10: less init

python/energy_flow_proper/10_antizeno_engine/10_first_anti_zeno_cc.py

@@ -31,7 +31,7 @@ from anti_zeno_engine import *
     ε=1,#.1,
     ω_c=1,
     ε_couple=.68,
-    n=40,
+    n=35,
     detune=.5,
     ω_0=20,
     T_c=5e3,
@@ -40,7 +40,7 @@ from anti_zeno_engine import *
     γ=.2,
     switch_cycles=1,
     therm_initial_state=False,
-    ε_init=.000001/2,
+    ε_init=.001/2,
     terms=7,
     dt=0.01/2,
     sp_tol=1e-4,
@@ -66,7 +66,7 @@ plot_az_sd_overview(model, params)
 
 plot_total_power(model, params)
 
-plot_excited_state(model, params)
+plot_excited_state(model, params, with_init=True)
 
 plot_coherences(model, params)
 

python/energy_flow_proper/10_antizeno_engine/anti_zeno_engine.py

@@ -248,12 +248,12 @@ def plot_az_sd_overview(model, params, ax=None):
 
     ax.plot(
         ωs,
-        model.full_thermal_spectral_density(0)(ωs),
+        model.full_thermal_spectral_density(0)(ωs) * model.bcf_scales[0],
         label="Cold Bath",
     )
     ax.plot(
         ωs,
-        model.full_thermal_spectral_density(1)(ωs),
+        model.full_thermal_spectral_density(1)(ωs) * model.bcf_scales[1],
         label="Hot Bath",
     )
     ax.axvline(model.H.operator_norm(0) * 2 + params.Δ)

python/energy_flow_proper/10_antizeno_engine/continously_couple.org

@@ -27,7 +27,7 @@ Init ray and silence stocproc.
 #+end_src
 
 #+RESULTS:
-: RayContext(dashboard_url='', python_version='3.9.13', ray_version='1.13.0', ray_commit='e4ce38d001dbbe09cd21c497fedd03d692b2be3e', address_info={'node_ip_address': '192.168.100.170', 'raylet_ip_address': '192.168.100.170', 'redis_address': None, 'object_store_address': '/tmp/ray/session_2022-08-14_15-01-34_034850_14258/sockets/plasma_store', 'raylet_socket_name': '/tmp/ray/session_2022-08-14_15-01-34_034850_14258/sockets/raylet', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-08-14_15-01-34_034850_14258', 'metrics_export_port': 45019, 'gcs_address': '192.168.100.170:53722', 'address': '192.168.100.170:53722', 'node_id': '2369bf21ce3f134ac9781d678096447e25ad28328ed1d38ad4f5c777'})
+: RayContext(dashboard_url='', python_version='3.9.13', ray_version='1.13.0', ray_commit='e4ce38d001dbbe09cd21c497fedd03d692b2be3e', address_info={'node_ip_address': '141.30.17.225', 'raylet_ip_address': '141.30.17.225', 'redis_address': None, 'object_store_address': '/tmp/ray/session_2022-08-26_09-16-24_372243_434989/sockets/plasma_store', 'raylet_socket_name': '/tmp/ray/session_2022-08-26_09-16-24_372243_434989/sockets/raylet', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-08-26_09-16-24_372243_434989', 'metrics_export_port': 64820, 'gcs_address': '141.30.17.225:62541', 'address': '141.30.17.225:62541', 'node_id': 'b13e6e8fe3cb7e0a8e40b763d39febfe0bac4a37ea2d205950b6dc19'})
 
 #+begin_src jupyter-python :results none
   from hops.util.logging_setup import logging_setup
@@ -49,7 +49,7 @@ Init ray and silence stocproc.
       ε=1,#.1,
       ω_c=1,
       ε_couple=.68,
-      n=40,
+      n=35,
       detune=.5,
       ω_0=20,
       T_c=5e3,
@@ -58,7 +58,7 @@ Init ray and silence stocproc.
       γ=.2,
       switch_cycles=1,
       therm_initial_state=False,
-      ε_init=.000001/2,
+      ε_init=.001/2,
       terms=7,
       dt=0.01/2,
       sp_tol=1e-4,
@@ -79,6 +79,12 @@ Init ray and silence stocproc.
   pu.plot_complex(ts, proc(ts) * model.bcf_scales[1])
 #+end_src
 
+#+RESULTS:
+:RESULTS:
+| <Figure | size | 520x320 | with | 1 | Axes> | <AxesSubplot:> |
+[[file:./.ob-jupyter/458ed32f5b39dff70d717cc2593889573946a962.svg]]
+:END:
+
 
