Ladder-Type Three-Level: Weak Pulse with Coupling — EIT

Define the Problem

mb_solve_json = """
{
  "atom": {
    "decays": [
      { "channels": [[0,1]],
        "rate": 1.0
      },
      { "channels": [[1,2]],
        "rate": 1.0e-3
      }
    ],
    "fields": [
      {
        "coupled_levels": [[0, 1]],
        "detuning": 5.0,
        "detuning_positive": true,
        "label": "probe",
        "rabi_freq": 1.0e-3,
        "rabi_freq_t_args":
          {
             "ampl": 1.0,
             "centre": 0.0,
             "fwhm": 1.0
          },
        "rabi_freq_t_func": "gaussian"
      },
      {
        "coupled_levels": [[1, 2]],
        "detuning": 0.0,
        "detuning_positive": true,
        "label": "coupling",
        "rabi_freq": 5.0,
        "rabi_freq_t_args":
        {
          "ampl": 1.0,
          "fwhm": 0.2,
          "on": -1.0,
          "off": 9.0
          },
        "rabi_freq_t_func": "ramp_onoff"
      }
    ],
    "num_states": 3
  },
  "t_min": -2.0,
  "t_max": 10.0,
  "t_steps": 60,
  "z_min": -0.2,
  "z_max": 1.2,
  "z_steps": 100,
  "z_steps_inner": 2,
  "interaction_strengths": [100.0, 100.0],
  "savefile": "mbs-ladder-weak-pulse-coupling-decay"
}
"""

from maxwellbloch import mb_solve
mb_solve_00 = mb_solve.MBSolve().from_json_str(mb_solve_json)

## Solve the Problem

%time Omegas_zt, states_zt = mb_solve_00.mbsolve(recalc=False)

Loaded tuple object.
CPU times: user 1.7 ms, sys: 312 µs, total: 2.01 ms
Wall time: 2.01 ms

## Plot Output

import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns

sns.set_style("dark")

import numpy as np

fig = plt.figure(1, figsize=(16, 12))

# Probe
ax = fig.add_subplot(211)
cmap_range = np.linspace(0.0, 1.0e-3, 11)
cf = ax.contourf(mb_solve_00.tlist, mb_solve_00.zlist,
                 np.abs(mb_solve_00.Omegas_zt[0]/(2*np.pi)),
                 cmap_range, cmap=plt.cm.Blues)
ax.set_title('Rabi Frequency ($\Gamma / 2\pi $)')
ax.set_ylabel('Distance ($L$)')
ax.text(0.02, 0.95, 'Probe',
        verticalalignment='top', horizontalalignment='left',
        transform=ax.transAxes, color='grey', fontsize=16)
plt.colorbar(cf)

# Coupling
ax = fig.add_subplot(212)
cmap_range = np.linspace(0.0, 8.0, 11)
cf = ax.contourf(mb_solve_00.tlist, mb_solve_00.zlist,
                 np.abs(mb_solve_00.Omegas_zt[1]/(2*np.pi)),
                 cmap_range, cmap=plt.cm.Greens)
ax.set_xlabel('Time ($1/\Gamma$)')
ax.set_ylabel('Distance ($L$)')
ax.text(0.02, 0.95, 'Coupling',
        verticalalignment='top', horizontalalignment='left',
        transform=ax.transAxes, color='grey', fontsize=16)
plt.colorbar(cf)

# Both
for ax in fig.axes:
    for y in [0.0, 1.0]:
        ax.axhline(y, c='grey', lw=1.0, ls='dotted')
plt.tight_layout();