mirror of
https://github.com/vale981/fibre_walk_project_code
synced 2025-03-04 09:21:38 -05:00
some new experiments
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3 changed files with 472 additions and 0 deletions
229
scripts/experiments/010_scan_v_ringdown.py
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229
scripts/experiments/010_scan_v_ringdown.py
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@ -0,0 +1,229 @@
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from rabifun.system import *
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from rabifun.plots import *
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from rabifun.utilities import *
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from rabifun.analysis import *
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from ringfit.data import ScanData
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import functools
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from scipy.ndimage import rotate
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# %% interactive
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def make_params_and_solve(
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total_lifetimes,
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eom_off_lifetime,
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ω_c=0.1 / 2,
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N=10,
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g_0=1 / 4,
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small_loop_detuning=0,
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laser_detuning=0,
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η=1.0,
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η_hybrid=1.0,
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drive_mode="all",
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scan=False,
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):
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"""
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Make a set of parameters for the system with the current
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best-known settings.
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"""
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Ω = 13
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params = Params(
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η=η,
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η_hybrid=η_hybrid,
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Ω=Ω,
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δ=1 / 4,
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ω_c=ω_c,
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g_0=g_0,
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laser_detuning=laser_detuning,
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N=N,
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N_couplings=N,
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measurement_detuning=0,
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α=0,
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rwa=False,
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flat_energies=False,
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correct_lamb_shift=0,
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laser_off_time=0,
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small_loop_detuning=small_loop_detuning,
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)
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params.laser_off_time = params.lifetimes(eom_off_lifetime)
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params.drive_off_time = params.lifetimes(eom_off_lifetime)
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if scan:
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params.laser_off_time = None
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params.dynamic_detunting = (N) * Ω, params.lifetimes(total_lifetimes)
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params.drive_off_time = 0
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match drive_mode:
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case "hybrid":
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params.drive_override = (
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np.array([params.Ω * params.δ * 2]),
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np.ones(1),
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)
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case "hybrid_to_one_bath":
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params.drive_override = (
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np.array([params.Ω * (1 - params.δ), params.Ω * (1 + params.δ)]),
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np.ones(2),
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)
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case "bath":
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params.drive_override = (
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np.array([params.Ω]),
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np.ones(1),
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)
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case _:
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params.drive_override = (
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np.array(
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[params.Ω, params.Ω * (1 - params.δ), params.δ * 2 * params.Ω]
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),
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np.ones(3),
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)
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t = time_axis(params, lifetimes=total_lifetimes, resolution=0.001)
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solution = solve(t, params)
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return params, t, solution
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def generate_phase_one_data(
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drive_mode="full",
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g_0=0.3,
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off_factor=0.21,
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noise=False,
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extra_title="",
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laser_detuning=0,
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yscale="linear",
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scan=False,
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):
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"""
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This generates some intensity data for phase one of the
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calibration protocol, where the aim is to extract the resonator
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spectrum.
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"""
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total_lifetimes = 2
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eom_off_lifetime = total_lifetimes * off_factor
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fluct_size = 0.05
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noise_amp = 0.3
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params, t, solution = make_params_and_solve(
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total_lifetimes,
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eom_off_lifetime,
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N=2,
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g_0=g_0,
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small_loop_detuning=0,
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laser_detuning=laser_detuning,
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η=0.18,
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η_hybrid=0.18 * 5,
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drive_mode=drive_mode,
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scan=scan,
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)
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rng = np.random.default_rng(seed=0)
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raw_signal = output_signal(t, solution.y, params)
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signal = raw_signal.copy()
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if noise:
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signal += noise_amp * rng.standard_normal(len(signal))
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fig = make_figure(f"simulation_noise_{noise}", figsize=(20, 3 * 5))
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ax_realtime, ax_rotating_bath, ax_rotating_system, ax_spectrum = (
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fig.subplot_mosaic("""
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AA
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BC
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DD
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DD
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""").values()
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)
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ax_rotating_system.sharey(ax_rotating_bath)
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ax_rotating_system.sharex(ax_rotating_bath)
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for mode in range(2):
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ax_rotating_system.plot(
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t[::50],
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abs(np.imag(solution.y[mode, ::50])) ** 2
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/ 2
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* (params.η / params.η_hybrid) ** 2,
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)
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for mode in range(2, solution.y.shape[0]):
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ax_rotating_bath.plot(t[::50], abs(np.imag(solution.y[mode, ::50])) ** 2)
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for ax in [ax_rotating_bath, ax_rotating_system]:
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ax.set_xlabel("Time")
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ax.set_ylabel("Intensity")
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ax_rotating_bath.set_title("Bath Modes")
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ax_rotating_system.set_title(
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"Hybridized Modes [corrected for magnitude visible in FFT]"
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)
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ax_realtime.plot(t[::50], signal[::50])
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ax_realtime.axvline(params.drive_off_time, color="black", linestyle="--")
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ax_realtime.set_xlabel("Time")
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ax_realtime.set_ylabel("Intensity")
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ax_realtime.set_title("Photo-diode AC Intensity")
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# now we plot the power spectrum
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window = (float(params.laser_off_time or 0), t[-1])
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# window = (0, float(params.laser_off_time or 0))
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ringdown_params = RingdownParams(
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fω_shift=params.measurement_detuning,
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mode_window=(5, 5),
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fΩ_guess=params.Ω * (1 + rng.standard_normal() * fluct_size),
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fδ_guess=params.Ω * params.δ * (1 + rng.standard_normal() * fluct_size),
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η_guess=0.5, # params.η * (1 + rng.standard_normal() * fluct_size),
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absolute_low_cutoff=2,
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)
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scan = ScanData(np.ones_like(signal), signal, t)
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peak_info = find_peaks(scan, ringdown_params, window, prominence=0.01)
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peak_info = refine_peaks(peak_info, ringdown_params)
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plot_spectrum_and_peak_info(ax_spectrum, peak_info, ringdown_params)
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runtime = RuntimeParams(params)
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for i, freq in enumerate(runtime.Ωs.real):
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pos = np.abs(
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params.measurement_detuning
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- freq / (2 * np.pi)
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+ params.δ * params.Ω
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+ params.laser_detuning,
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)
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ax_spectrum.axvline(
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pos,
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color="red",
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linestyle="--",
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zorder=-100,
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)
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ax_spectrum.annotate(mode_name(i), (pos + 0.1, peak_info.power.max()))
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ax_spectrum.set_xlim(ringdown_params.low_cutoff, ringdown_params.high_cutoff)
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ax_spectrum.set_yscale(yscale)
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fig.suptitle(
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f"""Calibration Phase One Demonstration {'with noise' if noise else ''}
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N={params.N} * 2 + 2 modes g_0={params.g_0}Ω, Noise Amp={noise_amp}, η={params.η}MHz, η_hybrid={params.η_hybrid}MHz
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"""
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+ extra_title
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)
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return fig
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# %% save
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if __name__ == "__main__":
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fig = generate_phase_one_data(
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laser_detuning=-13 / 3 * 2,
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g_0=0.3,
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drive_mode="hybrid_to_one_bath",
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off_factor=0.4,
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noise=False,
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scan=True,
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)
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229
scripts/experiments/011_dark_state.py
Normal file
229
scripts/experiments/011_dark_state.py
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@ -0,0 +1,229 @@
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from rabifun.system import *
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from rabifun.plots import *
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from rabifun.utilities import *
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from rabifun.analysis import *
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from ringfit.data import ScanData
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import functools
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from scipy.ndimage import rotate
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# %% interactive
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def make_params_and_solve(
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total_lifetimes,
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eom_off_lifetime,
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ω_c=0.1 / 2,
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N=10,
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g_0=1 / 4,
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small_loop_detuning=0,
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laser_detuning=0,
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η=1.0,
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η_hybrid=1.0,
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drive_mode="all",
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scan=False,
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):
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"""
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Make a set of parameters for the system with the current
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best-known settings.
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"""
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Ω = 13
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params = Params(
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η=η,
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η_hybrid=η_hybrid,
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Ω=Ω,
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δ=1 / 4,
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ω_c=ω_c,
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g_0=g_0,
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laser_detuning=laser_detuning,
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N=N,
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N_couplings=N,
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measurement_detuning=0,
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α=0,
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rwa=False,
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flat_energies=False,
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correct_lamb_shift=0,
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laser_off_time=0,
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small_loop_detuning=small_loop_detuning,
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)
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params.laser_off_time = params.lifetimes(eom_off_lifetime)
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params.drive_off_time = params.lifetimes(eom_off_lifetime)
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if scan:
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params.laser_off_time = None
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params.dynamic_detunting = (N) * Ω, params.lifetimes(total_lifetimes)
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params.drive_off_time = 0
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match drive_mode:
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case "hybrid":
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params.drive_override = (
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np.array([params.Ω * params.δ * 2]),
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np.ones(1),
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)
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case "hybrid_to_one_bath":
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params.drive_override = (
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np.array([params.Ω * (1 - params.δ), params.Ω * (1 + params.δ)]),
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np.ones(2),
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)
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case "bath":
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params.drive_override = (
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np.array([params.Ω]),
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np.ones(1),
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)
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case _:
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params.drive_override = (
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np.array(
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[params.Ω, params.Ω * (1 - params.δ), params.δ * 2 * params.Ω]
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),
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np.ones(3),
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)
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t = time_axis(params, lifetimes=total_lifetimes, resolution=0.001)
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solution = solve(t, params)
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return params, t, solution
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def generate_phase_one_data(
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drive_mode="full",
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g_0=0.3,
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off_factor=0.21,
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noise=False,
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extra_title="",
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laser_detuning=0,
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yscale="linear",
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scan=False,
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):
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"""
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This generates some intensity data for phase one of the
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calibration protocol, where the aim is to extract the resonator
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spectrum.
