electron_histogram = np.vstack(
(electron_histogram, electron_hist))
k += 1
#print("Ja!")
Vres = f["Vres"][()]
print("Out of %d simulations, %d did not converge..." %
(len(Vres), len(Vres) - np.sum(converged)))
fig = plt.figure(figsize=(7., 4.))
common.configure_axes(12)
plt.pcolormesh(Vres,
bins[:-1] * 1E6,
np.log10(electron_histogram.T),
vmin=0,
vmax=2.0,
cmap=plt.cm.hot_r)
plt.colorbar()
plt.xlim(Vres[0], Vres[-1])
plt.ylim(np.min(bins) * 1E6, np.max(bins) * 1E6)
plt.xlabel("Resonator voltage (V)")
plt.ylabel("Position across the channel ($\mu$m)")
plt.title(r"$^{10}\log (n_\ell)$ for bin size = %.1f nm" % (dbin * 1E9))
if save:
common.save_figure(fig, os.path.join(save_path, sub_dir))
print("Done!")
plt.show()
def coordinate_transformation(r):
x, y = anneal.r2xy(r)
y_new = EP.map_y_into_domain(y)
r_new = anneal.xy2r(x, y_new)
return r_new
# This is where the actual solving starts...
os.mkdir(os.path.join(save_path, sub_dir))
time.sleep(1)
os.mkdir(os.path.join(save_path, sub_dir, "Figures"))
if save:
common.save_figure(fig0, save_path=os.path.join(save_path, sub_dir))
common.save_figure(fig1, save_path=os.path.join(save_path, sub_dir))
# Save the data to a single file
f = h5py.File(os.path.join(os.path.join(save_path, sub_dir), "Results.h5"),
"w")
f.create_dataset("electrostatic_potential", data=-Uinterp_symmetric)
f.create_dataset("xpoints", data=x_symmetric * 1E-6)
f.create_dataset("ypoints", data=y_box)
f.create_dataset("Vres", data=resVs)
f.create_dataset("use_gradient", data=use_gradient)
f.create_dataset("gradient_tolerance", data=gradient_tolerance)
conv_mon_save_path = os.path.join(save_path, sub_dir, "Figures")
for k, Vres in tqdm(enumerate(resVs)):
plt.ylim(0., cavity_contributions[ten_strongest_mode_numbers[-1, -2]])
plt.xlabel("Mode number")
plt.ylabel("Cavity contributions")
plt.title("$V_\mathrm{res}$ = %.2f V" % Vres[-1])
Voi = 0.25
Voi_idx = common.find_nearest(np.array(Vres), Voi)
modes = ten_strongest_mode_numbers[Voi_idx, 1:10]
fig3 = plt.figure(figsize=(6., 4.))
plt.plot(np.sqrt(Eigenvalues[Voi_idx, ranked_cavity_contributions]) / (2 * np.pi * 1E9), 'o', **common.plot_opt('red', msize=4))
plt.xlabel("Decreasing coupling to the cavity")
plt.ylabel("$\omega_e/2\pi$ (GHz)")
plt.title("Frequency of all modes at Vres = %.2f V" % Voi)
if save:
common.save_figure(fig3, save_path=os.path.join(save_path, sub_dir))
# Look at the electron position of the last voltage step and single out the electrons in the left and right row
# Note: this only makes sense if you have two rows!
xi, yi = anneal.r2xy(electron_positions[Voi_idx, :])
right_idxs = np.where(xi > 0)[0]
sorted_right_idxs = np.argsort(right_idxs)
left_idxs = np.where(xi < 0)[0]
sorted_left_idxs = np.argsort(left_idxs)
sorted_idxs = np.argsort(yi)
if len(right_idxs) == 0 or len(left_idxs) == 0:
print("2 row configuration not detected, assuming 1 row")
two_rows = False
else:
two_rows = False
f.create_dataset("Vtg", data=Vtg)
f.close()
time.sleep(1)
# Take a slice through the middle, at y = 0 to check if the insertion went well and doesn't produce weird gradients.
if 0:
U = output[0]['V'].T
fig = plt.figure(figsize=(10.,3.))
common.configure_axes(13)
plt.plot(x_eval[np.int(len(y_eval)/2), :] * 1E6, -U[np.int(len(y_eval)/2), :], '-k')
plt.plot(x_trap_init * 1E6, np.zeros(len(x_trap_init)), 'o', color='mediumpurple', alpha=0.5)
plt.xlabel("$x$ ($\mu$m)")
plt.ylabel("Potential energy (eV)")
if save:
common.save_figure(fig, save_path=os.path.join(save_path, sub_dir))
plt.show()
# This is where the actual solving starts...
t = trap_analysis.TrapSolver()
c = trap_analysis.get_constants()
x_eval, y_eval, cropped_potentials = t.crop_potentials(output, ydomain=None, xdomain=None)
for k, s in tqdm(enumerate(sweep_points)):
coefficients = np.array([Vres, Vtrap, Vrg, Vcg, Vtg])
coefficients[SweepIdx] = s
if Vcg is None:
coefficients = np.delete(coefficients, 3)
plt.close('all')
if twod_slice:
electron_pos = electron_ri[::2] * 1E6
fig = plt.figure(figsize=(7., 3.))
common.configure_axes(13)
plt.plot(x_plot * 1E6, CMS.V(x_plot, 0), '-', color='orange')
plt.plot(electron_pos[electron_pos < 6],
CMS.V(electron_pos[electron_pos < 6] * 1E-6, 0) +
0.005,
'o',
color='cornflowerblue',
lw=2.0,
alpha=0.7,
mec='k',
mew=0.75)
plt.xlabel("$x$ ($\mu$m)")
plt.ylabel("Potential energy (eV)")
plt.title("%s = %.2f V" %
(electrode_names[swept_electrode_idx],
coefficients[swept_electrode_idx]))
#plt.ylim(np.min(CMS.V(x_plot, 0)), )
common.save_figure(fig,
save_path=os.path.join(
data_path, "2D slice"))
plt.close(fig)
k += 1
noof_electrons.append(N_electrons)
# Here we plot the scaled cavity frequency shift vs. the resonator voltage.
# fig6 = plt.figure(figsize=(6., 4.))
# plt.plot(Vres, scaled_cavity_frequency / 1E9, 'o', **common.plot_opt('red', msize=4))
# plt.ylabel("Scaled cavity frequency $\omega_0/2\pi$ (GHz)")
# plt.xlabel("Resonator voltage (V)")
# if save:
# common.save_figure(fig6, save_path=os.path.join(save_path, sub_dir))
color.cycle_cmap(len(sub_dirs), cmap=plt.cm.Spectral)
fig = plt.figure(figsize=(8., 4.))
common.configure_axes(12)
for r in range(len(sub_dirs)):
plt.plot(Vres,
expt_frequency[r, :] / 1E9,
'.-',
label="N = %d" % noof_electrons[r])
plt.ylabel("Scaled cavity frequency $\omega_0/2\pi$ (GHz)")
plt.xlabel("Resonator voltage (V)")
plt.ylim(7.95, 8.0)
plt.legend(loc=0, prop={'size': 10})
if save:
common.save_figure(fig, save_path=os.path.join(save_path, sub_dirs[-1]))
plt.show()
