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update NOTICE from FUSE default
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tomneiser authored Sep 11, 2024
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8 changes: 6 additions & 2 deletions NOTICE.md
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## Development Attribution

TGLFNN.jl was originally developed under the FUSE project by the Magnetic Fusion Energy group at General Atomics.
TGLFNN.jl was originally developed by the GA Theory division of the Magnetic Fusion Energy group at General Atomics. This work is supported by the U.S. DOE under DE-SC0018990 (MAST-U), DE-SC0024426 (FDP), DE-SC0022031 (ALF), DE-SC0017992 (AToM), DE-FG02-95ER54309 (GA Theory), DE-FC02-04ER54698 (DIII-D), and used computational resources at NERSC (DOE-AC02-05CH11231). Part of this work has been funded by the United Kingdom EPSRC Energy Programme EP/W006839/1 and the DOE Office of Workforce Development for Teachers and Scientists (WDTS) under the Science Undergraduate Laboratory Internships (SULI) program.

## Citation

If this software contributes to an academic publication, please cite it as follows:

> O. Meneghini, T. Slendebroek, B.C. Lyons, K. McLaughlin, J. McClenaghan, L. Stagner, J. Harvey, T.F. Neiser, A. Ghiozzi, G. Dose, J. Guterl, A. Zalzali, T. Cote, N. Shi, D. Weisberg, S.P. Smith, B.A. Grierson, _FUSE: A next generation framework for integrated design of fusion pilot plants_, Proceedings of the IAEA FEC 2023 Conference, (2023)
TGLF-NN:
> Tom Neiser, Orso Meneghini, Sterling Smith, Joseph McClenaghan, David Orozco, Joseph Hall, Gary Staebler, Emily Belli, Jeff Candy, _Database generation for validation of TGLF and retraining of neural network accelerated TGLF-NN_, APS Division of Plasma Physics Meeting Abstracts (2022)
GKNN:
> Tom Neiser, Orso Meneghini, Sterling Smith, Joseph McClenaghan, Tim Slendebroek, David Orozco, Brian Sammuli, Gary Staebler, Joseph Hall, Emily Belli, Jeff Candy, _Multi-fidelity neural network representation of gyrokinetic turbulence_, APS Division of Plasma Physics Meeting Abstracts (2023)
## Trademark Notice

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15 changes: 11 additions & 4 deletions README.md
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# TGLFNN.jl

Run TGLFNN, TGLF, and QLGYRO models
Run TGLF-NN, TGLF, and QLGYRO models

NOTE: Running TGLF and QLGYRO requires GACODE executables to be locally installed.

Link to instructions on GACODE installation: https://fuse.help/install.html#Install-GACODE

See the note following step 6 - you may need to replace mpif90-openmpi-mp with mpif90-openmpi-gcc12 in the platform-specific make file found in $GACODE_ROOT/platform/build/make.inc.OSX_MONTEREY and mpirun-openmpi-mp with mpirun-openmpi-gcc12 in the platform exec file found in $GACODE_ROOT/platform/exec/exec.OSX_MONTEREY.
Link to instructions on GACODE installation: https://gacode.io/build.html

## Online documentation
For more details, see the [online documentation](https://projecttorreypines.github.io/TGLFNN.jl/dev).

![Docs](https://github.com/ProjectTorreyPines/TGLFNN.jl/actions/workflows/make_docs.yml/badge.svg)

If this software contributes to an academic publication, please cite it as follows:

## Citation
TGLF-NN:
> Tom Neiser, Orso Meneghini, Sterling Smith, Joseph McClenaghan, David Orozco, Joseph Hall, Gary Staebler, Emily Belli, Jeff Candy, _Database generation for validation of TGLF and retraining of neural network accelerated TGLF-NN_, APS Division of Plasma Physics Meeting Abstracts (2022)
GKNN:
> Tom Neiser, Orso Meneghini, Sterling Smith, Joseph McClenaghan, Tim Slendebroek, David Orozco, Brian Sammuli, Gary Staebler, Joseph Hall, Emily Belli, Jeff Candy, _Multi-fidelity neural network representation of gyrokinetic turbulence_, APS Division of Plasma Physics Meeting Abstracts (2023)

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