mirror of
https://github.com/vale981/HOPSFlow-Paper
synced 2025-03-05 09:41:40 -05:00
add basic simulation
This commit is contained in:
parent
fa9757185f
commit
a46289dbfe
5 changed files with 101 additions and 71 deletions
6
python/otto_motor/flake.lock
generated
6
python/otto_motor/flake.lock
generated
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@ -32,11 +32,11 @@
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},
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"nixpkgs": {
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"locked": {
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"lastModified": 1669542132,
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"narHash": "sha256-DRlg++NJAwPh8io3ExBJdNW7Djs3plVI5jgYQ+iXAZQ=",
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"lastModified": 1669791787,
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"narHash": "sha256-KBfoA2fOI5+wCrm7PR+j7jHqXeTkVRPQ0m5fcKchyuU=",
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"owner": "NixOS",
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"repo": "nixpkgs",
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"rev": "a115bb9bd56831941be3776c8a94005867f316a7",
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"rev": "e76c78d20685a043d23f5f9e0ccd2203997f1fb1",
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"type": "github"
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},
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"original": {
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@ -21,7 +21,7 @@
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shellOverride = (pkgs: oldAttrs: {
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shellHook = ''
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export PYTHONPATH=/home/hiro/src/two_qubit_model/:$PYTHONPATH
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#export PYTHONPATH=/home/hiro/src/hops/:$PYTHONPATH
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export PYTHONPATH=/home/hiro/src/hops/:$PYTHONPATH
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export PYTHONPATH=/home/hiro/src/hopsflow/:$PYTHONPATH
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export LD_LIBRARY_PATH="${(pkgs.lib.makeLibraryPath [pkgs.arb])}"
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# '';
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@ -12,96 +12,111 @@
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import utilities as ut
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import stocproc
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import matplotlib.pyplot as plt
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import otto_utilities as ot
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#+end_src
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Init ray and silence stocproc.
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#+begin_src jupyter-python
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import ray
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ray.shutdown()
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#ray.init(address='auto')
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ray.init()
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ray.init(address='auto')
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#ray.init()
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#+end_src
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#+RESULTS:
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: RayContext(dashboard_url='', python_version='3.9.15', ray_version='1.13.0', ray_commit='e4ce38d001dbbe09cd21c497fedd03d692b2be3e', address_info={'node_ip_address': '10.0.0.102', 'raylet_ip_address': '10.0.0.102', 'redis_address': None, 'object_store_address': '/tmp/ray/session_2022-11-30_18-22-21_330665_940019/sockets/plasma_store', 'raylet_socket_name': '/tmp/ray/session_2022-11-30_18-22-21_330665_940019/sockets/raylet', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-11-30_18-22-21_330665_940019', 'metrics_export_port': 56187, 'gcs_address': '10.0.0.102:49774', 'address': '10.0.0.102:49774', 'node_id': '657606fac86410cf9d4a663984fdd108bb4ed71b2bad5450c38f8c7e'})
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: RayContext(dashboard_url='', python_version='3.9.15', ray_version='1.13.0', ray_commit='e4ce38d001dbbe09cd21c497fedd03d692b2be3e', address_info={'node_ip_address': '10.0.0.102', 'raylet_ip_address': '10.0.0.102', 'redis_address': None, 'object_store_address': '/tmp/ray/session_2022-12-01_12-49-01_211839_372329/sockets/plasma_store', 'raylet_socket_name': '/tmp/ray/session_2022-12-01_12-49-01_211839_372329/sockets/raylet', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-12-01_12-49-01_211839_372329', 'metrics_export_port': 51539, 'gcs_address': '10.0.0.102:6379', 'address': '10.0.0.102:6379', 'node_id': 'a0e22c6e0493add2b51aa52eeaf1e90766c796c1f430527c008a3242'})
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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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import logging
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logging_setup(logging.INFO)
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plt.rcParams['figure.figsize'] = (16,8)
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plt.rcParams['figure.figsize'] = (12,4)
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#+end_src
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* Model
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* Model: Baseline
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#+begin_src jupyter-python
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model = OttoEngine(
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δ=[.4, .4],
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δ=[0.4, 0.4],
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ω_c=[1, 1],
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ψ_0=qt.basis([2], [1]),
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description=f"An otto cycle on the way to finding the baseline.",
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description=f"A basic near-markovian, weakly coupled Otto Cycle that actually works.",
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k_max=4,
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bcf_terms=[6]*2,
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bcf_terms=[6] * 2,
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truncation_scheme="simplex",
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driving_process_tolerances=[StocProcTolerances(1e-3, 1e-3)] * 2,
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thermal_process_tolerances=[StocProcTolerances(1e-3, 1e-3)] * 2,
