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prepare cutoff dependence for taurus

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Valentin Boettcher 2022-08-24 18:14:45 +02:00
parent ba3a81aeb4
commit e76985d0a3
2 changed files with 1114 additions and 564 deletions
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18
python/energy_flow_proper/08_dynamic_one_bath/mod_freq.py
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@ -18,11 +18,11 @@ logging_setup(logging.INFO, show_stocproc=False)
from hops.util.dynamic_matrix import SmoothStep, Periodic, Harmonic, ConstantMatrix
Δs = np.linspace(1,10,20)#np.sort(np.concatenate((np.linspace(1, 5, 20), np.linspace(5, 7, int(20/5 * 2)))))
Δs = np.linspace(1,10,10)#np.sort(np.concatenate((np.linspace(1, 5, 20), np.linspace(5, 7, int(20/5 * 2)))))
Δ_models = []
strobe_ts = []
strobe_indices_s = []
δs = [2, 1,.5, .1]
δs = np.linspace(.1, 2, 10)
for Δ in Δs:
for δ in δs:
proto, strobe_t, strobe_indices = es.energy_shovel(Δ, periods=20, k_max=5, modulate_system=False)
@ -62,10 +62,10 @@ for (model, data), Δ, strobe_t, strobe_indices in zip(
# ax.plot(model.t, model.L(model.t)[:,0,1])
# print(strobe_t[1])
plt.ylabel(r"$\frac{\Delta E}{T}$")
ax.set_xlabel(r"$\Delta$")
ax.set_ylabel(r"$P_\mathrm{max}$")
for i, energy, σ in zip(itertools.count(0), final_e, final_e_error):
ax.errorbar(Δs, energy, σ, label=rf"$\alpha(0)$ = {δs[i]}")
ax.legend()
fs.export_fig("delta_dependence")
# plt.ylabel(r"$\frac{\Delta E}{T}$")
# ax.set_xlabel(r"$\Delta$")
# ax.set_ylabel(r"$P_\mathrm{max}$")
# for i, energy, σ in zip(itertools.count(0), final_e, final_e_error):
# ax.errorbar(Δs, energy, σ, label=rf"$\alpha(0)$ = {δs[i]}")
# ax.legend()
# fs.export_fig("delta_dependence")

1662
python/energy_flow_proper/08_dynamic_one_bath/shovel_experiments.org
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