 #+begin_src jupyter-python
   params.cycles
@@ -105,7 +111,7 @@ Init ray and silence stocproc.
 #+RESULTS:
 :RESULTS:
 | <Figure | size | 520x320 | with | 1 | Axes> | <AxesSubplot:xlabel= | $\tau$ | > |
-[[file:./.ob-jupyter/2a8f8502ac9e11101c59c75c15da03cab48dbc86.svg]]
+[[file:./.ob-jupyter/1f7ffd13448c6001e2f81fb22d1fa2c919b497ab.svg]]
 :END:
 
 #+begin_src jupyter-python
@@ -126,53 +132,17 @@ Init ray and silence stocproc.
 #+RESULTS:
 :RESULTS:
 | <Figure | size | 520x320 | with | 1 | Axes> | <AxesSubplot:> |
-[[file:./.ob-jupyter/a2ee618f4377def0d3f99b20f4d3fc914cbb1198.svg]]
+[[file:./.ob-jupyter/ad693ff3d3c543c7fc8bcf66c226d1ee53e1f3b9.svg]]
 :END:
 
 #+begin_src jupyter-python
-  plot_excited_state(model, params)
+  plot_excited_state(model, params, with_init=True)
 #+end_src
 
 #+RESULTS:
 :RESULTS:
-# [goto error]
-#+begin_example
-  ---------------------------------------------------------------------------
-  RuntimeError                              Traceback (most recent call last)
-  Input In [57], in <cell line: 1>()
-  ----> 1 plot_excited_state(model, params)
-
-  File ~/Documents/Projects/UNI/master/masterarb/python/energy_flow_proper/10_antizeno_engine/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/masterarb/python/energy_flow_proper/10_antizeno_engine/anti_zeno_engine.py:285, in plot_excited_state(model, params, ax, with_init)
-      283 @wrap_plot
-      284 def plot_excited_state(model, params, ax=None, with_init=False):
-  --> 285     with aux.get_data(model) as data:
-      286         mask = model.t >= 0 if with_init else model.t > params.τ_init
-      288         plot_with_σ(
-      289             model.t[mask],
-      290             abs(
-     (...)
-      298             ax=ax,
-      299         )
-
-  File ~/src/two_qubit_model/hiro_models/model_auxiliary.py:146, in get_data(model, data_path, read_only, **kwargs)
-      135         return HIData(
-      136             path,
-      137             hi_key=model.hops_config,
-     (...)
-      142             **kwargs,
-      143         )
-      145 else:
-  --> 146     raise RuntimeError(f"No data found for model with hash '{hexhash}'.")
-
-  RuntimeError: No data found for model with hash '043441e996b658af99b232ace67ecc5c8d9ff76b8190a6707bf2556908770a5c'.
-#+end_example
-[[file:./.ob-jupyter/6140cc8a5adedec7ec2beecd22a919c202fd1f03.svg]]
+| <Figure | size | 520x320 | with | 1 | Axes> | <AxesSubplot:> |
+[[file:./.ob-jupyter/5ab38efefb7c03476efb3dea22c64715e4c7131f.svg]]
 :END:
 
 #+begin_src jupyter-python
@@ -182,7 +152,7 @@ Init ray and silence stocproc.
 #+RESULTS:
 :RESULTS:
 | <Figure | size | 520x320 | with | 1 | Axes> | <AxesSubplot:> |
-[[file:./.ob-jupyter/39b065c6a65911b3349c41e28138c9e15ff080da.svg]]
+[[file:./.ob-jupyter/b53ff9a196a6e3f854b4fac57edc3a4f6341ab5c.svg]]
 :END:
 
 
@@ -192,6 +162,6 @@ Init ray and silence stocproc.
 
 #+RESULTS:
 :RESULTS:
-| <Figure | size | 520x320 | with | 1 | Axes> | <AxesSubplot:title= | (center : \(\bar{P}=-0.00092\pm 0.00015\)) | xlabel= | $\tau$ | ylabel= | $\langle{P}\rangle$ | > | EnsembleValue | (((40000 -0.000918483945087149 0.00014770367528033136))) |
-[[file:./.ob-jupyter/833c93cdbf0589c458fc058a3db8852a1144950e.svg]]
+| <Figure | size | 520x320 | with | 1 | Axes> | <AxesSubplot:title= | (center : \(\bar{P}=0.00043\pm 0.00015\)) | xlabel= | $\tau$ | ylabel= | $\langle{P}\rangle$ | > | EnsembleValue | (((20000 0.00043025179411284724 0.00014964069641804805))) |
+[[file:./.ob-jupyter/857d74261d2e1c38fc8bb26c43a46e15552ede09.svg]]
 :END: