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let's try a shorter cycle

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Valentin Boettcher 2022-06-15 18:39:11 +02:00
parent 9a9172f37f
commit c0934f815b
2 changed files with 9 additions and 10 deletions
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4
python/energy_flow_proper/10_antizeno_engine/10_first_anti_zeno.py
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@ -100,7 +100,7 @@ def anti_zeno_engine(
return model, Δ, (τ_mod, τ_c, τ_bath, cycles, model.ω_s, ω_0, τ_mod)
model, Δ, (τ_mod, τ_c, τ_bath, cycles, model.ω_s, ω_0, τ_s) = anti_zeno_engine(Δ = 12, ε=1/4, ω_c=1, ε_couple=.9, n=10, detune=-1, ω_0 = 15, T_h=20, δ=[6]*2, γ=.2, therm_initial_state=False)
model, Δ, (τ_mod, τ_c, τ_bath, cycles, model.ω_s, ω_0, τ_s) = anti_zeno_engine(Δ = 12, ε=1/2, ω_c=1, ε_couple=.9, n=10, detune=-1, ω_0 = 15, T_h=20, δ=[6]*2, γ=.2, therm_initial_state=False)
#model, params = anti_zeno_engine(ε=1/2, ε_couple=1e-4, n=1, detune=.5, δ=[.1,.1])
cycles
@ -146,7 +146,7 @@ with aux.get_data(model) as data:
fs.plot_with_σ(model.t, model.bath_energy(data).sum_baths(), ax=ax)
fs.plot_with_σ(model.t, model.total_energy(data), ax=ax)
#fs.plot_with_σ(model.t, model.interaction_energy(data).for_bath(1), ax=ax)
fs.plot_with_σ(model.t, model.interaction_energy(data).for_bath(1), ax=ax)
#fs.plot_with_σ(model.t, model.system_energy(data) + model.bath_energy(data).sum_baths() , ax=ax)

15
python/energy_flow_proper/10_antizeno_engine/anti_zeno_engine.org
View file

@ -123,12 +123,11 @@ Init ray and silence stocproc.
* Model Definition
#+begin_src jupyter-python
model, Δ, (τ_mod, τ_c, τ_bath, cycles, model.ω_s, ω_0, τ_s) = anti_zeno_engine(Δ = 12, ε=1/4, ω_c=1, ε_couple=.9, n=10, detune=-1, ω_0 = 15, T_h=20, δ=[6]*2, γ=.2, therm_initial_state=False)
model, Δ, (τ_mod, τ_c, τ_bath, cycles, model.ω_s, ω_0, τ_s) = anti_zeno_engine(Δ = 12, ε=1/2, ω_c=1, ε_couple=.9, n=10, detune=-1, ω_0 = 15, T_h=20, δ=[6]*2, γ=.2, therm_initial_state=False)
#model, params = anti_zeno_engine(ε=1/2, ε_couple=1e-4, n=1, detune=.5, δ=[.1,.1])
#+end_src
#+RESULTS:
| 1.2566370614359172 | 10.053096491487338 | 10.466663926059324 | 8 | (0 10) |
Let's test the assumptions of the paper.
@ -151,8 +150,8 @@ cycles
#+RESULTS:
:RESULTS:
| <matplotlib.lines.Line2D | at | 0x7f5ccaaa5ca0> |
[[file:./.ob-jupyter/f2a8c926955cb23facc2055f2692955cb4536030.svg]]
| <matplotlib.lines.Line2D | at | 0x7f5cca2bbf10> |
[[file:./.ob-jupyter/d94380f08c8c1f39b93f125cc758a912e9eaf7a6.svg]]
:END:
#+begin_src jupyter-python :tangle nil
@ -168,8 +167,8 @@ cycles
#+RESULTS:
:RESULTS:
| <matplotlib.lines.Line2D | at | 0x7f5ccb104af0> |
[[file:./.ob-jupyter/15ec9b7d21d6fe637ef4477a18dc7fa8542afdda.svg]]
| <matplotlib.lines.Line2D | at | 0x7f5cca40ff10> |
[[file:./.ob-jupyter/b12fa1cc0bdab054fc502c855493e9aee527a09f.svg]]
:END:
#+begin_src jupyter-python :results none
@ -398,14 +397,14 @@ We need the time points where we sample the total energy.
fs.plot_with_σ(model.t, model.bath_energy(data).sum_baths(), ax=ax)
fs.plot_with_σ(model.t, model.total_energy(data), ax=ax)
#fs.plot_with_σ(model.t, model.interaction_energy(data).for_bath(1), ax=ax)
fs.plot_with_σ(model.t, model.interaction_energy(data).for_bath(1), ax=ax)
#fs.plot_with_σ(model.t, model.system_energy(data) + model.bath_energy(data).sum_baths() , ax=ax)
#+end_src
#+RESULTS:
[[file:./.ob-jupyter/dbd6b9ddd10341a7cce60723109edc49f1b52bd4.svg]]
[[file:./.ob-jupyter/4f168f81eec0956194687794c9d7aff1b5d02dfb.svg]]
#+begin_src jupyter-python
with aux.get_data(model) as data: