Completed Activity 7
This commit is contained in:
Sylvain Tricot
parent
fed5ccd667
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f704dae1ba
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@ -878,7 +878,7 @@
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"name": "python",
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"name": "python",
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"nbconvert_exporter": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"pygments_lexer": "ipython3",
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"version": "3.11.3"
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"version": "3.11.13"
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}
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}
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},
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},
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"nbformat": 4,
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"nbformat": 4,
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@ -133,7 +133,7 @@
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"name": "python",
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"name": "python",
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"nbconvert_exporter": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"pygments_lexer": "ipython3",
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"version": "3.11.3"
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"version": "3.11.13"
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}
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}
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},
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},
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"nbformat": 4,
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"nbformat": 4,
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@ -103,7 +103,8 @@
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":::{figure-md} filters-fig\n",
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":::{figure-md} filters-fig\n",
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"<img src=\"filters.jpg\" alt=\"path filtering\" width=\"600px\" align=\"center\">\n",
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"<img src=\"filters.jpg\" alt=\"path filtering\" width=\"600px\" align=\"center\">\n",
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"\n",
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"\n",
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"Some examples of scattering paths with `forward_scattering`, `backward_scattering` and `distance` filters selected. The accepted forward angle is 45°, the accepted backscattering angle is 20° and the threshold distance is $6a_0$ where $a_0$ is the lattice parameter. Note that the yellow path is rejected but if the `off_cone_events` option is set to a value > 1, then it could have been accepted."
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"Some examples of scattering paths with `forward_scattering`, `backward_scattering` and `distance` filters selected. The accepted forward angle is 45°, the accepted backscattering angle is 20° and the threshold distance is $6a_0$ where $a_0$ is the lattice parameter. Note that the yellow path is rejected but if the `off_cone_events` option is set to a value > 1, then it could have been accepted.\n",
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":::"
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]
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]
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},
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},
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{
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{
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@ -113,7 +114,9 @@
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"source": [
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"source": [
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"## Application to a deep plane in a Si(001) sample\n",
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"## Application to a deep plane in a Si(001) sample\n",
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"\n",
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"\n",
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"The following script will compute contribution of all the planes of a Si(001) substrate to get the total photoelectron intensity of a Si(2s) polar scan. \n",
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"The following script will compute the contribution of a Si(2p) atom in the 4{sup}`th` plane of a Si(001) cluster at scattering order 3.\n",
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"\n",
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"Taking into account all scattering paths took 15 minutes to compute.\n",
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"\n",
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"\n",
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"(msd-paper)=\n",
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"(msd-paper)=\n",
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":::{seealso}\n",
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":::{seealso}\n",
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@ -126,14 +129,46 @@
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"\n",
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"\n",
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":::{tab-item} <i class=\"fa-solid fa-circle-question\"></i> Quiz\n",
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":::{tab-item} <i class=\"fa-solid fa-circle-question\"></i> Quiz\n",
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"\n",
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"\n",
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"The script is almost completed, try to define path filtering options and compare results with and without filtering for emitter in plane n° 3 at scattering order 2.\n",
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"The following script is almost completed, try to define path filtering options (no backscattering, accept all paths with forward angles < 40° and reject paths longer than the diameter of the cluster).\n",
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"\n",
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"\n",
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"Compute the contribution of plane n° 7\n",
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"```{literalinclude} Si001.py\n",
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":lineno-match:\n",
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":emphasize-lines: 37-41\n",
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"```\n",
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"\n",
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"1. How long was your calculation ?\n",
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"2. How does it compare to the calculation with **all** scattering paths up to order 3 ?\n",
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"3. What is the proportion of scattering paths of order 3 that were actually taken into account ?\n",
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"\n",
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"\n",
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":::\n",
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":::\n",
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"\n",
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"\n",
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"::::"
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"::::"
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]
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]
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},
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{
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"cell_type": "markdown",
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"id": "19fbd486-b0c1-450c-a00d-79984945aefd",
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"metadata": {},
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"source": [
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"```{toggle}\n",
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"The calculation took few seconds and the result is very close to the calculation with all scattering paths.\n",
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"\n",
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"Only 0.01% of 3{sup}`rd` order paths were actually taken into account\n",
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"\n",
