increase weight of off-axis element

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valentin.boettcher@mailbox.tu-dresden.de 2023-07-31 16:50:06 -04:00
parent 8e03fbd401
commit aa3ae06cd8
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3 changed files with 10 additions and 10 deletions

View file

@ -988,7 +988,7 @@ hamiltonian.
#+begin_src jupyter-python :tangle tangle/rot.py
rot_models = []
weights = [.3]
weights = [.5]
for weight in weights:
off_ax = sc.make_model(0, 0)
off_ax.H_bias = ConstantMatrix(weight / 2 * qt.sigmax().full())
@ -1001,17 +1001,17 @@ hamiltonian.
#+begin_src jupyter-python
τs = rot_models[0].t
#plt.plot(τs, np.einsum('tij,ij->t', rot_models[0].H(τs), qt.sigmay().full()).real)
plt.plot(τs, abs(rot_models[0].H(τs)[:, 0, 0]))
plt.plot(τs, abs(rot_models[0].H(τs)[:, 0, 1]))
plt.plot(τs, abs(rot_models[0].H.operator_norm(τs)))
# plt.plot(τs, abs(rot_models[0].H(τs)[:, 0, 0]))
# plt.plot(τs, abs(rot_models[0].H(τs)[:, 0, 1]))
# plt.plot(τs, abs(rot_models[0].H.operator_norm(τs)))
H = rot_models[0].H
plt.plot(τs, list(map(lambda t: get_energy_gap(H(t)), τs)), color="black")
#+end_src
#+RESULTS:
:RESULTS:
| <matplotlib.lines.Line2D | at | 0x7f36244f3340> |
[[file:./.ob-jupyter/e2600fe61c160903c60b7159b388b82b5ce667d0.svg]]
| <matplotlib.lines.Line2D | at | 0x7f36470cdd00> |
[[file:./.ob-jupyter/d5d7c229833877657c2abc95a30a085919c05d40.svg]]
:END:
** Integration

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@ -373,9 +373,9 @@ fs.export_fig(f"energy_change_off_axis", x_scaling=2, y_scaling=0.7)
τs = rot_models[0].t
#plt.plot(τs, np.einsum('tij,ij->t', rot_models[0].H(τs), qt.sigmay().full()).real)
plt.plot(τs, abs(rot_models[0].H(τs)[:, 0, 0]))
plt.plot(τs, abs(rot_models[0].H(τs)[:, 0, 1]))
plt.plot(τs, abs(rot_models[0].H.operator_norm(τs)))
# plt.plot(τs, abs(rot_models[0].H(τs)[:, 0, 0]))
# plt.plot(τs, abs(rot_models[0].H(τs)[:, 0, 1]))
# plt.plot(τs, abs(rot_models[0].H.operator_norm(τs)))
H = rot_models[0].H
plt.plot(τs, list(map(lambda t: get_energy_gap(H(t)), τs)), color="black")

View file

@ -22,7 +22,7 @@ import itertools
from hops.util.dynamic_matrix import ConstantMatrix
rot_models = []
weights = [.3]
weights = [.5]
for weight in weights:
off_ax = sc.make_model(0, 0)
off_ax.H_bias = ConstantMatrix(weight / 2 * qt.sigmax().full())