Initial Conditions of Astrophysical Simulations in 3D

In summary, the conversation discusses the use of a N-body code in 3D for gravitational problems and the creation of an OpenGL visualization. The speaker is looking for resources to generate more interesting initial conditions, such as those resembling a real galaxy. Suggestions are made to use 2MASS data or create a model for star and velocity distributions. However, there is no complete description of the Milky Way due to the limitations of observation. A 4-dimensional description is needed to achieve the desired results, which remains an unsolved problem.
  • #1
jwdozer327
1
0
So I've been playing with a little N-body code in 3D for gravitational problems and have made an OpenGL visualization to go along with it. I have been generating initial conditions (positions and velocities) using explicit formulas. I was wondering of anyone knew of any resources for getting more "interesting" initial conditions.

Right now all I generate is a uniform distribution or a spherical distribution. Is there any way to get positions and velocities for something that looks like a real galaxy or something? Does NASA have some huge CSV file for the milky way or something crazy? Google has failed me thus far. Thanks for any direction!
 
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  • #2
You could try to get 2MASS data, but they don't have stars uniform over the whole galaxy.
Some model for the star and velocity distributions could be interesting, too. Take stars nearby, and assume that the whole galaxy looks similar?
 
  • #3
Well, there is the JPL "Horizons" server... it gives data about Solar System objects. It's pretty funky and FTP-ish. Not very user-friendly. I don't know of anything similar for galactic positions of stars.
 
  • #4
There is no complete description of the Milky Way because it is impossible to observe the entire galaxy while we are stuck within it. A large portion of the other side of the MW is obscured by the galactic core.
 
  • #5
You need a 4 dimensional description to achieve what you are attempting. That remains an unsolved problem.
 

1. What are initial conditions in astrophysical simulations in 3D?

Initial conditions refer to the starting conditions or parameters that are set at the beginning of an astrophysical simulation in 3D. These conditions include the physical properties such as mass, density, temperature, and velocity of the simulated objects or systems.

2. Why are initial conditions important in astrophysical simulations?

Initial conditions play a crucial role in determining the outcomes of astrophysical simulations. They provide the starting point for the simulation and influence the evolution of the system over time. The accuracy and reliability of the initial conditions greatly impact the validity of the simulation results.

3. How are initial conditions determined in astrophysical simulations in 3D?

The initial conditions for astrophysical simulations are determined using a combination of theoretical predictions, observational data, and numerical techniques. These methods involve analyzing the physical properties of the objects or systems being simulated and using mathematical models to generate the initial conditions.

4. Can initial conditions be changed during the course of an astrophysical simulation?

In most cases, initial conditions are not changed once the simulation has begun. This is because any changes to the initial conditions can significantly alter the outcome of the simulation, making it difficult to compare the results with previous simulations or real-world observations. However, there are some cases where researchers may choose to vary the initial conditions to study the effects of different parameters on the simulation.

5. How do initial conditions affect the accuracy of astrophysical simulations in 3D?

The accuracy of astrophysical simulations depends heavily on the accuracy of the initial conditions. If the initial conditions are not representative of the real-world objects or systems being simulated, the results of the simulation may not accurately reflect reality. Thus, it is essential for scientists to carefully determine and validate the initial conditions before running a simulation to ensure the accuracy of their results.

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