semms to work reasonably well now

scripts/experiments/007_generate_fake_analysis_data.py

@@ -34,7 +34,7 @@ def make_params_and_solve(
         laser_detuning=laser_detuning,
         N=N,
         N_couplings=N,
-        measurement_detuning=Ω * (3),
+        measurement_detuning=200,
         α=0,
         rwa=False,
         flat_energies=False,
@@ -48,10 +48,9 @@ def make_params_and_solve(
 
     params.drive_override = (
         np.array([params.Ω, params.Ω * (1 - params.δ), params.δ * 2 * params.Ω]),
-        np.repeat(params.Ω, 3),
+        np.ones(3),
     )
-    params.drive_override[1][-1] *= 4
-    params.drive_override[1][-1] *= 4
+    params.drive_override[1][-1] *= 2
 
     t = time_axis(params, lifetimes=total_lifetimes, resolution=0.01)
     solution = solve(t, params)
@@ -75,8 +74,8 @@ def generate_phase_one_data():
         eom_off_lifetime,
         N=20,
         g_0=1,
-        small_loop_detuning=0,  # 0.05,
-        laser_detuning=-0.01,
+        small_loop_detuning=0.1,
+        laser_detuning=0.1,
     )
     signal = output_signal(t, solution.y, params)
 
@@ -109,7 +108,7 @@ def generate_phase_one_data():
 
     ringdown_params = RingdownParams(
         fω_shift=params.measurement_detuning,
-        mode_window=(params.N + 2, params.N + 2),
+        mode_window=(5, 5),
         fΩ_guess=params.Ω * (1 + rng.standard_normal() * fluct_size),
         fδ_guess=params.Ω * params.δ * (1 + rng.standard_normal() * fluct_size),
         η_guess=params.η * (1 + rng.standard_normal() * fluct_size),
@@ -121,7 +120,12 @@ def generate_phase_one_data():
     plot_spectrum_and_peak_info(ax_spectrum, peak_info, ringdown_params)
 
     Ω, ΔΩ, δ, Δδ, ladder = extract_Ω_δ(
-        peak_info, ringdown_params, Ω_threshold=0.1, ladder_threshold=0.1, start_peaks=4
+        peak_info,
+        ringdown_params,
+        Ω_threshold=0.1,
+        ladder_threshold=0.1,
+        start_peaks=6,
+        bifurcations=5,
     )
 
     for index, type in ladder:
@@ -135,8 +139,9 @@ def generate_phase_one_data():
             label=type,
         )
 
+    runtime = RuntimeParams(params)
     fig.suptitle(
-        f"""Calibration Phase One Demonstration\n N={params.N} * 2 modes g_0={params.g_0}, SNR={SNR}, Ω (input) = {params.Ω:.2f}, δ (input) = {params.Ω*params.δ:.2f}
+        f"""Calibration Phase One Demonstration\n N={params.N} * 2 modes g_0={params.g_0}, SNR={SNR}, Ω (input) = {params.Ω:.2f}, δ (input) = {(runtime.mode_splitting):.2f}
 Ω={Ω:.2f} ± {ΔΩ:.2f}, δ={δ:.2f} ± {Δδ:.2f}
 """
     )

src/rabifun/system.py

@@ -159,23 +159,12 @@ class RuntimeParams:
         )  # linear frequencies!
         if params.drive_override is not None:
             self.drive_frequencies = params.drive_override[0]
-            self.g = 2 * np.pi * params.drive_override[1]
+            self.g = params.drive_override[1]
+
             a_shift = 0
             self.detunings *= 0
             self.g *= params.g_0 / np.sqrt(np.sum(self.g**2))
 
-        # print(params.δ * 2 - (a_frequency - anti_a_frequency))
-        # print((params.Ω - params.δ) - (params.Ω - a_frequency))
-        # print(
-        #     (freqs[2] - freqs[1]) / (2 * np.pi),
-        #     (params.Ω * (1 - a_frequency)),
-        #     (params.Ω * (1 - params.δ)),
-        # )
-        # print(np.diff(freqs) / (2 * np.pi))
-        # import ipdb
-
-        # ipdb.set_trace()
-
         self.g *= 2 * np.pi
         self.Ωs = Ωs
 
@@ -205,8 +194,10 @@ class RuntimeParams:
 
         self.detuning_matrix = self.detuned_Ωs[:, None] - self.detuned_Ωs[None, :]
 
-    def __repr__(self):
-        return f"{self.__class__.__name__}(Ωs={self.Ωs}, drive_frequencies={self.drive_frequencies}, drive_amplitudes={self.g})"
+    @property
+    def mode_splitting(self):
+        """The mode splitting of the system in *frequency units*."""
+        return (self.Ωs[1] - self.Ωs[0]).real / (4 * np.pi)
 
 
 def time_axis(