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T = [1, 10],
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driving_process_tolerances=[StocProcTolerances(1e-4, 1e-4)] * 2,
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thermal_process_tolerances=[StocProcTolerances(1e-4, 1e-4)] * 2,
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T=[1, 10],
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therm_methods=["tanhsinh", "fft"],
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Δ=1,
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num_cycles=5,
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Θ=1/.05,
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dt=.001,
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timings_H=(0, .1, .5, .6),
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timings_L=((.6, .7, .9, 1), (.1, .2, .4, .5)),
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Θ=1.5 / 0.05,
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dt=0.001,
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timings_H=(0, 0.1, 0.5, 0.6),
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timings_L=((0.6, 0.7, 0.9, 1), (0.1, 0.2, 0.4, 0.5)),
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streaming_mode=True,
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)
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#+end_src
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#+RESULTS:
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# model = OttoEngine(
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# δ=[0.4, 0.4],
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# ω_c=[1, 1],
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# ψ_0=qt.basis([2], [1]),
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# description=f"An otto cycle on the way to finding the baseline.",
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# k_max=3,
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# bcf_terms=[4] * 2,
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# truncation_scheme="simplex",
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# driving_process_tolerances=[StocProcTolerances(1e-3, 1e-3)] * 2,
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# thermal_process_tolerances=[StocProcTolerances(1e-3, 1e-3)] * 2,
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# T=[1, 10],
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# therm_methods=["tanhsinh", "fft"],
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# Δ=1,
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# num_cycles=4,
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# Θ=1.5 / 0.05,
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# dt=0.001,
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# timings_H=(0, 0.1, 0.3, 0.4),
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# timings_L=((0.4, 0.5, 0.9, 1), (0.1, 0.11, 0.29, 0.3)),
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# streaming_mode=True,
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# )
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#+begin_src jupyter-python
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plt.plot(model.t, model.H.operator_norm(model.t) - 1, label="H")
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plt.plot(model.t, model.coupling_operators[0].operator_norm(model.t) * 2, label="cold")
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plt.plot(model.t, model.coupling_operators[1].operator_norm(model.t) * 2, label="hot")
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plt.legend()
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ot.plot_cycle(model)
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#+end_src
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#+RESULTS:
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:RESULTS:
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: <matplotlib.legend.Legend at 0x7f545fdea250>
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[[file:./.ob-jupyter/eebb82a5e335f4dddadad7a2863b41de48f0faf2.svg]]
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| <Figure | size | 1200x400 | with | 1 | Axes> | <AxesSubplot: | xlabel= | $\tau$ | ylabel= | Operator Norm | > |
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[[file:./.ob-jupyter/16e356aa8afc7a911b3edcfccea6559fe028821c.svg]]
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:END:
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#+begin_src jupyter-python
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ω = np.linspace(.01, 3, 1000)
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plt.plot(ω, model.full_thermal_spectral_density(0)(ω) * model.bcf_scales[0])
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plt.plot(1, model.full_thermal_spectral_density(0)(1) * model.bcf_scales[0], marker="o")
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plt.plot(ω, model.full_thermal_spectral_density(1)(ω) * model.bcf_scales[1])
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plt.plot(2, model.full_thermal_spectral_density(1)(2) * model.bcf_scales[1], marker="o")
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ot.plot_sd_overview(model)
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#+end_src
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#+RESULTS:
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:RESULTS:
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| <matplotlib.lines.Line2D | at | 0x7f545fc8ad30> |
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[[file:./.ob-jupyter/ee3ba754fa0f582037a99ec2f42d470f971fe91d.svg]]
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| <Figure | size | 1200x400 | with | 1 | Axes> | <AxesSubplot: | xlabel= | $\omega$ | ylabel= | Spectral Density | > |
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[[file:./.ob-jupyter/dc9e4dff3bc359892e01587cbcba157708c27487.svg]]
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:END:
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* Integration
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:LOGBOOK:
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CLOCK: [2022-11-30 Wed 16:27]
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:END:
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#+begin_src jupyter-python :tangle nil
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aux.integrate(model, 10_000, stream_file="results.fifo", analyze=True)
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aux.integrate(model, 100, stream_file="results.fifo", analyze=True)
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#+end_src
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#+RESULTS:
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: [INFO hops.core.integration 403378] Choosing the nonlinear integrator.
