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64 lines
2.1 KiB
64 lines
2.1 KiB
2 months ago
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# Copyright (c) [2024] []
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#
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# Permission is hereby granted, free of charge, to any person obtaining a copy
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# of this software and associated documentation files (the "Software"), to deal
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# in the Software without restriction, including without limitation the rights
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# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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# copies of the Software, and to permit persons to whom the Software is
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# furnished to do so, subject to the following conditions:
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#
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# The above copyright notice and this permission notice shall be included in all
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# copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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# SOFTWARE.
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2 months ago
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from typing import Final
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2 months ago
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import numpy as np
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# Pauli matrices
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TAU_X: Final[np.array] = np.array([[0, 1], [1, 0]])
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TAU_Y: Final[np.array] = np.array([[0, -1j], [1j, 0]])
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TAU_Z: Final[np.array] = np.array([[1, 0], [0, -1]])
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TAU_0: Final[np.array] = np.array([[1, 0], [0, 1]])
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2 months ago
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# list of accepted input parameters
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2 months ago
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ACCEPTED_INPUTS: Final[list] = [
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2 months ago
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"infile",
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"outfile",
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"scf_xcf_orientation",
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"ref_xcf_orientations",
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"kset",
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"kdirs",
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"ebot",
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"eset",
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"esetp",
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"parallel_solver_for_Gk",
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"padawan_mode",
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]
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2 months ago
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DEFAULT_ARGUMENTS: Final[dict] = dict(
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2 months ago
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infile=None,
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outfile=None,
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scf_xcf_orientation=np.array([0, 0, 1]),
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ref_xcf_orientations=[
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dict(o=np.array([1, 0, 0]), vw=[np.array([0, 1, 0]), np.array([0, 0, 1])]),
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dict(o=np.array([0, 1, 0]), vw=[np.array([1, 0, 0]), np.array([0, 0, 1])]),
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dict(o=np.array([0, 0, 1]), vw=[np.array([1, 0, 0]), np.array([0, 1, 0])]),
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],
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kset=2,
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kdirs="xyz",
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ebot=None,
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eset=42,
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esetp=1000,
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parallel_solver_for_Gk=False,
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padawan_mode=True,
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)
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