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"""
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total_lifetimes = 2
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eom_off_lifetime = total_lifetimes * off_factor
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fluct_size = 0.05
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noise_amp = 0.3
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params, t, solution = make_params_and_solve(
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total_lifetimes,
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eom_off_lifetime,
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N=2,
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g_0=g_0,
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small_loop_detuning=0,
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laser_detuning=laser_detuning,
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η=0.18,
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η_hybrid=0.18 * 5,
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drive_mode=drive_mode,
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scan=scan,
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)
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rng = np.random.default_rng(seed=0)
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raw_signal = output_signal(t, solution.y, params)
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signal = raw_signal.copy()
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if noise:
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signal += noise_amp * rng.standard_normal(len(signal))
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fig = make_figure(f"simulation_noise_{noise}", figsize=(20, 3 * 5))
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ax_realtime, ax_rotating_bath, ax_rotating_system, ax_spectrum = (
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fig.subplot_mosaic("""
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AA
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BC
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DD
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DD
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""").values()
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)
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ax_rotating_system.sharey(ax_rotating_bath)
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ax_rotating_system.sharex(ax_rotating_bath)
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for mode in range(2):
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ax_rotating_system.plot(
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t[::50],
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abs(np.imag(solution.y[mode, ::50])) ** 2
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/ 2
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* (params.η / params.η_hybrid) ** 2,
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)
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for mode in range(2, solution.y.shape[0]):
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ax_rotating_bath.plot(t[::50], abs(np.imag(solution.y[mode, ::50])) ** 2)
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for ax in [ax_rotating_bath, ax_rotating_system]:
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ax.set_xlabel("Time")
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ax.set_ylabel("Intensity")
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ax_rotating_bath.set_title("Bath Modes")
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ax_rotating_system.set_title(
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"Hybridized Modes [corrected for magnitude visible in FFT]"
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)
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ax_realtime.plot(t[::50], signal[::50])
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ax_realtime.axvline(params.drive_off_time, color="black", linestyle="--")
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ax_realtime.set_xlabel("Time")
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ax_realtime.set_ylabel("Intensity")
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ax_realtime.set_title("Photo-diode AC Intensity")
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|
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# now we plot the power spectrum
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window = (float(params.laser_off_time or 0), t[-1])
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# window = (0, float(params.laser_off_time or 0))
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ringdown_params = RingdownParams(
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fω_shift=params.measurement_detuning,
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mode_window=(5, 5),
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fΩ_guess=params.Ω * (1 + rng.standard_normal() * fluct_size),
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fδ_guess=params.Ω * params.δ * (1 + rng.standard_normal() * fluct_size),
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η_guess=0.5, # params.η * (1 + rng.standard_normal() * fluct_size),
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absolute_low_cutoff=2,
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)
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scan = ScanData(np.ones_like(signal), signal, t)
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peak_info = find_peaks(scan, ringdown_params, window, prominence=0.01)
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peak_info = refine_peaks(peak_info, ringdown_params)
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plot_spectrum_and_peak_info(ax_spectrum, peak_info, ringdown_params)
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runtime = RuntimeParams(params)
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for i, freq in enumerate(runtime.Ωs.real):
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pos = np.abs(
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params.measurement_detuning
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- freq / (2 * np.pi)
|
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+ params.δ * params.Ω
|
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+ params.laser_detuning,
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)
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ax_spectrum.axvline(
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pos,
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color="red",
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linestyle="--",
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zorder=-100,
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)
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ax_spectrum.annotate(mode_name(i), (pos + 0.1, peak_info.power.max()))
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ax_spectrum.set_xlim(ringdown_params.low_cutoff, ringdown_params.high_cutoff)
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ax_spectrum.set_yscale(yscale)
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fig.suptitle(
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f"""Calibration Phase One Demonstration {'with noise' if noise else ''}
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N={params.N} * 2 + 2 modes g_0={params.g_0}Ω, Noise Amp={noise_amp}, η={params.η}MHz, η_hybrid={params.η_hybrid}MHz
|
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"""
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+ extra_title
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)
|
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|
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return fig
|
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|
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|
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# %% save
|
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if __name__ == "__main__":
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fig = generate_phase_one_data(
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laser_detuning=-13 / 3 * 2,
|
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g_0=0.3,
|
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drive_mode="hybrid_to_one_bath",
|
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off_factor=0.4,
|
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noise=False,
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scan=True,
|
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)
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|
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@ -234,6 +234,20 @@ def plot_spectrum_and_peak_info(
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color="C2",
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)
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ax_angle = ax.twinx()
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ax_angle.clear()
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ax_angle.set_ylabel("Phase (rad)")
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unwrapped = np.unwrap(np.angle(peaks.fft) * 2) / 2
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ax_angle.plot(
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peaks.freq,
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unwrapped,
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linestyle="--",
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alpha=0.5,
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linewidth=0.5,
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zorder=10,
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)
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if annotate:
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for i, (freq, height, lorentz) in enumerate(
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zip(peaks.peak_freqs, peaks.power[peaks.peaks], peaks.lorentz_params)
|
||||
|
|
|
|||
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Reference in a new issue