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: [INFO root 403378] Starting analysis process.
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: [INFO root 403378] Started analysis process with pid 447894.
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: [INFO hops.core.hierarchy_data 403378] Creating the streaming fifo at: /home/hiro/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/results.fifo
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: [INFO hops.core.integration 403378] Using 16 integrators.
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: [INFO hops.core.integration 403378] Some 0 trajectories have to be integrated.
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: [INFO hops.core.integration 403378] Using 1820 hierarchy states.
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: 0it [00:00, ?it/s]
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#+begin_src jupyter-python :tangle nil
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f, a = pu.plot_energy_overview(model, strobe_frequency=model.Ω, hybrid=True, bath_names=["C","H"], online=True)
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a.plot(model.t, model.coupling_operators[0].operator_norm(model.t), linestyle="dashed", label="Mod Cold")
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a.plot(model.t, model.coupling_operators[1].operator_norm(model.t), linestyle="dashed", label="Mod Hot")
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a.plot(model.t, model.H.operator_norm(model.t) - 1, linestyle="dashed", label="Mod H")
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# a.set_xlabel(r"$\tau$")
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# a.plot(model.t, model.coupling_operators[0].operator_norm(model.t), label="cold")
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a.legend()
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@ -109,6 +124,6 @@ CLOCK: [2022-11-30 Wed 16:27]
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#+RESULTS:
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:RESULTS:
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: <matplotlib.legend.Legend at 0x7f545eda5fa0>
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[[file:./.ob-jupyter/24a2a15398d054ad800997d31485ea871537e98c.svg]]
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: <matplotlib.legend.Legend at 0x7fbce8788f40>
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[[file:./.ob-jupyter/c7e0e16b981d66a30d3686f1d753d1319794b083.svg]]
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:END:
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@ -8,45 +8,60 @@ import qutip as qt
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import utilities as ut
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import stocproc
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import matplotlib.pyplot as plt
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import otto_utilities as ot
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import ray
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ray.shutdown()
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#ray.init(address='auto')
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ray.init()
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ray.init(address='auto')
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#ray.init()
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from hops.util.logging_setup import logging_setup
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import logging
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logging_setup(logging.INFO)
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plt.rcParams['figure.figsize'] = (16,8)
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plt.rcParams['figure.figsize'] = (12,4)
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model = OttoEngine(
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δ=[.4, .4],
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δ=[0.4, 0.4],
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ω_c=[1, 1],
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ψ_0=qt.basis([2], [1]),
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description=f"An otto cycle on the way to finding the baseline.",
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description=f"A basic near-markovian, weakly coupled Otto Cycle that actually works.",
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k_max=4,
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bcf_terms=[6]*2,
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bcf_terms=[6] * 2,
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truncation_scheme="simplex",
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driving_process_tolerances=[StocProcTolerances(1e-3, 1e-3)] * 2,
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thermal_process_tolerances=[StocProcTolerances(1e-3, 1e-3)] * 2,
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T = [1, 10],
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driving_process_tolerances=[StocProcTolerances(1e-4, 1e-4)] * 2,
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thermal_process_tolerances=[StocProcTolerances(1e-4, 1e-4)] * 2,
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T=[1, 10],
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therm_methods=["tanhsinh", "fft"],
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Δ=1,
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num_cycles=5,
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Θ=1/.05,
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dt=.001,
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timings_H=(0, .1, .5, .6),
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timings_L=((.6, .7, .9, 1), (.1, .2, .4, .5)),
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Θ=1.5 / 0.05,
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dt=0.001,
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timings_H=(0, 0.1, 0.5, 0.6),
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timings_L=((0.6, 0.7, 0.9, 1), (0.1, 0.2, 0.4, 0.5)),
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streaming_mode=True,
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)
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plt.plot(model.t, model.H.operator_norm(model.t) - 1, label="H")
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plt.plot(model.t, model.coupling_operators[0].operator_norm(model.t) * 2, label="cold")
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plt.plot(model.t, model.coupling_operators[1].operator_norm(model.t) * 2, label="hot")
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plt.legend()
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# model = OttoEngine(
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# δ=[0.4, 0.4],
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# ω_c=[1, 1],
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# ψ_0=qt.basis([2], [1]),
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# description=f"An otto cycle on the way to finding the baseline.",
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# k_max=3,
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# bcf_terms=[4] * 2,
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# truncation_scheme="simplex",
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# driving_process_tolerances=[StocProcTolerances(1e-3, 1e-3)] * 2,
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# thermal_process_tolerances=[StocProcTolerances(1e-3, 1e-3)] * 2,
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# T=[1, 10],
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# therm_methods=["tanhsinh", "fft"],
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# Δ=1,
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# num_cycles=4,
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# Θ=1.5 / 0.05,
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# dt=0.001,
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# timings_H=(0, 0.1, 0.3, 0.4),
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# timings_L=((0.4, 0.5, 0.9, 1), (0.1, 0.11, 0.29, 0.3)),
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# streaming_mode=True,
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# )
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ω = np.linspace(.01, 3, 1000)
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plt.plot(ω, model.full_thermal_spectral_density(0)(ω) * model.bcf_scales[0])
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plt.plot(1, model.full_thermal_spectral_density(0)(1) * model.bcf_scales[0], marker="o")
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plt.plot(ω, model.full_thermal_spectral_density(1)(ω) * model.bcf_scales[1])
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plt.plot(2, model.full_thermal_spectral_density(1)(2) * model.bcf_scales[1], marker="o")
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ot.plot_cycle(model)
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ot.plot_sd_overview(model)
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6
python/otto_motor/poetry.lock
generated
6
python/otto_motor/poetry.lock
generated
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@ -135,7 +135,7 @@ test-tox-coverage = ["coverage (>=5.5)"]
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type = "git"
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url = "https://github.com/beartype/beartype"
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reference = "main"
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resolved_reference = "8f33d55d7673dc7f2e57216ed03e27d9b971f443"
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resolved_reference = "91d1d89c8015ba75a3c990e2ab6b93e9c61f8651"
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[[package]]
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name = "beautifulsoup4"
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@ -508,7 +508,7 @@ qutip = "^4.6.3"
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type = "git"
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url = "git@github.com:vale981/two_qubit_model.git"
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reference = "main"
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resolved_reference = "256ada3d767b93bec1bb340d89c947f966c8cab1"
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resolved_reference = "5d901b0878e738cb03ce17ceee910db240f1607a"
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[[package]]
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name = "hops"
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@ -569,7 +569,7 @@ tqdm = "^4.62.3"
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type = "git"
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url = "https://github.com/vale981/hopsflow"
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reference = "main"
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resolved_reference = "5afd2b6e081591350739b4c483dc0bf356a80b2a"
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resolved_reference = "51a55945cc1953442c8d10852a3793fb0414c853"
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[[package]]
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name = "humanfriendly"
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