying, and in analyzing data collected from different sources or in different coordinate systems.

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