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https://github.com/vale981/master-thesis
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better spectral separation
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e49469ae04
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2 changed files with 15 additions and 15 deletions
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@ -82,7 +82,7 @@ def anti_zeno_engine(
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return model, (τ_mod, τ_c, τ_bath, cycles, model.ω_s)
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model, params = anti_zeno_engine()
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model, params = anti_zeno_engine(ω_0=6)
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params
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@ -26,7 +26,7 @@ Init ray and silence stocproc.
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#+end_src
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#+RESULTS:
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: RayContext(dashboard_url='', python_version='3.9.12', ray_version='1.12.1', ray_commit='4863e33856b54ccf8add5cbe75e41558850a1b75', address_info={'node_ip_address': '192.168.100.160', 'raylet_ip_address': '192.168.100.160', 'redis_address': None, 'object_store_address': '/tmp/ray/session_2022-06-11_16-10-06_802932_36816/sockets/plasma_store', 'raylet_socket_name': '/tmp/ray/session_2022-06-11_16-10-06_802932_36816/sockets/raylet', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-06-11_16-10-06_802932_36816', 'metrics_export_port': 62760, 'gcs_address': '192.168.100.160:42264', 'address': '192.168.100.160:42264', 'node_id': 'a5d1451f14fd9269f1c7c703bd2e23cb84a94170d4ad40b3e7861a51'})
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: RayContext(dashboard_url='', python_version='3.9.12', ray_version='1.12.1', ray_commit='4863e33856b54ccf8add5cbe75e41558850a1b75', address_info={'node_ip_address': '192.168.99.108', 'raylet_ip_address': '192.168.99.108', 'redis_address': None, 'object_store_address': '/tmp/ray/session_2022-06-12_10-55-13_766289_1210189/sockets/plasma_store', 'raylet_socket_name': '/tmp/ray/session_2022-06-12_10-55-13_766289_1210189/sockets/raylet', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-06-12_10-55-13_766289_1210189', 'metrics_export_port': 43375, 'gcs_address': '192.168.99.108:58576', 'address': '192.168.99.108:58576', 'node_id': 'b177960ddfd37df792a8dacbd7f82440431287248aef27d90193e9fd'})
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#+begin_src jupyter-python :results none
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from hops.util.logging_setup import logging_setup
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@ -103,12 +103,12 @@ Init ray and silence stocproc.
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* Model Definition
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#+begin_src jupyter-python
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model, params = anti_zeno_engine()
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model, params = anti_zeno_engine(ω_0=6)
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params
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#+end_src
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#+RESULTS:
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| 1.2566370614359172 | 10.053096491487338 | 10.466663926059324 | 8 | (-4 6) |
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| 1.2566370614359172 | 10.053096491487338 | 10.466663926059324 | 8 | (0 10) |
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Let's test the assumptions of the paper.
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@ -122,14 +122,14 @@ Let's test the assumptions of the paper.
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return model.bcf(1)(t) + 2 * (model.thermal_correlations(1)(t).real)
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plt.plot(model.t, np.abs(thermal_bcf(model.t))/np.abs(thermal_bcf(0)))
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plt.plot(model.t, model.L[0].operator_norm(model.t))
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plt.plot(model.t, model.H.operator_norm(model.t) - ω_0/2)
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#plt.plot(model.t, model.H.operator_norm(model.t) - ω_0/2)
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plt.plot(model.t, np.exp(- model.t * np.min(np.array(model.bcf_coefficients()[1][0]).real)))
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#+end_src
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#+RESULTS:
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:RESULTS:
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| <matplotlib.lines.Line2D | at | 0x7f9ab0b195b0> |
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[[file:./.ob-jupyter/495a08e3d1d226b8d6a5c7034c56373089b44e01.svg]]
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| <matplotlib.lines.Line2D | at | 0x7f960b5e0640> |
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[[file:./.ob-jupyter/6627b6e160d82b9c88aede960db16d75efcbe787.svg]]
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:END:
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#+begin_src jupyter-python :tangle nil
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@ -140,8 +140,8 @@ Let's test the assumptions of the paper.
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#+RESULTS:
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:RESULTS:
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| <matplotlib.lines.Line2D | at | 0x7f9ab0f0f670> |
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[[file:./.ob-jupyter/c043366e4686530dd5fa8bcddaaf1bbf6ebab95f.svg]]
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| <matplotlib.lines.Line2D | at | 0x7f960bd896a0> |
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[[file:./.ob-jupyter/a1a3bf487639295688b6e279e56b9037bc41f08b.svg]]
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:END:
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@ -168,8 +168,8 @@ Let's test the assumptions of the paper.
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#+RESULTS:
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:RESULTS:
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: <matplotlib.legend.Legend at 0x7f9ab5735310>
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[[file:./.ob-jupyter/bb63ba7429e684f913a8b26a2a9540083c0e30cc.svg]]
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: <matplotlib.legend.Legend at 0x7f960bc44730>
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[[file:./.ob-jupyter/02f5910868ac6afe3e2039db428ac5cccc10491b.svg]]
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:END:
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- **too fast decoupling kills it**
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@ -200,7 +200,7 @@ Let's test the assumptions of the paper.
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: pts[1:N+1, 1] = dep1slice
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: /nix/store/pwhaggpgvxhy410r6vlx448v9lp8n08s-python3-3.9.12-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5224: ComplexWarning: Casting complex values to real discards the imaginary part
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: pts[N+2:, 1] = dep2slice[::-1]
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[[file:./.ob-jupyter/e44159b8feb819c05aa4a795c9acce3ad23cbe67.svg]]
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[[file:./.ob-jupyter/45ac729e831799ca145ea562480374c5efea6b5f.svg]]
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:END:
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@ -216,8 +216,8 @@ Let's test the assumptions of the paper.
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#+RESULTS:
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:RESULTS:
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| <matplotlib.lines.Line2D | at | 0x7f9ab0ba9670> |
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[[file:./.ob-jupyter/f3809dd8b346998aea1c4fad127f724b865a932f.svg]]
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| <matplotlib.lines.Line2D | at | 0x7f960c09d070> |
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[[file:./.ob-jupyter/9a0d753dbfd4743e0a0abd43d543885985439bd5.svg]]
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:END:
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** TODO Power and Efficiency
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@ -238,7 +238,7 @@ We need the time points where we sample the total energy.
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#+end_src
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#+RESULTS:
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[[file:./.ob-jupyter/c0bf0862cc10cdbbd0915588568b3cb4344efc07.svg]]
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[[file:./.ob-jupyter/d727e5dfb8edb23183c44c78f45d21d3adaf1afd.svg]]
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#+begin_src jupyter-python
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with aux.get_data(model) as data:
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