mirror of
https://github.com/vale981/master-thesis
synced 2025-03-05 10:01:43 -05:00
detune further
This commit is contained in:
parent
a0a5ab9195
commit
67eeae32d6
2 changed files with 148 additions and 20 deletions
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@ -20,7 +20,17 @@ import logging
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logging_setup(logging.INFO, show_stocproc=False)
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def anti_zeno_engine(
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Δ=5, γ=0.1 / 2, ω_c=1, ω_0=6, ε=1e-3, ε_couple=1 / 2, n=6, cycle_scale=1, switch_cycles=3, detune = 0
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Δ=5,
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γ=0.1 / 2,
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ω_c=1,
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ω_0=6,
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ε=1e-3,
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ε_couple=1 / 2,
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n=6,
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cycle_scale=1,
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switch_cycles=3,
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detune=0,
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δ=[2]*2
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):
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# τ_bath = 1 / ω_c
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τ_mod = 2 * np.pi / Δ
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@ -65,7 +75,7 @@ def anti_zeno_engine(
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model = QubitModelMutliBath(
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δ=[2, 2],
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ω_c=[ω_c, ω_c],
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ω_s=[ω_0 - Δ - ω_c + detune, ω_0 + Δ - ω_c - detune],
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ω_s=[ω_0 - Δ - ω_c - detune, ω_0 + Δ - ω_c - detune],
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t=ut.linspace_with_strobe(0, t_max, n * 1000, Δ),
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ψ_0=(0 * qt.basis([2], [0]) + qt.basis([2], [1])),
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description=f"Building the anti-zento-engine",
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@ -80,14 +90,15 @@ def anti_zeno_engine(
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therm_methods=["tanhsinh", "fft"],
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)
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return model, (τ_mod, τ_c, τ_bath, cycles, model.ω_s)
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return model, Δ, (τ_mod, τ_c, τ_bath, cycles, model.ω_s)
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model, params = anti_zeno_engine(ε=1/2, ε_couple=1e-10, n=1, detune=.5)
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model, Δ, params = anti_zeno_engine(ε=1/2, ε_couple=1e-10, n=1, detune=5, ω_0 = 10)
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#model, params = anti_zeno_engine(ε=1/2, ε_couple=1e-4, n=1, detune=.5, δ=[.1,.1])
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params
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aux.integrate(model, 1000)
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aux.integrate(model, 100)
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_, ax = fs.plot_energy_overview(model, markersize=1)
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# with aux.get_data(model) as data:
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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': '192.168.5.199', 'raylet_ip_address': '192.168.5.199', 'redis_address': None, 'object_store_address': '/tmp/ray/session_2022-06-13_10-34-07_952574_13972/sockets/plasma_store', 'raylet_socket_name': '/tmp/ray/session_2022-06-13_10-34-07_952574_13972/sockets/raylet', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-06-13_10-34-07_952574_13972', 'metrics_export_port': 53066, 'gcs_address': '192.168.5.199:65472', 'address': '192.168.5.199:65472', 'node_id': '07f03a66362d550884894637c253be83263961b18a3d40ac2cf5eb2c'})
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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': '192.168.5.199', 'raylet_ip_address': '192.168.5.199', 'redis_address': None, 'object_store_address': '/tmp/ray/session_2022-06-13_11-24-26_407050_23528/sockets/plasma_store', 'raylet_socket_name': '/tmp/ray/session_2022-06-13_11-24-26_407050_23528/sockets/raylet', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-06-13_11-24-26_407050_23528', 'metrics_export_port': 50809, 'gcs_address': '192.168.5.199:52030', 'address': '192.168.5.199:52030', 'node_id': '0535cf462e326eb68669025c6e3b1dc9896e726fe3b70941a8c6c6b3'})
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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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@ -37,7 +37,17 @@ Init ray and silence stocproc.
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* Model Definition
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#+begin_src jupyter-python :results none
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def anti_zeno_engine(
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Δ=5, γ=0.1 / 2, ω_c=1, ω_0=6, ε=1e-3, ε_couple=1 / 2, n=6, cycle_scale=1, switch_cycles=3, detune = 0
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Δ=5,
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γ=0.1 / 2,
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ω_c=1,
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ω_0=6,
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ε=1e-3,
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ε_couple=1 / 2,
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n=6,
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cycle_scale=1,
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switch_cycles=3,
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detune=0,
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δ=[2]*2
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):
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# τ_bath = 1 / ω_c
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τ_mod = 2 * np.pi / Δ
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@ -82,7 +92,7 @@ Init ray and silence stocproc.
