forked from Aquila-Consortium/JaxPM_highres
52 lines
1.4 KiB
Markdown
52 lines
1.4 KiB
Markdown
# Design Document for JaxPM
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This document aims to detail some of the API, implementation choices, and internal mechanism.
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## Objective
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Provide a user-friendly framework for distributed Particle-Mesh N-body simulations.
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## Related Work
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This project would be the latest iteration of a number of past libraries that have provided differentiable N-body models.
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- [FlowPM](https://github.com/DifferentiableUniverseInitiative/flowpm): TensorFlow
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- [vmad FastPM](https://github.com/rainwoodman/vmad/blob/master/vmad/lib/fastpm.py): VMAD
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- Borg
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In addition, a number of fast N-body simulation projets exist out there:
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- [FastPM](https://github.com/fastpm/fastpm)
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- ...
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## Design Overview
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### Coding principles
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Following recent trends and JAX philosophy, the library should have a functional programming type of interface.
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### Illustration of API
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Here is a potential illustration of what the user interface could be for the simulation code:
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```python
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import jaxpm as jpm
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import jax_cosmo as jc
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# Instantiate differentiable cosmology object
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cosmo = jc.Planck()
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# Creates initial conditions
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inital_conditions = jpm.generate_ic(cosmo, boxsize, nmesh, dtype='float32')
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# Create a particular solver
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solver = jpm.solvers.fastpm(cosmo, B=1)
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# Initialize and run the simulation
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state = solver.init(initial_conditions)
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state = solver.nbody(state)
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# Painting the results
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density = jpm.zeros(boxsize, nmesh)
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density = jpm.paint(density, state.positions)
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```
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