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Sequential Monte Carlo with NUTS for Gravitational Wave Inference

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# SHARPy
### Sequential HAmiltonian Riemann montecarlo Python sampler for cutting-edge Gravitational Wave inference
© 2025- Gabriele Demasi, Walter Del Pozzo

### Installation 
For avoiding package incompatibilities, create a dedicated conda environment 
`conda create --name sharpy_env python==3.11` `conda activate sharpy_env`

or if conda is not available

`python -m venv /path_to/sharpy_env` 
`source /path_to/sharpy_env/bin/activate`

then install SHARPy: 
`git clone git@github.com:gabrieledemasi/sharpy.git` 
`cd sharpy` 
`pip install .`

To run on GPU please install this version of JAX:
`pip install --upgrade "jax[cuda12]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html`

## Examples
This [notebook](Examples/11D_gaussian_mixture.ipynb) contains a simple test case( a 11D bimodal gaussian mixture) that can be run on a laptop. The run time should be around 1 min, depending on the hardware.

## Acknowledgements
If you use SHARPy in your research, please cite [Demasi et al, 2026](https://arxiv.org/abs/2601.02336)
```
@article{Demasi:2026ltw,
    author = "Demasi, Gabriele and others",
    title = "{The Sequential Monte Carlo goes NUTS: Boosting Gravitational-Wave Inference}",
    eprint = "2601.02336",
    archivePrefix = "arXiv",
    primaryClass = "gr-qc",
    month = "1",
    year = "2026"
}
```

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