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model = QubitModelMutliBath(
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δ=[2, 2],
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ω_c=[ω_c, ω_c],
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ω_s=[ω_0 - Δ - ω_c + detune, ω_0 + Δ - ω_c - detune],
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ω_s=[ω_0 - Δ - ω_c - detune, ω_0 + Δ - ω_c - detune],
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t=ut.linspace_with_strobe(0, t_max, n * 1000, Δ),
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ψ_0=(0 * qt.basis([2], [0]) + qt.basis([2], [1])),
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description=f"Building the anti-zento-engine",
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@ -97,18 +107,19 @@ Init ray and silence stocproc.
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therm_methods=["tanhsinh", "fft"],
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)
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return model, (τ_mod, τ_c, τ_bath, cycles, model.ω_s)
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return model, Δ, (τ_mod, τ_c, τ_bath, cycles, model.ω_s)
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#+end_src
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* Model Definition
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#+begin_src jupyter-python
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model, params = anti_zeno_engine(ε=1/2, ε_couple=1e-10, n=1, detune=.5)
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model, Δ, params = anti_zeno_engine(ε=1/2, ε_couple=1e-10, n=1, detune=5, ω_0 = 10)
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#model, params = anti_zeno_engine(ε=1/2, ε_couple=1e-4, n=1, detune=.5, δ=[.1,.1])
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params
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#+end_src
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#+RESULTS:
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| 1.2566370614359172 | 348.08846601774906 | 347.6950495572053 | 277 | (0.5 9.5) |
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| 1.2566370614359172 | 348.08846601774906 | 347.6950495572053 | 277 | (-1 9) |
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Let's test the assumptions of the paper.
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@ -122,34 +133,112 @@ 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)/model.H.max_operator_norm(model.t.max()))
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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 | 0x7f55e11dd400> |
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[[file:./.ob-jupyter/69cb662158ab6d839a8f0254c23d8d29a846be2d.svg]]
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| <matplotlib.lines.Line2D | at | 0x7fb766362700> |
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[[file:./.ob-jupyter/d68cd13212be9df27c475423cb36714795dc5870.svg]]
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:END:
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#+begin_src jupyter-python :tangle nil
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ωs = np.linspace(0, 20, 1000)
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plt.plot(ωs, model.spectral_density(0)(ωs))
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plt.plot(ωs, model.spectral_density(1)(ωs))
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plt.axvline(model.H.operator_norm(0) * 2 + Δ)
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plt.axvline(model.H.operator_norm(0) * 2 - Δ)
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#+end_src
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#+RESULTS:
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:RESULTS:
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| <matplotlib.lines.Line2D | at | 0x7f55e08b3700> |
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[[file:./.ob-jupyter/7c8fbae15d5d9ea0c78371aa8253c2c167834f08.svg]]
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: <matplotlib.lines.Line2D at 0x7fb7666b2070>
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[[file:./.ob-jupyter/72084cacfca9cdc33725619b1585143f92f10b51.svg]]
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:END:
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** TODO Integration
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#+begin_src jupyter-python
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aux.integrate(model, 1000)
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aux.integrate(model, 100)
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#+end_src
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#+RESULTS:
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:RESULTS:
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: [INFO hops.core.integration 22464] Choosing the nonlinear integrator.
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: /home/hiro/src/hops/hops/core/hierarchy_data.py:497: UserWarning: test_file_version FAILED with exception Unable to open file (file is already open for write/SWMR write (may use <h5clear file> to clear file consistency flags))
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: warnings.warn(
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: /home/hiro/src/hops/hops/core/hierarchy_data.py:500: UserWarning: hdf5_name .data/5dcdeeef6e79bd5c4ee636c23a1905053441c9fa49ea5b8f516844fd17e69033/_3/5dcdeeef6e79bd5c4ee636c23a1905053441c9fa49ea5b8f516844fd17e69033_3a50d7c5e5577f16c8ee57fead7fa546_1.h5
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: warnings.warn("hdf5_name {}".format(self.hdf5_name))
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: /home/hiro/src/hops/hops/core/hierarchy_data.py:503: UserWarning: Moving .data/5dcdeeef6e79bd5c4ee636c23a1905053441c9fa49ea5b8f516844fd17e69033/_3/5dcdeeef6e79bd5c4ee636c23a1905053441c9fa49ea5b8f516844fd17e69033_3a50d7c5e5577f16c8ee57fead7fa546_1.h5 to .data/5dcdeeef6e79bd5c4ee636c23a1905053441c9fa49ea5b8f516844fd17e69033/_3/5dcdeeef6e79bd5c4ee636c23a1905053441c9fa49ea5b8f516844fd17e69033_3a50d7c5e5577f16c8ee57fead7fa546_1.h5backup_1655110347.2761068 and starting fresh.
