This repository contains all code and data necessary to generate the results in Wave function-based emulation for nucleon-nucleon scattering in momentum space (arXiv:2301.05093). It extends the coordinate-space Kohn variational principle (KVP) emulator to momentum-space (including coupled channels) with arbitrary boundary conditions, which enable the mitigation of spurious singularities known as Kohn anomalies. It also provides comparisons with the Newton's variational principle (NVP) emulator for selected partial waves and NN observables using the semilocal momentum-space (SMS) regularized chiral potential at N4LO+.
For potential data files see the following link: https://zenodo.org/record/8066491
- This project relies on
python=3.9
. It was not tested with different versions. To view the entire list of required packages, seeenvironment.yml
. - Clone the repository to your local machine.
- Once you have
cd
into this repo, create a virtual environment (assuming you haveconda
installed) via
conda env create -f environment.yml
- Enter the virtual environment with
conda activate scattering-emulators-env
- Install the
emulate_kvp
andemulate_nvp
packages in the repo root directory usingpip install -e .
(you only need the-e
option if you intend to edit the source code inemulate/
).
The main class for the KVP-based emulator is KVP_emulator
, which implements both the standard Lippmann-Schwinger solver
and the KVP emulator.
The code snippet below shows how it should be used:
from emulate import KVP_emulator
# Setup
V0, V1 = ... # The parameter independent piece, and the linear piece of the potential
ps, ws = ... # The momentum and integration measure in units of inverse fm, corresponding to the potential mesh
E = ... # The lab energy in MeV
# Initialize object. Only handles linear potentials: V = V0 + V1 @ lecs
emu = KVP_emulator(k=k, ps=ps, ws=ws, V0=V0,
V1=V1, wave=wave, is_coupled=False)
# The argument wave controls the partial wave being trained.
# For coupled channels, is_coupled=True.
# Train the emulator
emu.train(train_params=basis, glockle=True, method=emu_method) # basis = (n_b, n_a)
# If glockle=True, the Glockle spline method is used in the calculation.
# If glockle=False, the Standard method is used.
# The method argument controls the boundary conditions used by the emulator.
# Boundary conditions for emulator: 'K', '1/K', 'T', 'all'
# Predict phase shifts at validation parameter values using the simulator and the emulator
emu_pred = emu.prediction(test_params=lecs, glockle=False, sol=solver, h=nugget) # Emulator
sim = emu.high_fidelity(params=lecs) # No emulator
The main class for the NVP-based emulator is NVP_emulator
, which implements both the standard Lippmann-Schwinger solver
and the NVP emulator.
The code snippet below shows how it should be used (with the same setup as above):
from emulate import TwoBodyScattering as NVP_emulator
# Initialize object. Only handles linear potentials: V = V0 + V1 @ p
scatt = NVP_emulator(V0=V0, V1=V1, k=ps, dk=ws,
t_lab=E, system="np")
# Train the emulator
scatt.fit(basis) # basis = (n_b, n_a)
# Predict phase shifts at validation parameter values using the simulator and the emulator
phase_pred_valid = scatt.predict(lecs, return_phase=True) # Emulator
phase_full_valid = scatt.predict(lecs, return_phase=True, full_space=True) # No emulator
# If full_space=True, the simulator is used.
# If full_space=False, the emulator is used.
Please cite this work as follows:
@article{Garcia:2023slj,
author = "Garcia, A. J. and Drischler, C. and Furnstahl, R. J. and Melendez, J. A. and Zhang, Xilin",
title = "{Wave-function-based emulation for nucleon-nucleon scattering in momentum space}",
eprint = "2301.05093",
archivePrefix = "arXiv",
primaryClass = "nucl-th",
doi = "10.1103/PhysRevC.107.054001",
journal = "Phys. Rev. C",
volume = "107",
number = "5",
pages = "054001",
year = "2023"
}