hiro/master-thesis
1
0
Fork 0
mirror of https://github.com/vale981/master-thesis synced 2025-03-04 17:41:43 -05:00
Code Issues Projects Releases Packages Wiki Activity Actions

try longtime

Browse source
This commit is contained in:
Valentin Boettcher 2022-06-18 16:30:51 +02:00
parent e8736e7d80
commit ae83a9b4a3
2 changed files with 9 additions and 3 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

1
python/energy_flow_proper/10_antizeno_engine/10_first_anti_zeno.py
View file

@ -232,6 +232,7 @@ with aux.get_data(model) as data:
plt.plot(model.t, mean_norm / mean_norm.max())
plt.yscale("log")
mean_norm.max()
model, _ = anti_zeno_engine(Δ=5, γ=0.1 / 2, ω_c=1, ω_0=2, ε=1e-1, ε_couple=1 / 3, n=6, cycle_scale=1, switch_cycles=3)

11
python/energy_flow_proper/10_antizeno_engine/anti_zeno_engine.org
View file

@ -294,8 +294,8 @@ Let's test the assumptions of the paper.
#+RESULTS:
:RESULTS:
: <matplotlib.legend.Legend at 0x7f132fe19460>
[[file:./.ob-jupyter/ba6c791f1832931e5812afc9a68b21595f3bbba8.svg]]
: <matplotlib.legend.Legend at 0x7f4260457790>
[[file:./.ob-jupyter/6b5cd3972ff3a7b14357d87084276dcb5da496d3.svg]]
:END:
- **too fast decoupling kills it**
@ -377,10 +377,15 @@ We need the time points where we sample the total energy.
plt.plot(model.t, mean_norm / mean_norm.max())
plt.yscale("log")
mean_norm.max()
#+end_src
#+RESULTS:
[[file:./.ob-jupyter/64ac8170bee42810cf16ee89546c935e035b762c.svg]]
:RESULTS:
[[file:./.ob-jupyter/bdb31ef8b89503ed0bbada8f235f6c547e142c3b.svg]]
: 8.916284416712514e-05
[[file:./.ob-jupyter/22379dd36f375ead2a12699f7dab26107e94bb2f.svg]]
:END:
* Too long modulation?, more likely to small spectral sep or to strong coupling
- definitely not too long mod