8bca0b13f1
- correcting issue in src/SPIN/atom_vec_spin.cpp (inconsistency packing/unpacking hybrid) - rerunning all examples with corrections of former commit
71 lines
2.2 KiB
Python
Executable File
71 lines
2.2 KiB
Python
Executable File
#!/usr/bin/env python3
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import numpy as np , pylab, tkinter
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import math
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import matplotlib.pyplot as plt
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import mpmath as mp
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hbar=0.658212 # Planck's constant (eV.fs/rad)
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J0=0.05 # per-neighbor exchange interaction (eV)
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S1 = np.array([1.0, 0.0, 0.0])
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S2 = np.array([0.0, 1.0, 0.0])
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alpha=0.01 # damping coefficient
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pi=math.pi
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N=30000 # number of timesteps
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dt=0.1 # timestep (fs)
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# Rodrigues rotation formula
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def rotation_matrix(axis, theta):
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"""
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Return the rotation matrix associated with counterclockwise
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rotation about the given axis by theta radians
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"""
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axis = np.asarray(axis)
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a = math.cos(theta / 2.0)
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b, c, d = -axis * math.sin(theta / 2.0)
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aa, bb, cc, dd = a * a, b * b, c * c, d * d
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bc, ad, ac, ab, bd, cd = b * c, a * d, a * c, a * b, b * d, c * d
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return np.array([[aa + bb - cc - dd, 2 * (bc + ad), 2 * (bd - ac)],
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[2 * (bc - ad), aa + cc - bb - dd, 2 * (cd + ab)],
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[2 * (bd + ac), 2 * (cd - ab), aa + dd - bb - cc]])
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# calculating precession field of spin Sr
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def calc_rot_vector(Sr,Sf):
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rot = (J0/hbar)*(Sf-alpha*np.cross(Sf,Sr))/(1.0+alpha**2)
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return rot
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# second-order ST decomposition as implemented in LAMMPS
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for t in range (0,N):
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# advance s1 by dt/4
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wf1 = calc_rot_vector(S1,S2)
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theta=dt*np.linalg.norm(wf1)*0.25
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axis=wf1/np.linalg.norm(wf1)
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S1 = np.dot(rotation_matrix(axis, theta), S1)
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# advance s2 by dt/2
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wf2 = calc_rot_vector(S2,S1)
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theta=dt*np.linalg.norm(wf2)*0.5
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axis=wf2/np.linalg.norm(wf2)
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S2 = np.dot(rotation_matrix(axis, theta), S2)
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# advance s1 by dt/2
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wf1 = calc_rot_vector(S1,S2)
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theta=dt*np.linalg.norm(wf1)*0.5
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axis=wf1/np.linalg.norm(wf1)
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S1 = np.dot(rotation_matrix(axis, theta), S1)
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# advance s2 by dt/2
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wf2 = calc_rot_vector(S2,S1)
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theta=dt*np.linalg.norm(wf2)*0.5
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axis=wf2/np.linalg.norm(wf2)
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S2 = np.dot(rotation_matrix(axis, theta), S2)
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# advance s1 by dt/4
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wf1 = calc_rot_vector(S1,S2)
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theta=dt*np.linalg.norm(wf1)*0.25
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axis=wf1/np.linalg.norm(wf1)
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S1 = np.dot(rotation_matrix(axis, theta), S1)
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# calc. average magnetization
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Sm = (S1+S2)*0.5
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# calc. energy
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en = -J0*(np.dot(S1,S2))
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# print res. in ps for comparison with LAMMPS
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print(t*dt/1000.0,Sm[0],Sm[1],Sm[2],en)
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