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":::{figure-md} si-fig\n",
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"<img src=\"results.png\" alt=\"Si polar scan\" width=\"600px\" align=\"center\">\n",
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"\n",
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"Si(2p) polar scan (contribution of an emitter in the 4{sup}`th` plane with all 7 114 945 scattering paths taken into account (orange curve), and for only 1525 filtered paths (blue curve).\n",
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"\n",
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":::\n",
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"\n",
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":::{literalinclude} Si001_completed.py\n",
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":lineno-match:\n",
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":emphasize-lines: 37-41\n",
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":::\n",
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"\n",
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"``` "
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]
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}
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}
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],
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],
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"metadata": {
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"metadata": {
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@ -152,7 +187,7 @@
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"name": "python",
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"name": "python",
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"nbconvert_exporter": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"pygments_lexer": "ipython3",
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"version": "3.11.3"
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"version": "3.11.13"
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}
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}
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},
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},
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"nbformat": 4,
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"nbformat": 4,
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@ -1,165 +1,56 @@
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# coding: utf8
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# coding: utf8
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import logging
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import numpy as np
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import numpy as np
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import os
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from ase.build import bulk
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import sys
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from ase.build import bulk, diamond111
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from msspec.calculator import MSSPEC, XRaySource
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from msspec.calculator import MSSPEC, XRaySource
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from msspec.iodata import Data
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from msspec.iodata import Data
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from msspec.utils import hemispherical_cluster, get_atom_index, cut_sphere, cut_plane
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from msspec.utils import hemispherical_cluster, get_atom_index
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logging.basicConfig(level=logging.INFO)
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def create_clusters(nplanes=6, direction='100', a=5.43, c=5.43, radius=30):
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clusters = []
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Si = bulk('Si', a=a, cubic=True)
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# Get scaled positions and cell
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p = Si.get_scaled_positions()
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cell = Si.get_cell()
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# Resize
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covera = c / a
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cell[2,:] *= covera
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p[:,2] *= covera
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Si.set_scaled_positions(p)
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Si.set_cell(cell)
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if direction in ('001', '010', '100'):
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pass
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elif direction in ('111'):
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Si.rotate([1,1,1], [1,1,0], rotate_cell=True)
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Si.rotate([1,1,0], [1,0,0], rotate_cell=True)
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Si.rotate([1,0,0], [0,0,1], rotate_cell=True)
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for iplane in range(nplanes):
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#for iplane in (nplanes-1,):
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logging.info(f'Building cluster #{iplane:d}/{nplanes-1:d}')
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cluster = hemispherical_cluster(Si, #planes=max(iplane+1, 4),
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diameter=70,
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emitter_plane=iplane,
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shape = 'cylindrical',
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)
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cluster = cut_sphere(cluster, radius = radius)
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cluster = cut_plane(cluster, z = -a/4)
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for atom in cluster:
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atom.set('mean_square_vibration', 0.006)
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atom.set('mt_radius', 1.1)
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cluster.absorber = get_atom_index(cluster, 0, 0, 0)
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cluster.info.update(emitter_plane=iplane)
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clusters.append(cluster)
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return clusters
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def compute_polar_scan(cluster, data=None, phi=0, folder='calc', RA_cutoff=2,
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max_ndif=6, level='2p', kinetic_energy=1382.28):
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emitter_plane = cluster.info['emitter_plane']
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calc = MSSPEC(spectroscopy='PED', algorithm='expansion',
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folder=folder)
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calc.muffintin_parameters.interstitial_potential = 0.
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#calc.tmatrix_parameters.exchange_correlation = 'x_alpha_real'
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calc.tmatrix_parameters.exchange_correlation = 'hedin_lundqvist_complex'
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calc.source_parameters.energy = XRaySource.AL_KALPHA
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calc.source_parameters.theta = -54.7
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calc.source_parameters.phi = 90
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calc.spectroscopy_parameters.final_state = 1
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calc.detector_parameters.angular_acceptance = 1.0
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calc.detector_parameters.average_sampling = 'high'
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calc.calculation_parameters.scattering_order = min(max_ndif,
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max(1, emitter_plane))
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#calc.tmatrix_parameters.lmax_mode ='imposed'
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#calc.tmatrix_parameters.lmaxt = 10
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calc.tmatrix_parameters.tl_threshold = 1e-4
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#calc.calculation_parameters.scattering_order = 6
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#calc.calculation_parameters.mean_free_path = 10.