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: warnings.warn(
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# [goto error]
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#+begin_example
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[0;31m---------------------------------------------------------------------------[0m
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[0;31mRaySystemError[0m Traceback (most recent call last)
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Input [0;32mIn [8][0m, in [0;36m<cell line: 1>[0;34m()[0m
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[0;32m----> 1[0m [43maux[49m[38;5;241;43m.[39;49m[43mintegrate[49m[43m([49m[43mmodel[49m[43m,[49m[43m [49m[38;5;241;43m100[39;49m[43m)[49m
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File [0;32m~/src/two_qubit_model/hiro_models/model_auxiliary.py:108[0m, in [0;36mintegrate[0;34m(model, n, data_path, clear_pd)[0m
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[1;32m 98[0m [38;5;66;03m# with model_db(data_path) as db:[39;00m
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[1;32m 99[0m [38;5;66;03m# if hash in db and "data" db[hash][39;00m
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[1;32m 101[0m supervisor [38;5;241m=[39m HOPSSupervisor(
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[1;32m 102[0m model[38;5;241m.[39mhops_config,
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[1;32m 103[0m n,
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[1;32m 104[0m data_path[38;5;241m=[39mdata_path,
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[1;32m 105[0m data_name[38;5;241m=[39m[38;5;28mhash[39m,
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[1;32m 106[0m )
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[0;32m--> 108[0m [43msupervisor[49m[38;5;241;43m.[39;49m[43mintegrate[49m[43m([49m[43mclear_pd[49m[43m)[49m
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[1;32m 110[0m [38;5;28;01mwith[39;00m supervisor[38;5;241m.[39mget_data([38;5;28;01mTrue[39;00m) [38;5;28;01mas[39;00m data:
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[1;32m 111[0m [38;5;28;01mwith[39;00m model_db(data_path) [38;5;28;01mas[39;00m db:
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File [0;32m~/src/hops/hops/core/integration.py:1238[0m, in [0;36mHOPSSupervisor.integrate[0;34m(self, clear_pd)[0m
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[1;32m 1235[0m [38;5;28;01mwith[39;00m [38;5;28mself[39m[38;5;241m.[39mget_data_and_maybe_clear(clear_pd) [38;5;28;01mas[39;00m data:
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[1;32m 1236[0m t [38;5;241m=[39m data[38;5;241m.[39mget_time()
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[0;32m-> 1238[0m num_integrators [38;5;241m=[39m [38;5;28mint[39m([43mray[49m[38;5;241;43m.[39;49m[43mavailable_resources[49m[43m([49m[43m)[49m[38;5;241m.[39mget([38;5;124m"[39m[38;5;124mCPU[39m[38;5;124m"[39m, [38;5;241m0[39m))
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[1;32m 1240[0m [38;5;28;01mif[39;00m num_integrators [38;5;241m==[39m [38;5;241m0[39m:
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[1;32m 1241[0m [38;5;28;01mraise[39;00m [38;5;167;01mRuntimeError[39;00m([38;5;124m"[39m[38;5;124mNo cpu available for integration![39m[38;5;124m"[39m)
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File [0;32m/nix/store/pwhaggpgvxhy410r6vlx448v9lp8n08s-python3-3.9.12-env/lib/python3.9/site-packages/ray/_private/client_mode_hook.py:105[0m, in [0;36mclient_mode_hook.<locals>.wrapper[0;34m(*args, **kwargs)[0m
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[1;32m 103[0m [38;5;28;01mif[39;00m func[38;5;241m.[39m[38;5;18m__name__[39m [38;5;241m!=[39m [38;5;124m"[39m[38;5;124minit[39m[38;5;124m"[39m [38;5;129;01mor[39;00m is_client_mode_enabled_by_default:
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[1;32m 104[0m [38;5;28;01mreturn[39;00m [38;5;28mgetattr[39m(ray, func[38;5;241m.[39m[38;5;18m__name__[39m)([38;5;241m*[39margs, [38;5;241m*[39m[38;5;241m*[39mkwargs)
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[0;32m--> 105[0m [38;5;28;01mreturn[39;00m [43mfunc[49m[43m([49m[38;5;241;43m*[39;49m[43margs[49m[43m,[49m[43m [49m[38;5;241;43m*[39;49m[38;5;241;43m*[39;49m[43mkwargs[49m[43m)[49m
