What is an orthogonal chart in the context of Gaussian Normal Coordinates?

In summary: Orthogonal curvilinear coordinates are used in mathematical physics to diagonalize charts in order to solve problems.Gaussian normal coordinates have a metric of the formds^2 = -dt^2 + g_{ij} dx^i dx^jThis implies that:1) the t coordinate measures proper time of "stationary" observers, i.e. observers with constant spatial coordinates.2) the time coordinate is orthogonal to the space coordinates (more precisely, the vector \partial / \partial t is orthogonal to all of the vectors \partial / \partial x^i )These are also known as synchronous coordinates, a common example from cos
  • #1
quantum123
306
1
What are Gaussian Normal Coordinates?
 
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  • #2
Gaussian normal coordinates have a metric of the form

[tex]
ds^2 = -dt^2 + g_{ij} dx^i dx^j
[/tex]

This implies that:

1) the t coordinate measures proper time of "stationary" observers, i.e. observers with constant spatial coordinates.

2) the time coordinate is orthogonal to the space coordinates (more precisely, the vector [itex]\partial / \partial t[/itex] is orthogonal to all of the vectors [itex]\partial / \partial x^i[/itex] )

These are also known as synchronous coordinates, a common example from cosmology is comvoing coordinates.
 
  • #3
quantum123 said:
What are Gaussian Normal Coordinates?

There are various kinds of "normal coordinates" used in Riemannian geometry (positive definite metric tensors) and semi-Riemannian geometry (allows indefinite metric tensors, such as occur in Lorentzian manifolds as used in general relativity).

In Riemannian geometry, the idea is to fix a point P and to construct a chart in which metric tensor assumes the usual flat space Euclidean form at P, with the Christoffel coefficients and first partials of the metric components all vanishing at P, so that the quadratic deviation of the metric at points near P are given in terms of the components of the curvature tensor at P. It is important to understand that such charts are not unique; what is important is that near P, the metric can be approximated by the curvature components at P. See http://en.wikipedia.org/wiki/Geodesic_normal_coordinates

In general relativity, Riemann normal coordinates are often used as a technical device in various places, and Fermi normal coordinates are also useful at times. See section 3.1-3.2 of http://relativity.livingreviews.org/Articles/lrr-2004-6/title.html#articlese3.html for more about Riemann and Fermi normal coordinates.

pervect said:
Gaussian normal coordinates have a metric of the form

[tex]
ds^2 = -dt^2 + g_{ij} dx^i dx^j
[/tex]

I've only seen that usage in the book by Wheeler and Cuifolini, Inertia and Gravitation. Most people would just call these synchronous coordinates.
 
Last edited by a moderator:
  • #4
Chris Hillman said:
I've only seen that usage in the book by Wheeler and Cuifolini, Inertia and Gravitation. Most people would just call these synchronous coordinates.

MTW uses it too, that's where I looked it up. (See pg 717).
 
Last edited:
  • #5
Here I stand, corrected, not unlike a normal vector on a surface

pervect said:
MTW uses it too, that's where I looked it up. (See pg 717).

So they do! Thanks for reminding me.
 
  • #6
While we're on this topic, what are orthogonal curvilinear coordinates? I briefly encountered them a while ago & learned to take gradients etc, but I'm looking for a more detailed treatment.
 
  • #7
In this context, an "orthogonal chart" probably means a chart in which the metric appears "diagonalized", e.g. the Schwarzschild chart is diagonalized but the Eddington chart is not (because of the "cross-terms" du \, dr, which signify that the coordinate vectors are "skew", i.e. non-orthogonal).

Many models, e.g. the Kerr vacuum, possesses no "diagonal" charts.
 

FAQ: What is an orthogonal chart in the context of Gaussian Normal Coordinates?

What are Gaussian Normal Coordinates?

Gaussian Normal Coordinates are a type of coordinate system used in mathematics and physics to describe the position of a point in space. They are based on the concept of a normal distribution, also known as a Gaussian distribution, which is a mathematical function that describes the probability of a random variable falling within a certain range of values.

How are Gaussian Normal Coordinates different from other coordinate systems?

Gaussian Normal Coordinates are unique in that they are based on a normal distribution, which allows for a more accurate representation of the probability of a point's position in space. They also take into account the curvature of space, making them particularly useful in the field of general relativity.

What is the purpose of using Gaussian Normal Coordinates?

Gaussian Normal Coordinates are primarily used in mathematical and physical models to simplify the representation of complex systems. They allow for a more intuitive understanding of the distribution of points in space and can be used to solve a variety of equations in physics, engineering, and statistics.

What are the limitations of Gaussian Normal Coordinates?

While Gaussian Normal Coordinates are widely used and have many applications, they do have some limitations. For example, they are not suitable for describing systems with discontinuities or singularities. They also cannot be used in non-Euclidean spaces.

How are Gaussian Normal Coordinates used in real-world applications?

Gaussian Normal Coordinates have a wide range of applications in various fields, such as physics, engineering, and statistics. They are used to model and analyze complex systems, such as the behavior of particles in a gas, the distribution of galaxies in the universe, and the movement of objects in space. They are also used in data analysis and machine learning algorithms to identify patterns and make predictions.

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