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calc.calculation_parameters.vibrational_damping = 'averaged_tl'
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calc.calculation_parameters.RA_cutoff = RA_cutoff
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my_filters = ('forward_scattering', 'distance_cutoff')
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calc.calculation_parameters.path_filtering = my_filters
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#calc.calculation_parameters.path_filtering = 'forward_scattering'
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calc.calculation_parameters.distance = 30
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calc.calculation_parameters.off_cone_events = 0
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calc.calculation_parameters.RA_cutoff_damping = 1
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[a.set('forward_angle', 40) for a in cluster]
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calc.phagen_parameters.noproto = '.false.'
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calc.set_atoms(cluster)
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data = calc.get_theta_scan(level=level,
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theta=np.arange(-30., 80., 0.5),
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kinetic_energy = kinetic_energy,
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phi=phi, data=data)
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return data
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def sum_planes(data):
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cs = None
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ds = None
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for dset in data:
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theta = dset.theta
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phi = dset.phi
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try:
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cs += dset.cross_section
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ds += dset.direct_signal
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except:
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cs = dset.cross_section.copy()
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ds = dset.direct_signal.copy()
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dset = data.add_dset('Substrate signal')
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dset.add_columns(theta=theta, phi=phi, cross_section=cs,
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direct_signal=ds, chi=(cs-ds)/ds)
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phi_values = np.unique(phi)
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view = dset.add_view('Substrate signal',
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title=r'Si(2p)',
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xlabel=r'$\Theta (\degree$)',
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ylabel='Signal (a.u.)')
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for phi_value in phi_values:
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condition = f'phi == {phi_value:.1f}'
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legend = '$\Phi = $' + f'{phi_value:.1f}' + '$^\circ$'
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view.select('theta', 'cross_section', where=condition, legend=legend)
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view.set_plot_options(autoscale=True)
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# Create the list of clusters
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# Create the cluster
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RA = 2 #int(sys.argv[1])
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a = 5.43
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NDIF = 5 #int(sys.argv[2])
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Si = bulk('Si', a=a, cubic=True)
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RAD = 20. #float(sys.argv[3])
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cluster = hemispherical_cluster(Si,
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PHI = float(sys.argv[1])
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diameter=30, planes=4,
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KE = float(sys.argv[2])
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emitter_plane=3,
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#basename = f'RA{RA:d}_NDIF{NDIF:d}_RAD{RAD:.1f}_PHI{PHI:.1f}'
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shape = 'cylindrical',
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basename = f'PHI{PHI:.1f}_KE{KE:.2f}'
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)
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data = Data(basename)
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for atom in cluster:
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clusters = create_clusters(nplanes=15, radius=RAD)
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atom.set('mean_square_vibration', 0.006)
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atom.set('mt_radius', 1.1)
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cluster.emitter = get_atom_index(cluster, 0, 0, 0)
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if 'view' in sys.argv:
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# Create a calculator and set parameters
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for cluster in clusters:
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calc = MSSPEC(spectroscopy='PED', algorithm='expansion')
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cluster.edit()
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exit(0)
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for cluster in clusters:
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calc.source_parameters.energy = XRaySource.AL_KALPHA
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#for cluster in (clusters[-1],):
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calc.source_parameters.theta = -54.7
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data = compute_polar_scan(cluster, data, phi=PHI,
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calc.source_parameters.phi = 90
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folder='calc_' + basename,
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calc.spectroscopy_parameters.final_state = 1
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RA_cutoff=RA,
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max_ndif=NDIF,
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kinetic_energy=KE
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)
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sum_planes(data)
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calc.calculation_parameters.scattering_order = 3
