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try to see if the decoupling affects the modulation here

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Valentin Boettcher 2022-08-13 19:16:29 +02:00
parent 8b37c2a953
commit 12cb4f15c3
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2 changed files with 19 additions and 19 deletions
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16
python/energy_flow_proper/10_antizeno_engine/10_first_anti_zeno_cc.py
View file

@ -15,7 +15,7 @@ import plot_utils as pu
import ray
ray.shutdown()
ray.init(address="141.30.17.16:6379")
ray.init()
from hops.util.logging_setup import logging_setup
import logging
@ -28,10 +28,10 @@ from anti_zeno_engine import *
params
) = anti_zeno_engine(
Δ=11,
ε=.1,
ε=1,#.1,
ω_c=1,
ε_couple=0.7,
n=10,
ε_couple=1e-5,
n=1,
detune=.5,
ω_0=20,
T_c=1e3,
@ -43,15 +43,15 @@ from anti_zeno_engine import *
ε_init=.00001/2,
terms=7,
dt=0.01,
sp_tol=1e-3,
sp_tol=1e-4,
init_time_steps=10,
)
model.k_max = 3
aux.integrate(model, 1)
params.cycles
aux.integrate(model, 10_000)
plot_az_coupling_diagram(model, params)
plot_az_sd_overview(model, params)
@ -60,4 +60,4 @@ plot_total_power(model, params)
plot_excited_state(model, params)
plot_power_output(model, params)
plot_power_output(model, params, steady_index=5)

22
python/energy_flow_proper/10_antizeno_engine/continously_couple.org
View file

@ -48,8 +48,8 @@ Init ray and silence stocproc.
Δ=11,
ε=1,#.1,
ω_c=1,
ε_couple=0.7,
n=15,
ε_couple=1e-5,
n=1,
detune=.5,
ω_0=20,
T_c=1e3,
@ -59,9 +59,9 @@ Init ray and silence stocproc.
switch_cycles=1,
therm_initial_state=False,
ε_init=.00001/2,
terms=6,
terms=7,
dt=0.01,
sp_tol=1e-3,
sp_tol=1e-4,
init_time_steps=10,
)
model.k_max = 3
@ -76,7 +76,7 @@ Let's test the assumptions of the paper.
#+end_src
#+RESULTS:
: 9
: 304
#+begin_src jupyter-python
aux.integrate(model, 10_000)
@ -89,7 +89,7 @@ Let's test the assumptions of the paper.
#+RESULTS:
:RESULTS:
| <Figure | size | 520x320 | with | 1 | Axes> | <AxesSubplot:xlabel= | $\tau$ | > |
[[file:./.ob-jupyter/a941e4ac84ce34fd566734c1aba25daec397b27d.svg]]
[[file:./.ob-jupyter/3166301f0aa353e82b7d0ad2b3b3e7ae6f693d5a.svg]]
:END:
#+begin_src jupyter-python
@ -110,7 +110,7 @@ Let's test the assumptions of the paper.
#+RESULTS:
:RESULTS:
| <Figure | size | 520x320 | with | 1 | Axes> | <AxesSubplot:> |
[[file:./.ob-jupyter/a3b4954409608a3f24b4cfc3ffd2462e0584aad2.svg]]
[[file:./.ob-jupyter/0e07e17ad91085f92d3554b857cae59a40d26a14.svg]]
:END:
#+begin_src jupyter-python
@ -120,15 +120,15 @@ Let's test the assumptions of the paper.
#+RESULTS:
:RESULTS:
| <Figure | size | 520x320 | with | 1 | Axes> | <AxesSubplot:> |
[[file:./.ob-jupyter/e80d88373632fdca29311847c2cd654fec89c2bf.svg]]
[[file:./.ob-jupyter/f7b752fa9d2a15f6131f8c7f5e7c3669e3074247.svg]]
:END:
#+begin_src jupyter-python
plot_power_output(model, params)
plot_power_output(model, params, steady_index=5)
#+end_src
#+RESULTS:
:RESULTS:
| <Figure | size | 520x320 | with | 1 | Axes> | <AxesSubplot:title= | (center : \(\bar{P}=-0.00044\pm 0.00020\)) | xlabel= | $\tau$ | ylabel= | $\langle{P}\rangle$ | > | EnsembleValue | (((100000 -0.0004421216901391656 0.00020060870097189892))) |
[[file:./.ob-jupyter/5f54c22a0a8a8ef9cef5cb03b167e0152b4504dc.svg]]
| <Figure | size | 520x320 | with | 1 | Axes> | <AxesSubplot:title= | (center : \(\bar{P}=0.0016\pm 0.0006\)) | xlabel= | $\tau$ | ylabel= | $\langle{P}\rangle$ | > | EnsembleValue | (((10000 0.0015680654088805373 0.0006339387301083156))) |
[[file:./.ob-jupyter/934ebe0f97cbd6d5887c70a8de502ae6a1c4db0b.svg]]
:END: