From d977670eab54af5c611f2a74e617d224fd710936 Mon Sep 17 00:00:00 2001 From: Valentin Boettcher Date: Mon, 25 Jul 2022 22:08:17 +0200 Subject: [PATCH] 10: more periods, longer init --- .../10_antizeno_engine/10_first_anti_zeno.py | 6 +-- .../10_antizeno_engine/anti_zeno_engine.org | 46 +++++++++++++------ 2 files changed, 36 insertions(+), 16 deletions(-) diff --git a/python/energy_flow_proper/10_antizeno_engine/10_first_anti_zeno.py b/python/energy_flow_proper/10_antizeno_engine/10_first_anti_zeno.py index e91bcd9..0a7a75e 100644 --- a/python/energy_flow_proper/10_antizeno_engine/10_first_anti_zeno.py +++ b/python/energy_flow_proper/10_antizeno_engine/10_first_anti_zeno.py @@ -218,7 +218,7 @@ def anti_zeno_engine( ε=1,#.1, ω_c=2, ε_couple=0.7, - n=4, + n=12, detune=.5, ω_0=20, T_c=1e3, @@ -227,7 +227,7 @@ def anti_zeno_engine( γ=.2, switch_cycles=1, therm_initial_state=False, - ε_init=.1, + ε_init=.1/2, terms=6, dt=0.01, sp_tol=1e-3, @@ -311,7 +311,7 @@ with aux.get_data(model) as data: ρ_ee = data.rho_t_accum.mean[:, 0, 0].real -plt.plot(model.t, ρ_ee) +# plt.plot(model.t, ρ_ee) plt.plot(model.t, ut.smoothen(model.t, ρ_ee, frac=.06, it=0)) diff --git a/python/energy_flow_proper/10_antizeno_engine/anti_zeno_engine.org b/python/energy_flow_proper/10_antizeno_engine/anti_zeno_engine.org index 4989381..c5848e8 100644 --- a/python/energy_flow_proper/10_antizeno_engine/anti_zeno_engine.org +++ b/python/energy_flow_proper/10_antizeno_engine/anti_zeno_engine.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': '141.30.17.225', 'raylet_ip_address': '141.30.17.225', 'redis_address': None, 'object_store_address': '/tmp/ray/session_2022-07-25_14-41-55_295382_2912078/sockets/plasma_store', 'raylet_socket_name': '/tmp/ray/session_2022-07-25_14-41-55_295382_2912078/sockets/raylet', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-07-25_14-41-55_295382_2912078', 'metrics_export_port': 52919, 'gcs_address': '141.30.17.225:36995', 'address': '141.30.17.225:36995', 'node_id': '995901bf6a2394187d4d497304265d37862811c6c6b957849e379b0a'}) +: 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_2022-07-25_22-00-30_945686_3162741/sockets/plasma_store', 'raylet_socket_name': '/tmp/ray/session_2022-07-25_22-00-30_945686_3162741/sockets/raylet', 'webui_url': '', 'session_dir': '/tmp/ray/session_2022-07-25_22-00-30_945686_3162741', 'metrics_export_port': 57398, 'gcs_address': '141.30.17.225:47171', 'address': '141.30.17.225:47171', 'node_id': 'ec35f16714019c3e897b7d2e14e60586716f2ef0d72e3c5085510348'}) #+begin_src jupyter-python :results none from hops.util.logging_setup import logging_setup @@ -237,7 +237,7 @@ Init ray and silence stocproc. ε=1,#.1, ω_c=2, ε_couple=0.7, - n=4, + n=12, detune=.5, ω_0=20, T_c=1e3, @@ -246,7 +246,7 @@ Init ray and silence stocproc. γ=.2, switch_cycles=1, therm_initial_state=False, - ε_init=.1, + ε_init=.1/2, terms=6, dt=0.01, sp_tol=1e-3, @@ -317,8 +317,8 @@ Let's test the assumptions of the paper. #+RESULTS: :RESULTS: -: -[[file:./.ob-jupyter/4a970ef1e5583c085376f49d8c28e0d089db2897.svg]] +: +[[file:./.ob-jupyter/4b60e04c9426dcd4913627aceeac9e9adf55989f.svg]] :END: #+begin_src jupyter-python :tangle nil @@ -368,7 +368,7 @@ Let's test the assumptions of the paper. #+end_src #+RESULTS: -[[file:./.ob-jupyter/037c2f495a4aab55f6678990a5a40af9b1dc276e.svg]] +[[file:./.ob-jupyter/df1bb49b2d831b72f47fb1276f1abd8782708179.svg]] #+begin_src jupyter-python ts = np.linspace(0,50,1000) @@ -523,7 +523,7 @@ Let's test the assumptions of the paper. #+end_src #+RESULTS: -[[file:./.ob-jupyter/0bc30f7339c1a8fd5e874736b36475fa8ae8e057.svg]] +[[file:./.ob-jupyter/d3befbb9d1b11bcbd94eb7452b2dd9f4a0784f47.svg]] - **too fast decoupling kills it** - no anti-zeno effects without detuning? @@ -549,20 +549,32 @@ Let's test the assumptions of the paper. #+end_src #+RESULTS: -[[file:./.ob-jupyter/26455cb6c80fa89722bc6f48e49b2840a3ff75dc.svg]] +:RESULTS: +: /nix/store/akzgacnj2l97sldws5cnxjlgv27317xd-python3-3.9.13-env/lib/python3.9/site-packages/matplotlib/cbook/__init__.py:1298: ComplexWarning: Casting complex values to real discards the imaginary part +: return np.asarray(x, float) +: /nix/store/akzgacnj2l97sldws5cnxjlgv27317xd-python3-3.9.13-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5218: ComplexWarning: Casting complex values to real discards the imaginary part +: pts[0] = start +: /nix/store/akzgacnj2l97sldws5cnxjlgv27317xd-python3-3.9.13-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5219: ComplexWarning: Casting complex values to real discards the imaginary part +: pts[N + 1] = end +: /nix/store/akzgacnj2l97sldws5cnxjlgv27317xd-python3-3.9.13-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5222: ComplexWarning: Casting complex values to real discards the imaginary part +: pts[1:N+1, 1] = dep1slice +: /nix/store/akzgacnj2l97sldws5cnxjlgv27317xd-python3-3.9.13-env/lib/python3.9/site-packages/matplotlib/axes/_axes.py:5224: ComplexWarning: Casting complex values to real discards the imaginary part +: pts[N+2:, 1] = dep2slice[::-1] +[[file:./.ob-jupyter/bdbfb7472f39f1754b44fa9362ea38cb2f328ee6.svg]] +:END: - no steady state ... but we have to average... #+begin_src jupyter-python - plt.plot(model.t, ρ_ee) + # plt.plot(model.t, ρ_ee) plt.plot(model.t, ut.smoothen(model.t, ρ_ee, frac=.06, it=0)) #+end_src #+RESULTS: :RESULTS: -| | -[[file:./.ob-jupyter/d6322a2cfa8157f6d6369a23f0ed6b97d793a210.svg]] +| | +[[file:./.ob-jupyter/15866c10ff396d5cf845d81482f7a03a06763d03.svg]] :END: ** TODO Power and Efficiency @@ -587,6 +599,14 @@ We need the time points where we sample the total energy. #ax.plot(model.t, np.gradient(model.total_energy(data).value)) #+end_src +#+RESULTS: +:RESULTS: +: +: KeyboardInterrupt +: +[[file:./.ob-jupyter/8a673495cd87215235b3b2edf4b58bbee5fdc597.svg]] +:END: + #+begin_src jupyter-python ts_begin = τ_init + τ_off + ((τ_c + τ_off) * np.arange(0, n)) ts_end = τ_c + ts_begin @@ -645,8 +665,8 @@ We need the time points where we sample the total energy. #+RESULTS: :RESULTS: -: \(P=-0.0065\pm 0.0017\) -[[file:./.ob-jupyter/b8415ff3ff1ca0d745bbbb682031b0cba8276302.svg]] +: \(P=0.0101\pm 0.0027\) +[[file:./.ob-jupyter/e508f485cb6d1f43d160d67d409ac40986c810da.svg]] :END: