jitr
A fast just-in-time (JIT) compiled calculable R-matrix solver for parametric reaction models, production ready for calibration and uncertainty-quantification.
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Repository
A fast just-in-time (JIT) compiled calculable R-matrix solver for parametric reaction models, production ready for calibration and uncertainty-quantification.
Basic Info
Statistics
- Stars: 7
- Watchers: 3
- Forks: 1
- Open Issues: 21
- Releases: 22
Metadata Files
README.md
just-in-time R-Matrix (jitR)
A nuclear reaction toolkit, production ready for calibration and uncertainty-quantification, featuring:
- fast calculable $\mathcal{R}$-matrix solver for parametric reaction models
- built in uncertainty-quantified optical potentials
- built in nuclear data
- plenty of examples demonstrating the propagation of uncertainties into reaction observables and model calibration
Give your nuclear reaction UQ workflow a caffeine-kick with jitR!
quick start
pip install jitr
The release versions of the package are hosted at pypi.org/project/jitr/.
examples and tutorials
Various example scripts live in examples/. Tutorials live in examples/notebooks/.
In particular, check out:
- examples/notebooks/reactions.ipynb which demonstrates the use of the reactions submodule
- examples/notebooks/builtin_omps_uq.ipynb to see how to use the built-in uncertainty-quantified optical model potentials to propagate uncertainties into reaction observables
description
A framework for uncertainty-quantification of nuclear reaction observables using parametric reaction models. Consider a local coordinate-space potential $V(r;\theta)$ that is a function of some parameters $\theta$. Just write it like so:
python
def V(r,*theta):
a,b,c,... = theta
# calculate and return potential at radial coordinate r as a function of parameters a,b,c,...
Then, you can pass it along with many samples of $\theta$ into jitR to calculate many samples of the corresponding cross sections for your system and reaction of interest! The reaction observables jitR can calculate are represented as Workspace instances, and live in src/jitr/xs/.
Under the hood, jitR solves the radial Bloch-Shrödinger equation in the continuum using the calculable $\mathcal{R}$-Matrix method on a Lagrange-Legendre mesh. It is fast because it gives users the tools to precompute everything that they can for a system and reaction of interest, so given a single parameter sample, the minimal amount of compute is required to spit a cross section back out. For this reason, jitR is really suited to calculating an ensemble of observables for many parameter samples. Additionally, jitR relies on vectorized operations from numpy, as well as just-in-time (JIT) compilation from numba for the small subset of performance-critical code.
The theory generally follows: - Baye, D. (2015). The Lagrange-mesh method. Physics reports, 565, 1-107 - Descouvemont, P. (2016). An R-matrix package for coupled-channel problems in nuclear physics. Computer physics communications, 200, 199-219 - Descouvemont P. and Baye D. (2010). The R-matrix theory. Rep. Prog. Phys. 73 036301
with the primary difference being that this code uses the energy-scaled version of the Bloch-Shrödinger equation, with dimensionless domain, $s = k0 r$, where $r$ is the radial coordinate and $k0$ is the entrance channel wavenumber.
contributing, developing, and testing
To set up the repository for contributing, testing, access to non-release branches, access to the examples and notebooks, etc., clone the repository and install locally:
git clone git@github.com:beykyle/jitr.git
pip install -r ./jitr/requirements.txt
pip install -e ./jitr
then run the tests:
pytest jitr
Feel free to fork and make a pull request if you have things to contribute. There are many open issues, feel free to add more.
BAND
This package is part of the BAND Framework
citation
latex
@software{Beyer_JITR_2024,
author = {Beyer, Kyle},
license = {BSD-3-Clause},
month = oct,
title = {{JITR}},
url = {https://github.com/beykyle/jitr},
version = {1.3.0},
year = {2024}
}
Owner
- Name: Kyle Beyer
- Login: beykyle
- Kind: user
- Company: University of Michigan
- Repositories: 22
- Profile: https://github.com/beykyle
PhD candidate at the University of Michigan studying nuclear fission and nuclear reaction phenomenology away from stability
GitHub Events
Total
- Create event: 18
- Release event: 7
- Issues event: 20
- Watch event: 4
- Issue comment event: 11
- Push event: 104
- Pull request review event: 2
- Pull request event: 29
Last Year
- Create event: 18
- Release event: 7
- Issues event: 20
- Watch event: 4
- Issue comment event: 11
- Push event: 104
- Pull request review event: 2
- Pull request event: 29
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 5
- Total pull requests: 9
- Average time to close issues: 8 months
- Average time to close pull requests: 16 minutes
- Total issue authors: 2
- Total pull request authors: 1
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 8
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 4
- Pull requests: 9
- Average time to close issues: N/A
- Average time to close pull requests: 16 minutes
- Issue authors: 2
- Pull request authors: 1
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 8
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- beykyle (29)
Pull Request Authors
- beykyle (21)
Top Labels
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Packages
- Total packages: 1
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Total downloads:
- pypi 59 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 18
- Total maintainers: 1
pypi.org: jitr
Calculable R-matrix solver for quantum scattering using just-in-time compilation for performance.
- Documentation: https://jitr.readthedocs.io/
- License: BSD 3-Clause License Copyright (c) 2023, Kyle Beyer Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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Latest release: 2.5.1
published 6 months ago