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data.save('simulation_' + basename + '.hdf5', append=False)
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calc.tmatrix_parameters.tl_threshold = 1e-4
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data.export('simulation_' + basename)
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calc.calculation_parameters.vibrational_damping = 'averaged_tl'
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#data.view()
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calc.calculation_parameters.RA_cutoff = 2
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# Define path filtering options such that you only
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# accept scattering paths with a forward cone <= 40°
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# and whose length are <= cluster diameter
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#
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#
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calc.set_atoms(cluster)
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# Compute and add previous data for comparison
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data = calc.get_theta_scan(level='2p',
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theta=np.arange(-30., 80., 0.5),
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phi=0,
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kinetic_energy=1382.28)
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no_filters = Data.load('path_filtering.hdf5')
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data[0].add_columns(**{'no_filters': no_filters[0].cross_section})
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view = data[0].views[0]
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view.select('theta', 'cross_section', index=0, legend="With path filtering")
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view.select('theta', 'no_filters', legend="Without path filtering")
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data.view()
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@ -0,0 +1,56 @@
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# coding: utf8
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import numpy as np
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from ase.build import bulk
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from msspec.calculator import MSSPEC, XRaySource
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from msspec.iodata import Data
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from msspec.utils import hemispherical_cluster, get_atom_index
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# Create the cluster
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a = 5.43
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Si = bulk('Si', a=a, cubic=True)
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cluster = hemispherical_cluster(Si,
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diameter=30, planes=4,
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emitter_plane=3,
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shape = 'cylindrical',
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)
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for atom in cluster:
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atom.set('mean_square_vibration', 0.006)
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atom.set('mt_radius', 1.1)
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cluster.emitter = get_atom_index(cluster, 0, 0, 0)
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# Create a calculator and set parameters
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calc = MSSPEC(spectroscopy='PED', algorithm='expansion')
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calc.source_parameters.energy = XRaySource.AL_KALPHA
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calc.source_parameters.theta = -54.7
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calc.source_parameters.phi = 90
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calc.spectroscopy_parameters.final_state = 1
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calc.calculation_parameters.scattering_order = 3
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calc.tmatrix_parameters.tl_threshold = 1e-4
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calc.calculation_parameters.vibrational_damping = 'averaged_tl'
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calc.calculation_parameters.RA_cutoff = 2
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my_filters = ('forward_scattering', 'distance_cutoff')
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calc.calculation_parameters.path_filtering = my_filters
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calc.calculation_parameters.distance = 30
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calc.calculation_parameters.off_cone_events = 0
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[a.set('forward_angle', 40) for a in cluster]
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calc.set_atoms(cluster)
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||||||
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# Compute and add previous data for comparison
|
||||||
|
data = calc.get_theta_scan(level='2p',
|
||||||
|
theta=np.arange(-30., 80., 0.5),
|
||||||
|
phi=0,
|
||||||
|
kinetic_energy=1382.28)
|
||||||
|
no_filters = Data.load('path_filtering.hdf5')
|
||||||
|
data[0].add_columns(**{'no_filters': no_filters[0].cross_section})
|
||||||
|
view = data[0].views[0]
|
||||||
|
view.select('theta', 'cross_section', index=0, legend="With path filtering")
|
||||||
|
view.select('theta', 'no_filters', legend="Without path filtering")
|
||||||
|
|
||||||
|
data.view()
|
||||||
|
|
@ -11,6 +11,7 @@ natoms = []
|
||||||
allt = []
|
allt = []
|
||||||
for emitter_plane in planes:
|
for emitter_plane in planes:
|
||||||
cluster = hemispherical_cluster(Si, diameter=40, emitter_plane=emitter_plane, planes=emitter_plane+1)
|
cluster = hemispherical_cluster(Si, diameter=40, emitter_plane=emitter_plane, planes=emitter_plane+1)
|
||||||
|
cluster.edit()
|
||||||
N = len(cluster)
|
N = len(cluster)
|
||||||
npaths = np.sum([(N-1)**i for i in range(emitter_plane + 1)])
|
npaths = np.sum([(N-1)**i for i in range(emitter_plane + 1)])
|
||||||
t = npaths * 1e-6
|
t = npaths * 1e-6
|
||||||
|
|
@ -54,4 +55,4 @@ plt.ylim(1e-6, 1e20)
|
||||||
plt.xlabel("Number of atoms for emitter in plane 1 to 9")
|
plt.xlabel("Number of atoms for emitter in plane 1 to 9")
|
||||||
plt.ylabel("Computation time (s)")
|
plt.ylabel("Computation time (s)")
|
||||||
plt.savefig('my_plot.png', transparent=True)
|
plt.savefig('my_plot.png', transparent=True)
|
||||||
plt.show()
|
plt.show()
|
||||||
|
|
|
||||||
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Reference in New Issue