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File [0;32m/nix/store/pwhaggpgvxhy410r6vlx448v9lp8n08s-python3-3.9.12-env/lib/python3.9/site-packages/ray/state.py:912[0m, in [0;36mavailable_resources[0;34m()[0m
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[1;32m 898[0m [38;5;129m@DeveloperAPI[39m
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[1;32m 899[0m [38;5;129m@client_mode_hook[39m(auto_init[38;5;241m=[39m[38;5;28;01mFalse[39;00m)
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[1;32m 900[0m [38;5;28;01mdef[39;00m [38;5;21mavailable_resources[39m():
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[1;32m 901[0m [38;5;124;03m"""Get the current available cluster resources.[39;00m
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[1;32m 902[0m
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[1;32m 903[0m [38;5;124;03m This is different from `cluster_resources` in that this will return idle[39;00m
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[0;32m (...)[0m
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[1;32m 910[0m [38;5;124;03m resource in the cluster.[39;00m
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[1;32m 911[0m [38;5;124;03m """[39;00m
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[0;32m--> 912[0m [38;5;28;01mreturn[39;00m [43mstate[49m[38;5;241;43m.[39;49m[43mavailable_resources[49m[43m([49m[43m)[49m
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File [0;32m/nix/store/pwhaggpgvxhy410r6vlx448v9lp8n08s-python3-3.9.12-env/lib/python3.9/site-packages/ray/state.py:724[0m, in [0;36mGlobalState.available_resources[0;34m(self)[0m
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[1;32m 712[0m [38;5;28;01mdef[39;00m [38;5;21mavailable_resources[39m([38;5;28mself[39m):
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[1;32m 713[0m [38;5;124;03m"""Get the current available cluster resources.[39;00m
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[1;32m 714[0m
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[1;32m 715[0m [38;5;124;03m This is different from `cluster_resources` in that this will return[39;00m
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[0;32m (...)[0m
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[1;32m 722[0m [38;5;124;03m resource in the cluster.[39;00m
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[1;32m 723[0m [38;5;124;03m """[39;00m
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[0;32m--> 724[0m [38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43m_check_connected[49m[43m([49m[43m)[49m
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[1;32m 726[0m available_resources_by_id [38;5;241m=[39m [38;5;28mself[39m[38;5;241m.[39m_available_resources_per_node()
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[1;32m 728[0m [38;5;66;03m# Calculate total available resources.[39;00m
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File [0;32m/nix/store/pwhaggpgvxhy410r6vlx448v9lp8n08s-python3-3.9.12-env/lib/python3.9/site-packages/ray/state.py:48[0m, in [0;36mGlobalState._check_connected[0;34m(self)[0m
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[1;32m 46[0m [38;5;66;03m# _really_init_global_state should have set self.global_state_accessor[39;00m
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[1;32m 47[0m [38;5;28;01mif[39;00m [38;5;28mself[39m[38;5;241m.[39mglobal_state_accessor [38;5;129;01mis[39;00m [38;5;28;01mNone[39;00m:
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[0;32m---> 48[0m [38;5;28;01mraise[39;00m ray[38;5;241m.[39mexceptions[38;5;241m.[39mRaySystemError(
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[1;32m 49[0m [38;5;124m"[39m[38;5;124mRay has not been started yet. You can start Ray with [39m[38;5;124m'[39m[38;5;124mray.init()[39m[38;5;124m'[39m[38;5;124m.[39m[38;5;124m"[39m
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[1;32m 50[0m )
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[0;31mRaySystemError[0m: System error: Ray has not been started yet. You can start Ray with 'ray.init()'.
