Replication Data for: Atomic-optical interferometry in fractured loops: a general solution for Rydberg radio frequency receivers

Simulation Data The .npy and .npz files store the results of simulations that are visualized in Figure 3 and Figures 5-12. For all plots we use Matplotlib and Numpy packages. Variable path is the path to de storage with data. Plotting the Fig. 3 - a4p_mode_evol import matplotlib.pyplot as plt import numpy as np plot_data = np.load(path + r"\a4p_mode_evol.npy") re01 = np.real(plot_data[:, 1, 0]) im01 = np.imag(plot_data[:, 1, 0]) p11 = plot_data[:, 1, 1] x = np.linspace(0, 3, p11.shape[0]) fig, axes = plt.subplots(nrows=3, figsize=(6, 5), sharex=True) axes[0].set_ylabel(r"$\text{Im}{\tilde{\boldsymbol{\rho}}_{10}}$") axes[0].plot(x, im01, label=r"$\text{Im}{\tilde{\boldsymbol{\rho}}_{01}}$") axes[1].set_ylabel(r"$\text{Re}{\tilde{\boldsymbol{\rho}}_{10}}$") axes[1].plot(x, re01, label=r"$\text{Re}{\tilde{\boldsymbol{\rho}}_{01}}$") axes[2].set_ylabel(r"$\tilde{\boldsymbol{\rho}}_{11}$") axes[2].plot(x, p11.real, label=r"$\tilde{\boldsymbol{\rho}}_{11}$") axes[2].set_xlabel(r"$\delta t$ [$2\pi$ rad]") fig.tight_layout() plt.show() Plotting the Fig. 5 - mod_transfer_gamma_transit_lo_delta import matplotlib.pyplot as plt import numpy as np plot_data = np.load(path + r"\mod_transfer_gamma_transit_lo_delta.npy") fig, ax = plt.subplots(figsize=(6, 6)) omega_seq = np.linspace(0.05, 15, 500) delta_seq = np.linspace(-7.5, 7.5, 500) obj = ax.imshow( plot_data, cmap="YlOrRd", interpolation="none", extent=[omega_seq[0], omega_seq[-1], delta_seq[0], delta_seq[-1]], aspect="equal", ) ax.set_xlabel("$\Omega_{LO}$ [$2 \pi \cdot$MHz]") ax.set_ylabel("$\delta$ [$2 \pi \cdot$MHz]") ax.set_title("$\Omega_{LS} = 0.05 \cdot$$2 \pi \cdot$MHz") cbar = fig.colorbar(obj, ax=ax, fraction=0.05, pad=0.04) cbar.set_label(r"$|\alpha_{01}^{(1)}|$") fig.show() Plotting the Fig. 6 - mod_transfer_gamma_transit_ls_compare_1_2 import matplotlib.pyplot as plt import matplotlib.gridspec as gridspec import numpy as np plot_data_1, plot_data_2 = np.load( path + r"\mod_transfer_gamma_transit_ls_compare_1_2.npy" ) omega_seq = np.linspace(0.05, 15, 500) delta_seq = np.linspace(-7.5, 7.5, 500) fig = plt.figure(figsize=(14, 6)) gs = gridspec.GridSpec(1, 3, width_ratios=[1, 1, 0.05], wspace=0) kwargs = { "cmap": "YlOrRd", "interpolation": "none", "extent": [omega_seq[0], omega_seq[-1], delta_seq[0], delta_seq[-1]], "aspect": "equal", "vmin": min(np.abs(plot_data_1).min(), np.abs(plot_data_2).min()), "vmax": max(np.abs(plot_data_1).max(), np.abs(plot_data_2).max()), } ax1 = fig.add_subplot(gs[0]) ax2 = fig.add_subplot(gs[1]) im1 = ax1.imshow(np.abs(plot_data_1), **kwargs) ax1.set_ylabel("$\delta$ [$2 \pi \cdot$MHz]") ax1.set_xlabel("$\Omega_{LS}$ [$2 \pi \cdot$MHz]") ax1.set_title(r"$d = 1$") im2 = ax2.imshow(np.abs(plot_data_2), **kwargs) ax2.set_ylabel("$\delta$ [$2 \pi \cdot$MHz]") ax2.set_xlabel("$\Omega_{LS}$ [$2 \pi \cdot$MHz]") ax2.set_title(r"$d = 2$") ax2.get_yaxis().set_tick_params(labelleft=False) ax2.set_ylabel("") cbar_ax = fig.add_subplot(gs[2]) cbar = fig.colorbar(im1, cax=cbar_ax, fraction=0.05, pad=0.04) cbar.set_label(r"$|\alpha_{01}^{(d)}|$") fig.show() Plotting the Fig. 7 - bandwidth_gamma_transit_ls import matplotlib.pyplot as plt import numpy as np color0, color1, color2 = ("#FF4500", "#FFB6C1", "#800080") plot_data_bandwidth = np.load( path + r"\bandwidth_gamma_transit_ls_plot_data_bandwidth.npy" ) plot_data_mod_transfer = np.load( path + r"\bandwidth_gamma_transit_ls_plot_data_mod_transfer.npy" ) fig, ax1 = plt.subplots() ax1.set_xlabel(r"$\Omega_{LS}~[2\pi \cdot$MHz]") ax1.set_ylabel(r"Bandwidth [$2\pi \cdot$MHz]") ax1.plot(*plot_data_bandwidth, color="blue", label="Bandwidth") ax1.tick_params(axis="y") move = 0.1 ax1.set_ylim(plot_data_bandwidth[1].min() - move, plot_data_bandwidth[1].max() + move) ax2 = ax1.twinx() ax2.set_ylabel(r"$|\alpha_{01}^{(1)}|$") ax2.plot( *plot_data_mod_transfer, color=color2, label=r"$|\alpha_{01}^{(1)}(\delta = 0)|$", ) ax2.tick_params(axis="y") fig.legend(loc="lower left", bbox_to_anchor=(0.17, 0.15)) fig.tight_layout() Plotting the Fig. 8 - calculated detuned smaller peak heights import matplotlib.pyplot as plt import numpy as np color0, color1, color2 = ("#FF4500", "#FFB6C1", "#800080") plot_data_bandwidth = np.load( path + r"\bandwidth_gamma_transit_lo_plot_data_bandwidth.npy" ) plot_data_mod_transfer = np.load( path + r"\bandwidth_gamma_transit_lo_plot_data_mod_transfer.npy" ) fig, ax1 = plt.subplots() ax1.set_xlabel(r"$\Omega_{LO}~[2\pi \cdot$MHz]") ax1.set_ylabel(r"Bandwidth [$2\pi \cdot$MHz]") ax1.plot(*plot_data_bandwidth, color="blue", label="Bandwidth") ax1.tick_params(axis="y") move = 0.1 ax1.set_ylim(plot_data_bandwidth[1].min() - move, plot_data_bandwidth[1].max() + move) ax2 = ax1.twinx() ax2.set_ylabel(r"$|\alpha_{01}^{(1)}|$") ax2.plot( *plot_data_mod_transfer, color=color2, label=r"$|\alpha_{01}^{(1)}(\delta = 0)|$", ) ax2.tick_params(axis="y") fig.legend(loc="lower left", bbox_to_anchor=(0.17, 0.15)) fig.tight_layout() fig.show() Plotting the Fig. 9 -...