Question about Geodesic Equation Derivation using Lagrangian

In summary, the Lagrangian is a function of coordinates and not derivatives, so the metric tensor is zero.
  • #1
LoadedAnvils
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I'm trying to derive the Geodesic equation, [itex]\ddot{x}^{α} + {Γ}^{α}_{βγ} \dot{x}^{β} \dot{x}^{γ} = 0[/itex].

However, when I take the Lagrangian to be [itex]{L} = {g}_{γβ} \dot{x}^{γ} \dot{x}^{β}[/itex], and I'm taking [itex]\frac{\partial {L}}{\partial \dot{x}^{α}}[/itex], I don't understand why the partial derivative of [itex]{g}_{γβ}[/itex] with respect to [itex]\dot{x}^{α}[/itex] is zero.

I've been looking for a derivation that explained this step but I'm having no luck.

Anyone care to explain?
 
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  • #2
metric tensor is function of coordinates only,not derivatives of it.So it is zero.
 
  • #3
LoadedAnvils said:
I'm trying to derive the Geodesic equation, [itex]\ddot{x}^{α} + {Γ}^{α}_{βγ} \dot{x}^{β} \dot{x}^{γ} = 0[/itex].

However, when I take the Lagrangian to be [itex]{L} = {g}_{γβ} \dot{x}^{γ} \dot{x}^{β}[/itex], and I'm taking [itex]\frac{\partial {L}}{\partial \dot{x}^{α}}[/itex], I don't understand why the partial derivative of [itex]{g}_{γβ}[/itex] with respect to [itex]\dot{x}^{α}[/itex] is zero.

I've been looking for a derivation that explained this step but I'm having no luck.

Anyone care to explain?


Although you might think that since [itex] \dot{x} [/itex] is related to x, the derivative should be zero, we actually consider the two to be separate variables. This is because in the lagrangian formalism, you are considering functions, not positions (you are techinically varying over paths). To see how they are independent, consider a function [itex]f(t) = x[/itex]. Since all we know is that it equals x at t, then the first derivative is not fixed (since the derivative is the slope of the tangent, think of how many lines you can draw through a single point). Since we are considering all functions, we don't actually know anything about the first derivative, so we have to treat it as an independent parameter.

In that case, you'll notice that the metric is not written to have explicit dependence on [itex] \dot{x} [/itex], which is for a reason, because the metric is chosen to not have any dependence on [itex] \dot{x} [/itex]. Physically, this is because the distance between two points doesn't depend on the speed that you are going, so the metric field shouldn't depend on [itex] \dot{x} [/itex]
 
  • #4
Thank you both. I can now continue with the derivation.
 
  • #5


The reason why the partial derivative of {g}_{γβ} with respect to \dot{x}^{α} is zero is because the metric tensor {g}_{γβ} does not depend on the velocity terms \dot{x}^{α}. The metric tensor is a function of the position coordinates x^{α} and it describes the geometry of the space in which the particle is moving. In the Lagrangian formulation, the partial derivative \frac{\partial {L}}{\partial \dot{x}^{α}} represents the momentum of the particle in the direction of \dot{x}^{α}. Since the metric tensor does not depend on the velocity terms, it means that the momentum in that direction is conserved and therefore the partial derivative is zero.

To further understand this, let's consider the simpler case of a particle moving in a flat Euclidean space with no curvature. In this case, the metric tensor is simply the Kronecker delta {\delta}_{γβ} and it is constant, meaning it does not depend on the position or velocity terms. In this case, the Lagrangian would be {L} = {\delta}_{γβ} \dot{x}^{γ} \dot{x}^{β} and the partial derivative \frac{\partial {L}}{\partial \dot{x}^{α}} would also be zero. This is because the momentum in any direction is conserved in a flat space.

In summary, the reason why the partial derivative of the metric tensor with respect to the velocity terms is zero is because the metric tensor is a function of the position coordinates and not the velocity terms. This is a fundamental property of the metric tensor and is crucial in the derivation of the geodesic equation.
 

FAQ: Question about Geodesic Equation Derivation using Lagrangian

What is the Geodesic Equation?

The Geodesic Equation is a mathematical expression that describes the shortest path between two points on a curved surface (such as a planet or a curved space-time). It is derived from the concept of a geodesic, which is a curve that follows the shortest distance between two points on a curved surface.

How is the Geodesic Equation derived using Lagrangian?

The Geodesic Equation can be derived using the Lagrangian formalism in the field of variational calculus. This approach involves minimizing the action integral, which is a function of the Lagrangian and the path of the particle. The resulting Euler-Lagrange equations then give rise to the Geodesic Equation.

What is the significance of the Lagrangian in the derivation of the Geodesic Equation?

The Lagrangian is a mathematical function that encodes the dynamics of a system. In the case of the Geodesic Equation, the Lagrangian represents the energy of a particle moving along a curved path. It allows us to take into account the effects of both the particle's position and velocity on its motion, resulting in a more accurate and comprehensive derivation of the Geodesic Equation.

Can the Geodesic Equation be used to describe the motion of particles in all curved spaces?

Yes, the Geodesic Equation is a general mathematical expression that applies to any curved space. It is a fundamental concept in the field of differential geometry and is used in a variety of scientific disciplines, from general relativity to computer graphics.

What are some real-world applications of the Geodesic Equation?

The Geodesic Equation has numerous practical applications. In physics, it is used to describe the motion of particles in curved space-time, such as in the theory of general relativity. It is also used in geodesy to study the shape and curvature of the Earth's surface. In computer graphics, the Geodesic Equation is used to create realistic 3D models of curved objects and surfaces. It also has applications in optimization and control theory, robotics, and navigation systems.

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