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#+end_example
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:END:
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#+begin_src jupyter-python
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_, ax = fs.plot_energy_overview(model, markersize=1)
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@ -161,8 +250,36 @@ 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 0x7f55e189ef40>
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[[file:./.ob-jupyter/508e73e3013240ee3be5f6c1f1282dfd9af71d98.svg]]
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# [goto error]
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#+begin_example
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[0;31m---------------------------------------------------------------------------[0m
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[0;31mRuntimeError[0m Traceback (most recent call last)
|
||||
Input [0;32mIn [51][0m, in [0;36m<cell line: 1>[0;34m()[0m
|
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[0;32m----> 1[0m _, ax [38;5;241m=[39m [43mfs[49m[38;5;241;43m.[39;49m[43mplot_energy_overview[49m[43m([49m[43mmodel[49m[43m,[49m[43m [49m[43mmarkersize[49m[38;5;241;43m=[39;49m[38;5;241;43m1[39;49m[43m)[49m
|
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[1;32m 2[0m [38;5;66;03m# with aux.get_data(model) as data:[39;00m
|
||||
[1;32m 3[0m [38;5;66;03m# fs.plot_with_σ(model.t, model.total_energy(data), ax=ax)[39;00m
|
||||
[1;32m 5[0m ax[38;5;241m.[39mlegend()
|
||||
|
||||
File [0;32m~/Documents/Projects/UNI/master/masterarb/python/energy_flow_proper/10_antizeno_engine/figsaver.py:495[0m, in [0;36mplot_energy_overview[0;34m(model, ensemble_args, **kwargs)[0m
|
||||
[1;32m 491[0m ensemble_args [38;5;241m=[39m {}
|
||||
[1;32m 493[0m fig, ax [38;5;241m=[39m plt[38;5;241m.[39msubplots()
|
||||
[0;32m--> 495[0m [38;5;28;01mwith[39;00m [43maux[49m[38;5;241;43m.[39;49m[43mget_data[49m[43m([49m[43mmodel[49m[43m)[49m [38;5;28;01mas[39;00m data:
|
||||
[1;32m 496[0m system_energy [38;5;241m=[39m model[38;5;241m.[39msystem_energy(data, [38;5;241m*[39m[38;5;241m*[39mensemble_args)
|
||||
[1;32m 497[0m bath_energy [38;5;241m=[39m model[38;5;241m.[39mbath_energy(data, [38;5;241m*[39m[38;5;241m*[39mensemble_args)
|
||||
|
||||
File [0;32m~/src/two_qubit_model/hiro_models/model_auxiliary.py:146[0m, in [0;36mget_data[0;34m(model, data_path, read_only, **kwargs)[0m
|
||||
[1;32m 135[0m [38;5;28;01mreturn[39;00m HIData(
|
||||
[1;32m 136[0m path,
|
||||
[1;32m 137[0m hi_key[38;5;241m=[39mmodel[38;5;241m.[39mhops_config,
|
||||
[0;32m (...)[0m
|
||||
[1;32m 142[0m [38;5;241m*[39m[38;5;241m*[39mkwargs,
|
||||
[1;32m 143[0m )
|
||||
[1;32m 145[0m [38;5;28;01melse[39;00m:
|
||||
[0;32m--> 146[0m [38;5;28;01mraise[39;00m [38;5;167;01mRuntimeError[39;00m([38;5;124mf[39m[38;5;124m"[39m[38;5;124mNo data found for model with hash [39m[38;5;124m'[39m[38;5;132;01m{[39;00mhexhash[38;5;132;01m}[39;00m[38;5;124m'[39m[38;5;124m.[39m[38;5;124m"[39m)
|
||||
|
||||
[0;31mRuntimeError[0m: No data found for model with hash '3d9833cf167312158bc916c6bd14d7af84a33e3a83974fa07c121059176438ec'.
|
||||
#+end_example
|
||||
[[file:./.ob-jupyter/644935f5bd4c8d288ddfc65c0c2b7d99c4abe4d1.svg]]
|
||||
:END:
|
||||
|
||||
- **too fast decoupling kills it**
|
||||
|
|
@ -233,7 +350,7 @@ We need the time points where we sample the total energy.
|
|||
#+end_src
|
||||
|
||||
#+RESULTS:
|
||||
[[file:./.ob-jupyter/a5c8087ba2dd5cedc8d7fa99833ee0725d40a9d4.svg]]
|
||||
[[file:./.ob-jupyter/f6f9936f1326d0a6d63fdfb7293f6f354acd5b54.svg]]
|
||||
|
||||
#+begin_src jupyter-python
|
||||
with aux.get_data(model) as data:
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue