add baseline decoupling dynamics

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valentin.boettcher@mailbox.tu-dresden.de 2023-07-07 16:13:18 -04:00
parent f71127c010
commit cc5776893e
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69 changed files with 288356 additions and 407532 deletions

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@ -29,7 +29,7 @@
# export PYTHONPATH=/home/hiro/src/stocproc/:$PYTHONPATH
export PYTHONPATH=/home/hiro/src/two_qubit_model/:$PYTHONPATH
# export PYTHONPATH=/home/hiro/src/hops/:$PYTHONPATH
# export PYTHONPATH=/home/hiro/src/hopsflow/:$PYTHONPATH
export PYTHONPATH=/home/hiro/src/hopsflow/:$PYTHONPATH
export LD_LIBRARY_PATH="${(pkgs.lib.makeLibraryPath [pkgs.arb])}"
# '';
});

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@ -114,38 +114,60 @@ coupling-change/cycle time.
#+begin_src jupyter-python
fig, ax = plt.subplots()
for model in models[:22]:
for model in models:
pu.plot_with_σ(models[0].t, model.interaction_power().sum_baths().integrate(model.t), ax=ax)
print(model.power(steady_idx=2).value, model.T[0], model.ω_c[0])
#+end_src
#+RESULTS:
:RESULTS:
: -0.0035256859094574657 0.4 0.5
: -0.003003232549170266 0.45 0.5
: -0.002486223631053281 0.5 0.5
: -0.002031171680593496 0.55 0.5
: -0.0015762813191599482 0.6 0.5
: -0.004799000397073388 0.4 0.75
: -0.0043251633398041734 0.45 0.75
: -0.0038327711397568402 0.5 0.75
: -0.0034164331023658415 0.55 0.75
# [goto error]
#+begin_example
-0.0034551659388595505 0.4 0.5
-0.002904596596987212 0.45 0.5
-0.0023659365036140375 0.5 0.5
-0.0019355134236714987 0.55 0.5
-0.0014524274934447788 0.6 0.5
-0.004793786801168995 0.4 0.75
-0.004345910814395173 0.45 0.75
-0.003837955397297659 0.5 0.75
-0.0033846244411344056 0.55 0.75
-0.0029960642459121102 0.6 0.75
-0.004871336818211319 0.4 1.0
-0.004443564282016794 0.45 1.0
-0.0039839481344293454 0.5 1.0
-0.0035662462002002022 0.55 1.0
-0.0031004548905917647 0.6 1.0
-0.0047150449741200865 0.4 1.25
-0.004223951236090775 0.45 1.25
-0.003871633835637403 0.5 1.25
-0.0034857454518454926 0.55 1.25
-0.003170841523344448 0.6 1.25
-0.004713925136010963 0.4 1.5
-0.004262014237031279 0.45 1.5
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
Cell In[20], line 3
 1 fig, ax = plt.subplots()
 2 for model in models:
----> 3 pu.plot_with_σ(models[0].t, model.interaction_power().sum_baths().integrate(model.t), ax=ax)
 4 print(model.power(steady_idx=2).value, model.T[0], model.ω_c[0])
File ~/src/two_qubit_model/hiro_models/model_base.py:560, in Model.interaction_power(self, data, results_path, **kwargs)
 550 """Calculates interaction power from the hierarchy data
 551 ``data`` or, if not supplied, tries to load the online results from ``results_path``.
 552
 (...)
 556 :returns: See :any:`hopsflow.util.interaction_energy_ensemble`.
 557 """
 559 if data is None:
--> 560 return self.try_get_online_data(
 561  results_path, self.online_interaction_power_name
 562  )
 564 N, kwargs = _get_N_kwargs(kwargs, data)
 566 return hopsflow.hopsflow.interaction_energy_ensemble(
 567 data.valid_sample_iterator(data.stoc_traj), # type: ignore
 568 data.valid_sample_iterator(data.aux_states), # type: ignore
 (...)
 574 **kwargs,
 575 )
File ~/src/two_qubit_model/hiro_models/model_base.py:298, in Model.try_get_online_data(self, path, results_path)
 296 file_path = os.path.join(path, results_path)
 297 if not os.path.exists(file_path):
--> 298 raise RuntimeError(f"No data found under '{file_path}'.")
 300 return hopsflow.util.get_online_values_from_cache(file_path)
RuntimeError: No data found under 'results/interaction_power_1c98408e7172b7ca2a5507aed3dcd2b5a45ba1fded942d635720693e91be50c2.npz'.
#+end_example
[[file:./.ob-jupyter/0717c8898072b9d5d4c6d7ac8e6097ba822e7de8.svg]]
[[file:./.ob-jupyter/3f12e992b6683aa19bdb72118d76e5b70849f69c.svg]]
:END:
#+begin_src jupyter-python
@ -155,7 +177,38 @@ coupling-change/cycle time.
#+end_src
#+RESULTS:
[[file:./.ob-jupyter/64e281864076e8697d6c337f105aeb08bfd9c5e7.svg]]
:RESULTS:
# [goto error]
#+begin_example
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
Cell In[11], line 3
 1 fig, ax = plt.subplots()
 2 for model in models[:22]:
----> 3 pu.plot_with_σ(models[0].t, model.system_energy(), ax=ax)
File ~/src/two_qubit_model/hiro_models/model_base.py:315, in Model.system_energy(self, data, results_path, **kwargs)
 305 """Calculates the system energy from the hierarchy data
 306 ``data`` or, if not supplied, tries to load the online results from ``results_path``.
 307
 (...)
 311 :returns: See :any:`hopsflow.util.ensemble_mean`.
 312 """
 314 if data is None:
--> 315 return self.try_get_online_data(results_path, self.online_system_name)
 317 operator = self.system
 318 return self.system_expectation(data, operator, real=True, **kwargs)
File ~/src/two_qubit_model/hiro_models/model_base.py:298, in Model.try_get_online_data(self, path, results_path)
 296 file_path = os.path.join(path, results_path)
 297 if not os.path.exists(file_path):
--> 298 raise RuntimeError(f"No data found under '{file_path}'.")
 300 return hopsflow.util.get_online_values_from_cache(file_path)
RuntimeError: No data found under 'results/system_1c98408e7172b7ca2a5507aed3dcd2b5a45ba1fded942d635720693e91be50c2.npz'.
#+end_example
[[file:./.ob-jupyter/bd5dd629f6ab7c9804f51e1ce295e899dd88b2c4.svg]]
:END:
#+begin_src jupyter-python
fig, ax = plt.subplots()
@ -181,7 +234,81 @@ coupling-change/cycle time.
#+end_src
#+RESULTS:
[[file:./.ob-jupyter/a6d1361f6b9238fd63a5cce405fdd9209d6f635b.svg]]
:RESULTS:
# [goto error]
#+begin_example
---------------------------------------------------------------------------
EOFError Traceback (most recent call last)
File /nix/store/fai1b55231rnk4jyj0kjicdnqcgdf9ph-python3-3.9.15-env/lib/python3.9/site-packages/numpy/lib/npyio.py:441, in load(file, mmap_mode, allow_pickle, fix_imports, encoding, max_header_size)
 440 try:
--> 441 return pickle.load(fid, **pickle_kwargs)
 442 except Exception as e:
EOFError: Ran out of input
The above exception was the direct cause of the following exception:
UnpicklingError Traceback (most recent call last)
Cell In[21], line 5
 3 for bath, style in enumerate(styles):
 4 for i, T in enumerate(Ts):
----> 5 inters = np.array([abs(model.interaction_energy().for_bath(bath).slice(slice(model.strobe[1][2], -1))).max.value for model in models[i::len(Ts)]])
 6 bcf_scales = np.array([(model.bcf_scales[bath]) for model in models[i::len(Ts)]])
 7 ωs_filter = [model.ω_c[0] for model in models[::len(Ts)]]
Cell In[21], line 5, in <listcomp>(.0)
 3 for bath, style in enumerate(styles):
 4 for i, T in enumerate(Ts):
----> 5 inters = np.array([abs(model.interaction_energy().for_bath(bath).slice(slice(model.strobe[1][2], -1))).max.value for model in models[i::len(Ts)]])
 6 bcf_scales = np.array([(model.bcf_scales[bath]) for model in models[i::len(Ts)]])
 7 ωs_filter = [model.ω_c[0] for model in models[::len(Ts)]]
File ~/src/two_qubit_model/hiro_models/model_base.py:533, in Model.interaction_energy(self, data, results_path, **kwargs)
 523 """Calculates interaction energy from the hierarchy data
 524 ``data`` or, if not supplied, tries to load the online results from ``results_path``.
 525
 (...)
 529 :returns: See :any:`hopsflow.util.interaction_energy_ensemble`.
 530 """
 532 if data is None:
--> 533 return self.try_get_online_data(results_path, self.online_interaction_name)
 535 N, kwargs = _get_N_kwargs(kwargs, data)
 537 return hopsflow.hopsflow.interaction_energy_ensemble(
 538 data.valid_sample_iterator(data.stoc_traj), # type: ignore
 539 data.valid_sample_iterator(data.aux_states), # type: ignore
 (...)
 544 **kwargs,
 545 )
File ~/src/two_qubit_model/hiro_models/model_base.py:300, in Model.try_get_online_data(self, path, results_path)
 297 if not os.path.exists(file_path):
 298 raise RuntimeError(f"No data found under '{file_path}'.")
--> 300 return hopsflow.util.get_online_values_from_cache(file_path)
File ~/src/hopsflow/hopsflow/util.py:902, in get_online_values_from_cache(path)
 899 vals = []
 901 for path in all_versions:
--> 902 agg = WelfordAggregator.from_dump(str(path))
 903 vals.append([agg.n, agg.mean, agg.ensemble_std])
 904 vals.sort(key=lambda el: el[0])
File ~/src/hopsflow/hopsflow/util.py:730, in WelfordAggregator.from_dump(cls, path)
 728 instance = cls(np.empty(1))
 729 with portalocker.Lock(path, "rb", flags=portalocker.LockFlags.EXCLUSIVE) as f:
--> 730 dump_file = np.load(f, allow_pickle=True)
 732 instance.n = int(dump_file["n"])
 733 instance.mean = dump_file["mean"]
File /nix/store/fai1b55231rnk4jyj0kjicdnqcgdf9ph-python3-3.9.15-env/lib/python3.9/site-packages/numpy/lib/npyio.py:443, in load(file, mmap_mode, allow_pickle, fix_imports, encoding, max_header_size)
 441 return pickle.load(fid, **pickle_kwargs)
 442 except Exception as e:
--> 443 raise pickle.UnpicklingError(
 444 f"Failed to interpret file {file!r} as a pickle") from e
UnpicklingError: Failed to interpret file <_io.BufferedReader name='results/interaction_5343573c062907a778a707b8bb68db373c0082ab4606d528534812fdb0f94786_60000.npz'> as a pickle
#+end_example
[[file:./.ob-jupyter/fdd2225c78b3d368377fec25eab6bfb3e5699f7e.svg]]
:END:
#+begin_src jupyter-python
fig, ax = plt.subplots()
@ -225,7 +352,7 @@ coupling-change/cycle time.
0.55 [[0.55, 4], [0.55, 4], [0.55, 4], [0.55, 4], [0.55, 4]] 1 *
0.6 [[0.6, 4], [0.6, 4], [0.6, 4], [0.6, 4], [0.6, 4]] 1 *
#+end_example
[[file:./.ob-jupyter/d802e193d6695eb382972e8a3652a157a854a569.svg]]
[[file:./.ob-jupyter/828b5a24bad8964f79a87618f48012aa3d81c549.svg]]
:END:
@ -238,10 +365,7 @@ coupling-change/cycle time.
#+end_src
#+RESULTS:
[[file:./.ob-jupyter/b69b1130c17be6de63bc0ed992a34fbea26daa18.svg]]
[[file:./.ob-jupyter/b9024c9d49fcea3025a1a688e979b6854d435e3a.svg]]
[[file:./.ob-jupyter/112a8c6e447f4211f90e5db647df83a97bdfb292.svg]]
#+begin_src jupyter-python
@ -266,7 +390,7 @@ coupling-change/cycle time.
#+end_src
#+RESULTS:
[[file:./.ob-jupyter/253ca412ce97ab193b8e0d63b443a255138f8944.svg]]
[[file:./.ob-jupyter/582e63e77847cd7744d08b50f6b3a44972a66156.svg]]
#+begin_src jupyter-python
def thermal_state(T, Ω):
@ -320,17 +444,17 @@ coupling-change/cycle time.
#+RESULTS:
:RESULTS:
: /nix/store/y48ylcnfb6lb7447lrmmddfsqcna3a9q-python3-3.9.15-env/lib/python3.9/site-packages/matplotlib/cbook/__init__.py:1369: ComplexWarning: Casting complex values to real discards the imaginary part
: /nix/store/32immcyww09pavyq3x5gdn14r3rfy8nl-python3-3.9.15-env/lib/python3.9/site-packages/matplotlib/cbook/__init__.py:1369: ComplexWarning: Casting complex values to real discards the imaginary part
: return np.asarray(x, float)
: /nix/store/y48ylcnfb6lb7447lrmmddfsqcna3a9q-python3-3.9.15-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5340: ComplexWarning: Casting complex values to real discards the imaginary part
: /nix/store/32immcyww09pavyq3x5gdn14r3rfy8nl-python3-3.9.15-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5340: ComplexWarning: Casting complex values to real discards the imaginary part
: pts[0] = start
: /nix/store/y48ylcnfb6lb7447lrmmddfsqcna3a9q-python3-3.9.15-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5341: ComplexWarning: Casting complex values to real discards the imaginary part
: /nix/store/32immcyww09pavyq3x5gdn14r3rfy8nl-python3-3.9.15-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5341: ComplexWarning: Casting complex values to real discards the imaginary part
: pts[N + 1] = end
: /nix/store/y48ylcnfb6lb7447lrmmddfsqcna3a9q-python3-3.9.15-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5344: ComplexWarning: Casting complex values to real discards the imaginary part
: /nix/store/32immcyww09pavyq3x5gdn14r3rfy8nl-python3-3.9.15-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5344: ComplexWarning: Casting complex values to real discards the imaginary part
: pts[1:N+1, 1] = dep1slice
: /nix/store/y48ylcnfb6lb7447lrmmddfsqcna3a9q-python3-3.9.15-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5346: ComplexWarning: Casting complex values to real discards the imaginary part
: /nix/store/32immcyww09pavyq3x5gdn14r3rfy8nl-python3-3.9.15-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5346: ComplexWarning: Casting complex values to real discards the imaginary part
: pts[N+2:, 1] = dep2slice[::-1]
[[file:./.ob-jupyter/02fe89bca1c7946a8228dce3381435aa45921b6a.svg]]
[[file:./.ob-jupyter/87ee9582d91c2e1b413352d63ce90bec9395a473.svg]]
:END:
@ -386,7 +510,7 @@ coupling-change/cycle time.
#+end_src
#+RESULTS:
[[file:./.ob-jupyter/5229f244f0a611e72d9445d2a9bc66bcb279c11a.svg]]
[[file:./.ob-jupyter/b9ca63a22b07896f059e501f293122a207f60016.svg]]
#+begin_src jupyter-python
@ -396,7 +520,7 @@ coupling-change/cycle time.
#+RESULTS:
:RESULTS:
| <Figure | size | 340x320 | with | 2 | Axes> | <AxesSubplot: | xlabel= | $\omega_c$ | ylabel= | $\bar{P}$ | > | (<AxesSubplot: xlabel= $\omega_c$ ylabel= $\bar{P}$ > <AxesSubplot: ylabel= $\eta$ >) |
[[file:./.ob-jupyter/cb7d0dc9bc64c874514e72287385326a2f710625.svg]]
[[file:./.ob-jupyter/69b499338780926af7bb8c3936bf6c23a27c7d9e.svg]]
:END:
@ -408,7 +532,7 @@ coupling-change/cycle time.
#+RESULTS:
:RESULTS:
| <Figure | size | 340x320 | with | 2 | Axes> | (<AxesSubplot: xlabel= $N$ ylabel= $P$ > <AxesSubplot: xlabel= $N$ ylabel= $\eta$ >) |
[[file:./.ob-jupyter/6384006b2616a827ceb6cd032b029cbccf0773f3.svg]]
[[file:./.ob-jupyter/8146b7071cda2606563186cddc75c7551a4508b8.svg]]
:END:
@ -447,49 +571,173 @@ coupling-change/cycle time.
#+end_src
#+RESULTS:
:RESULTS:
[[file:./.ob-jupyter/22b8e23a40d90760837338c77db60ceb8f46b39e.svg]]
: (pid=gcs_server) [2023-05-18 16:55:57,199 E 126618 126618] (gcs_server) gcs_server.cc:283: Failed to get the resource load: GrpcUnavailable: RPC Error message: Connection reset by peer; RPC Error details:
: (pid=gcs_server) [2023-05-18 16:55:57,199 E 126618 126618] (gcs_server) gcs_server.cc:283: Failed to get the resource load: GrpcUnavailable: RPC Error message: Connection reset by peer; RPC Error details:
: (pid=gcs_server) [2023-05-18 16:55:57,199 E 126618 126618] (gcs_server) gcs_server.cc:283: Failed to get the resource load: GrpcUnavailable: RPC Error message: Connection reset by peer; RPC Error details:
: (pid=gcs_server) [2023-05-18 16:55:57,199 E 126618 126618] (gcs_server) gcs_server.cc:283: Failed to get the resource load: GrpcUnavailable: RPC Error message: Connection reset by peer; RPC Error details:
: (pid=gcs_server) [2023-05-18 16:55:57,200 E 126618 126618] (gcs_server) gcs_server.cc:283: Failed to get the resource load: GrpcUnavailable: RPC Error message: Connection reset by peer; RPC Error details:
:END:
[[file:./.ob-jupyter/28cfefab23d9ed0190a04f826614e6220cd36555.svg]]
#+begin_src jupyter-python
for model in models:
ot.plot_bloch_components(model)
#+end_src
#+RESULTS:
:RESULTS:
: /home/hiro/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/subprojects/bath_memory/plot_utils.py:38: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`). Consider using `matplotlib.pyplot.close()`.
: fig, ax = setup_function()
[[file:./.ob-jupyter/ca6f8c77e0d1c2c4c0588a27f1d5a73f06959b28.svg]]
[[file:./.ob-jupyter/9f04f59f958f8cd05e7fcfae012822448e28a0fa.svg]]
[[file:./.ob-jupyter/7e64dd5c305b62d7e61c8d54061ba0d5c0bd9c71.svg]]
[[file:./.ob-jupyter/a1049ebdd7cfc3033bda8fa6d8db69c76b10c5d4.svg]]
[[file:./.ob-jupyter/6f7c25ffff1125b68ed93c42984b3fbdbc623e4f.svg]]
[[file:./.ob-jupyter/bd8ed043725eac4e7087ce04a8f79cb6dd550bea.svg]]
[[file:./.ob-jupyter/b9f416d4b1330798fc77fc4e38c6ec544c84a2ad.svg]]
[[file:./.ob-jupyter/b7f019626c425b7fd2e28f1d70953cd433a26848.svg]]
[[file:./.ob-jupyter/fdde454c6d1a1e31736ab2f26b35c64424e217f3.svg]]
[[file:./.ob-jupyter/e0af7e1701860e27f7e3fe45f05b8c7c7bf21925.svg]]
[[file:./.ob-jupyter/af151eefe6085deb9679052c683cd68c4d511ade.svg]]
[[file:./.ob-jupyter/28b0b7edde79a9c047b455633716a30c742dcd8f.svg]]
[[file:./.ob-jupyter/471db72082118a478b1ca5e58ac27511fdb93ad5.svg]]
[[file:./.ob-jupyter/66c1ff99f83e6c30af2feb9341d02522d77dde69.svg]]
[[file:./.ob-jupyter/623e14113817b5d8f1074943abccdb7caa0c0bb0.svg]]
[[file:./.ob-jupyter/675689df6d994ce4b35bb864a382f9d7d285b248.svg]]
[[file:./.ob-jupyter/1ac491c0d095e16d95afe9602af94955acde385f.svg]]
[[file:./.ob-jupyter/41bcaaaa18868654a7a90a5f911a994028d3d3e8.svg]]
[[file:./.ob-jupyter/0bc90e1a20c538d634aa21afed202d1c2648222a.svg]]
[[file:./.ob-jupyter/b4790ef001a8c49fdf9a178196428c3ccdb95d25.svg]]
[[file:./.ob-jupyter/70822f7bcdb6cffa813ca2c828a59e6b3307d4ef.svg]]
[[file:./.ob-jupyter/7bcf53ab551180350c7516d1cd29b3c0608229b7.svg]]
[[file:./.ob-jupyter/6375902d049d7c66e42fc1ef593ce9a109b5992c.svg]]
[[file:./.ob-jupyter/9911ddfe7318ac880f7254510fc9dd449cf1a11d.svg]]
[[file:./.ob-jupyter/2b14a9fdd7d143dbeeba0b108a2df8c49e853c01.svg]]
# [goto error]
#+begin_example
---------------------------------------------------------------------------
OSError Traceback (most recent call last)
File ~/src/two_qubit_model/hiro_models/model_auxiliary.py:221, in get_data(model, data_path, read_only, **kwargs)
 220 try:
--> 221 return HIData(path, read_only=read_only, robust=False, **kwargs)
 222 except:
File /nix/store/32immcyww09pavyq3x5gdn14r3rfy8nl-python3-3.9.15-env/lib/python3.9/site-packages/hops/core/hierarchy_data.py:255, in HIData.__init__(self, hdf5_name, read_only, hi_key, hi_key_bin, hi_key_bin_hash, check_consistency, overwrite_key, robust, stream_file)
 254 if not hi_key:
--> 255 with h5py.File(hdf5_name, "r", libver="latest") as h5File:
 256 try:
File /nix/store/32immcyww09pavyq3x5gdn14r3rfy8nl-python3-3.9.15-env/lib/python3.9/site-packages/h5py/_hl/files.py:533, in File.__init__(self, name, mode, driver, libver, userblock_size, swmr, rdcc_nslots, rdcc_nbytes, rdcc_w0, track_order, fs_strategy, fs_persist, fs_threshold, fs_page_size, page_buf_size, min_meta_keep, min_raw_keep, locking, alignment_threshold, alignment_interval, **kwds)
 530 fcpl = make_fcpl(track_order=track_order, fs_strategy=fs_strategy,
 531 fs_persist=fs_persist, fs_threshold=fs_threshold,
 532 fs_page_size=fs_page_size)
--> 533 fid = make_fid(name, mode, userblock_size, fapl, fcpl, swmr=swmr)
 535 if isinstance(libver, tuple):
File /nix/store/32immcyww09pavyq3x5gdn14r3rfy8nl-python3-3.9.15-env/lib/python3.9/site-packages/h5py/_hl/files.py:226, in make_fid(name, mode, userblock_size, fapl, fcpl, swmr)
 225 flags |= h5f.ACC_SWMR_READ
--> 226 fid = h5f.open(name, flags, fapl=fapl)
 227 elif mode == 'r+':
File h5py/_objects.pyx:54, in h5py._objects.with_phil.wrapper()
File h5py/_objects.pyx:55, in h5py._objects.with_phil.wrapper()
File h5py/h5f.pyx:106, in h5py.h5f.open()
OSError: Unable to open file (file is already open for write (may use <h5clear file> to clear file consistency flags))
During handling of the above exception, another exception occurred:
OSError Traceback (most recent call last)
Cell In[33], line 2
 1 for model in models:
----> 2 ot.plot_bloch_components(model)
File ~/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/subprojects/bath_memory/plot_utils.py:40, in wrap_plot.<locals>.wrapped(ax, setup_function, *args, **kwargs)
 37 if not ax:
 38 fig, ax = setup_function()
---> 40 ret_val = f(*args, ax=ax, **kwargs)
 41 return (fig, ax, ret_val) if ret_val else (fig, ax)
File ~/Documents/Projects/UNI/master/eflow_paper/python/otto_motor/subprojects/bath_memory/otto_utilities.py:553, in plot_bloch_components(model, ax, **kwargs)
 551 @pu.wrap_plot
 552 def plot_bloch_components(model, ax=None, **kwargs):
--> 553 with aux.get_data(model) as data:
 554 ρ = data.rho_t_accum.mean[:]
 555 σ_ρ = data.rho_t_accum.ensemble_std[:]
File ~/src/two_qubit_model/hiro_models/model_auxiliary.py:223, in get_data(model, data_path, read_only, **kwargs)
 221 return HIData(path, read_only=read_only, robust=False, **kwargs)
 222 except:
--> 223 return HIData(
 224  path,
 225  hi_key=model.hops_config,
 226  read_only=False,
 227  check_consistency=False,
 228  overwrite_key=True,
 229  robust=False,
 230  **kwargs,
 231  )
 233 else:
 234 raise RuntimeError(f"No data found for model with hash '{hexhash}'.")
File /nix/store/32immcyww09pavyq3x5gdn14r3rfy8nl-python3-3.9.15-env/lib/python3.9/site-packages/hops/core/hierarchy_data.py:416, in HIData.__init__(self, hdf5_name, read_only, hi_key, hi_key_bin, hi_key_bin_hash, check_consistency, overwrite_key, robust, stream_file)
 404 """The time points on which the trajectories and everything else are
 405 given.
 406
 (...)
 412 :any:`time_set`.
 413 """
 415 self._init_bcf_terms_and_aux_states()
--> 416 self._open_file(read_only, hi_key_bin, hi_key_bin_hash, overwrite_key, robust)
 418 if check_consistency:
 419 self._check_consistency(hi_key_bin, hi_key_bin_hash)
File /nix/store/32immcyww09pavyq3x5gdn14r3rfy8nl-python3-3.9.15-env/lib/python3.9/site-packages/hops/core/hierarchy_data.py:552, in HIData._open_file(self, read_only, hi_key_bin, hi_key_bin_hash, overwrite_key, backup_if_error)
 550 if not read_only:
 551 try:
--> 552 p = test_file_version(self.hdf5_name)
 553 if p:
 554 warnings.warn(
 555 "can not check version! process list {} has access to hdf5 file {}".format(
 556 p, self.hdf5_name
 557 )
 558 )
File /nix/store/32immcyww09pavyq3x5gdn14r3rfy8nl-python3-3.9.15-env/lib/python3.9/site-packages/hops/core/hierarchy_data.py:1543, in test_file_version(hdf5_name)
 1538 if len(p) > 0:
 1539 # another process accesses the file, assume that the file has allready the new format,
 1540 # since that other process has already changed it
 1541 return p
-> 1543 with h5py.File(hdf5_name, "r+", libver="latest") as h5File:
 1544 # print("test file, open", hdf5_name, "'r+")
 1545 try:
 1546 # print("test file, try to set swmr_mode True")
 1547 h5File.swmr_mode = True
File /nix/store/32immcyww09pavyq3x5gdn14r3rfy8nl-python3-3.9.15-env/lib/python3.9/site-packages/h5py/_hl/files.py:533, in File.__init__(self, name, mode, driver, libver, userblock_size, swmr, rdcc_nslots, rdcc_nbytes, rdcc_w0, track_order, fs_strategy, fs_persist, fs_threshold, fs_page_size, page_buf_size, min_meta_keep, min_raw_keep, locking, alignment_threshold, alignment_interval, **kwds)
 525 fapl = make_fapl(driver, libver, rdcc_nslots, rdcc_nbytes, rdcc_w0,
 526 locking, page_buf_size, min_meta_keep, min_raw_keep,
 527 alignment_threshold=alignment_threshold,
 528 alignment_interval=alignment_interval,
 529 **kwds)
 530 fcpl = make_fcpl(track_order=track_order, fs_strategy=fs_strategy,
 531 fs_persist=fs_persist, fs_threshold=fs_threshold,
 532 fs_page_size=fs_page_size)
--> 533 fid = make_fid(name, mode, userblock_size, fapl, fcpl, swmr=swmr)
 535 if isinstance(libver, tuple):
 536 self._libver = libver
File /nix/store/32immcyww09pavyq3x5gdn14r3rfy8nl-python3-3.9.15-env/lib/python3.9/site-packages/h5py/_hl/files.py:228, in make_fid(name, mode, userblock_size, fapl, fcpl, swmr)
 226 fid = h5f.open(name, flags, fapl=fapl)
 227 elif mode == 'r+':
--> 228 fid = h5f.open(name, h5f.ACC_RDWR, fapl=fapl)
 229 elif mode in ['w-', 'x']:
 230 fid = h5f.create(name, h5f.ACC_EXCL, fapl=fapl, fcpl=fcpl)
File h5py/_objects.pyx:54, in h5py._objects.with_phil.wrapper()
File h5py/_objects.pyx:55, in h5py._objects.with_phil.wrapper()
File h5py/h5f.pyx:106, in h5py.h5f.open()
OSError: Unable to open file (file is already open for write/SWMR write (may use <h5clear file> to clear file consistency flags))
#+end_example
[[file:./.ob-jupyter/391839204016c027928dce723e2f60989df24238.svg]]
[[file:./.ob-jupyter/9cabaf41cf638bbfa616935e4dbca0b60bcfd3cd.svg]]
[[file:./.ob-jupyter/397d515cf3f849f2c51109ec484f8cecce7fddae.svg]]
[[file:./.ob-jupyter/f387eaadc3e789d6657cc553054130a90f9d954d.svg]]
[[file:./.ob-jupyter/5a16efe74b0164bb08689d0240fac7670b841b3b.svg]]
[[file:./.ob-jupyter/4150efcade266857daeff2a083dbacb5890d4f0b.svg]]
[[file:./.ob-jupyter/ef888b06352df909cb330d223bc51c7a2ce4b964.svg]]
[[file:./.ob-jupyter/840187a1542d72f699a7eb68d2a13067ab633e64.svg]]
[[file:./.ob-jupyter/aecd112aabeff70627d43b3808a17a0d5ffcd53a.svg]]
[[file:./.ob-jupyter/151a897d81d62634709dba7ef6b2ea0860cf7061.svg]]
[[file:./.ob-jupyter/3cb4a449492bba16272b7701c096f694fe025415.svg]]
[[file:./.ob-jupyter/48a2d5d58391caa1218752b06fca5c80fad369c1.svg]]
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[[file:./.ob-jupyter/b9d0c73884c96e71bb4d517ade6d0ff1641e6936.svg]]
[[file:./.ob-jupyter/d56c099c7f74f44c3067a8da8efcef6ec451eba2.svg]]
[[file:./.ob-jupyter/c55409a2e0a9df91920de0513761c0410b31887a.svg]]
[[file:./.ob-jupyter/157f23707f76f0d13ed9bf18c950c4c744a6e165.svg]]
[[file:./.ob-jupyter/ef56e6d0cc0f6b2ad02ed7d9ec09787d1a9fc2ab.svg]]
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[[file:./.ob-jupyter/0df7cfe50115ce562288e0ee5ac51256a864dbe6.svg]]
:END:
* Things to Look At

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@ -0,0 +1,599 @@
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<dc:creator>
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@ -133,7 +133,7 @@ fs.export_fig("shift_power", y_scaling=0.7)
f, a = plt.subplots()
a.axhline(best_shift_model.system_energy().value[np.argmin(abs(best_shift_model.t - model.Θ * 2))], color="gray", linestyle="--")
r = pu.plot_with_σ(
best_shift_model.t, best_shift_model.interaction_energy().for_bath(0), ax=a,
best_shift_model.t, best_shift_model.interaction_energy().sum_baths(), ax=a,
label=r"$\langle H_\mathrm{inter}\rangle$"
)
pu.plot_with_σ(
@ -146,23 +146,60 @@ a.plot(
label="cold bath modulation",
)
# a.plot(
# best_shift_model.t,
# best_shift_model.coupling_operators[1].operator_norm(best_shift_model.t) / 5,
# label="hot bath modulation",
# )
a.plot(
best_shift_model.t, best_shift_model.system.operator_norm(best_shift_model.t) / 5,
label="system modulation"
)
a.plot(
best_shift_model.t,
best_shift_model.coupling_operators[1].operator_norm(best_shift_model.t) / 5,
label="hot bath modulation",
)
# a.plot(best_shift_model.t, best_shift_model.coupling_operators[1].operator_norm(best_shift_model.t) / 5)
a.set_xlim((model.Θ * 2, model.Θ * 2 + 11))
a.set_xlim((model.Θ * 2, model.Θ * 2 + 20))
a.set_ylim((-.21, .45))
a.set_xlabel(r"$\tau$")
a.legend(loc="upper right", fontsize="x-small")
fs.export_fig("cold_bath_decoupling", y_scaling=.6)
f, a = plt.subplots()
a.axhline(baseline.system_energy().value[np.argmin(abs(baseline.t - model.Θ * 2))], color="gray", linestyle="--")
r = pu.plot_with_σ(
baseline.t, baseline.interaction_energy().sum_baths(), ax=a,
label=r"$\langle H_\mathrm{inter}\rangle$"
)
pu.plot_with_σ(
baseline.t, baseline.system_energy(), ax=a, label=r"$\langle H_\mathrm{sys}\rangle$"
)
# a.plot(baseline.t, baseline.H(baseline.t)[:, 0,0])
a.plot(
baseline.t,
baseline.coupling_operators[0].operator_norm(baseline.t) / 5,
label="cold bath modulation",
)
a.plot(
baseline.t, baseline.system.operator_norm(baseline.t) / 5,
label="system modulation"
)
a.plot(
baseline.t,
baseline.coupling_operators[1].operator_norm(baseline.t) / 5,
label="hot bath modulation",
)
# a.plot(baseline.t, baseline.coupling_operators[1].operator_norm(baseline.t) / 5)
a.set_xlim((model.Θ * 2, model.Θ * 2 + 11))
a.set_ylim((-.21, .45))
a.set_xlabel(r"$\tau$")
a.legend(loc="upper right", fontsize="x-small")
#fs.export_fig("cold_bath_decoupling", y_scaling=.6)
fs.export_fig("cold_bath_decoupling_baseline", y_scaling=.6)
for shift, model in zip(shifts, long_models):
print(
shift, best_shift,
@ -338,6 +375,7 @@ fs.export_fig(f"energy_change_off_axis", x_scaling=2, y_scaling=0.7)
#plt.plot(τs, np.einsum('tij,ij->t', rot_models[0].H(τs), qt.sigmay().full()).real)
plt.plot(τs, abs(rot_models[0].H(τs)[:, 0, 0]))
plt.plot(τs, abs(rot_models[0].H(τs)[:, 0, 1]))
plt.plot(τs, abs(rot_models[0].H.operator_norm(τs)))
aux.import_results(other_data_path="taurus/.data", other_results_path="taurus/results", models_to_import=rot_models)