Numerical Solution of Complex Systems in GR

In summary, the conversation discusses the concept of using numerical methods to solve the Einstein field equations for a system of two black holes orbiting each other. This involves specifying the stress-energy tensor and metric on a Cauchy surface and solving the field equations with those boundary conditions. The need for the second fundamental form, which describes how the Cauchy surface is embedded in the spacetime, is also mentioned. Potential resources for learning more about this topic are mentioned, including the book "Wald."
  • #1
epovo
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TL;DR Summary
If we could solve the EFE's for a given stress-energy configuration, the LHS of the equation would represent the whole history of the system
Please help me confirm that I understand this correctly.
Imagine a system comprised of two black holes orbiting each other, which will eventually merge. At any point in time we describe the stress-energy tensor of the system. Assume that we could solve the EFE's for every point (t,x,y,z). This solution would contain the whole future (and past) evolution of the system, including the merge.
It is my understanding that this is not really possible, so we have to do the following: we take ##T_{\alpha\beta}(t_0)## and solve numerically for ##G_{\alpha\beta}(t_0)##. Then we compute how ##T_{\alpha\beta}## changes in a short period Δt, in which the configuration of mass and energy follow whatever geodesics are there, obtaining ##T_{\alpha\beta}(t_0+\Delta t)##. Now we do it again, giving us ##G_{\alpha\beta}(t_0+\Delta t)##
Is this how numerical methods work, in essence?
 
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  • #2
That sounds like you're trying to describe GR as an initial value problem. You specify the stress-energy tensor and metric on a Cauchy surface, which is to say an acausal surface that spans the causal past or future of all events (so "all of space at one time"), and then solve the field equations with those boundary conditions. It's certainly possible to do that (and the ADM formalism is well-adapted to it), but it isn't the only way to do things.
 
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  • #3
Thank you @Ibix - where can I learn more about this topic? The description I gave is the only way I could come up with
 
  • #4
Ibix said:
That sounds like you're trying to describe GR as an initial value problem. You specify the stress-energy tensor and metric on a Cauchy surface, which is to say an acausal surface that spans the causal past or future of all events (so "all of space at one time"), and then solve the field equations with those boundary conditions. It's certainly possible to do that (and the ADM formalism is well-adapted to it), but it isn't the only way to do things.
You also need the second fundamental form.
 
  • #5
martinbn said:
You also need the second fundamental form.
I don't even know what that is :frown:
 
  • #6
epovo said:
Thank you @Ibix - where can I learn more about this topic? The description I gave is the only way I could come up with
I read about it in Wald, and I need to revisit it, apparently.

I think the second fundamental form describes how the Cauchy surface is embedded in the spacetime, but I might be wrong about that.
 
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1. What is numerical solution in the context of General Relativity (GR)?

Numerical solution in GR refers to the use of computational methods to solve complex systems of equations that arise in the study of General Relativity. These methods involve breaking down the equations into smaller, more manageable parts and using algorithms to approximate the solutions.

2. Why is numerical solution necessary in GR?

Numerical solution is necessary in GR because many of the equations and systems that arise in this field are too complex to be solved analytically. This means that they cannot be solved using traditional mathematical methods and require the use of numerical techniques to obtain solutions.

3. What are some common numerical methods used in solving complex systems in GR?

Some common numerical methods used in solving complex systems in GR include finite difference methods, finite element methods, and spectral methods. These methods involve discretizing the equations and using iterative algorithms to approximate the solutions.

4. What are the advantages and disadvantages of using numerical solution in GR?

The main advantage of using numerical solution in GR is that it allows for the study of complex systems that cannot be solved analytically. It also allows for the incorporation of more realistic and complicated physical conditions. However, the main disadvantage is that numerical solutions are only approximations and may not be as accurate as analytical solutions.

5. How do scientists ensure the accuracy of numerical solutions in GR?

To ensure the accuracy of numerical solutions in GR, scientists use a variety of techniques such as convergence tests, error analysis, and comparison with known analytical solutions. They also continuously refine and improve their numerical methods to increase the accuracy of the solutions.

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