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# -*- coding: utf-8 -*-
"""
Created on Sun Nov 10 15:42:46 2024
@author: shen_t2
"""
import os
os.chdir(os.path.abspath(os.path.dirname(__file__)))
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 14})
#%%
MAIN_EXP_folder = 'C:/RE_qubit_TS/202504_CW_PLE_167Er/20250408_BalongcScan_sigma/'
os.chdir(MAIN_EXP_folder)
timestampsuffix = '_04080258.npy'
actual_counts_all = np.load('actual_counts_All_Bfields_rep0' + timestampsuffix)
raw_counts_all = np.load('actual_counts_All_Bfields_rep0' + timestampsuffix)
B_field_all = np.load('wl_scan_Bfields' + timestampsuffix)
wl_scan_all = np.load('wl_scan_x_axis_20.00_120.00_speed0.5000_CWGatedD' + timestampsuffix)
B_field_all = B_field_all.reshape(len(B_field_all), 1)
B_field_all = np.repeat(B_field_all, len(wl_scan_all), axis=1)
wl_scan_all = np.tile(wl_scan_all, (len(B_field_all), 1) )
wn_PLE_c = 6535.0997 # OK w/o precise fitting
wn_FTIR_c = 6534.356431
wn_scan_all = wl_scan_all#1e7 / wl_scan_all - wn_PLE_c + wn_FTIR_c
#%%
counts_all = raw_counts_all
counts_threshold = 2500
counts_all = actual_counts_all
counts_threshold = 40000
plt.figure(11, figsize=[9,6], dpi=100)
plt.clf()
plt.pcolormesh(B_field_all, wn_scan_all, counts_all, norm='linear',
vmin=0,
# vmax=counts_threshold, # to see satellites
cmap='RdBu')
plt.colorbar(label='Photon Counting (cps)')
# to see the full
# plt.contourf(B_field_all, wn_scan_all, counts_all,
# cmap='RdBu', levels=200)
# plt.colorbar(label='Photon Counting (cps)')
# to see satellites
# plt.contourf(B_field_all, wn_scan_all, counts_all,
# levels=np.linspace(0, counts_threshold, 201),
# cmap='RdBu',
# extend='both')
# plt.colorbar(label='Photon Counting (cps)', ticks=np.linspace(0, counts_threshold, 6))
# plt.grid()
# plt.legend(loc=1)
plt.title('Gated CW PLE @ #22, 0.01%, 167Er, 3.4 K, OD 0.5,\n 1/2 V/s, AOM, DAQ = 10 ms, sigma $E\perp c$, $B_{ext}\parallel c$')
plt.xlabel('Magnetic field (Gauss)')
plt.ylabel('Calibrated wavenumber (cm$^{-1}$)')
plt.ylabel('Piezo voltage (V)')
# plt.ylabel('Wavelength (nm)')
# plt.xlim(-100, )
# plt.ylim(6533.5, 6536.0)
plt.tight_layout()
plt.savefig( MAIN_EXP_folder + '20250408_plot_BalongcScan_sigma_167Er_full.jpg' )
plt.show()
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# -*- coding: utf-8 -*-
"""
Created on Wed Feb 5 13:08:12 2025
@author: shen_t2
"""
import os
# os.chdir(os.path.abspath(os.path.dirname(__file__)))
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 14})
from scipy import optimize
# %%
MAIN_EXP_folder = 'C:/RE_qubit_TS/202510_T1_pair/20250208_T1/'
os.chdir(MAIN_EXP_folder)
timestampsuffix = '_02081615.npy'
time_scan = np.load('detection_delay_x_axis_0-120ms' + timestampsuffix) # in [us]
time_scan *= 1e-3 # in [ms]
# raw_count_rep = np.load('raw_counts_B150Gs_rep0_exc30ms_count3ms' + timestampsuffix)
actual_count_rep = np.load('actual_counts_B150Gs_rep0_exc30ms_count3ms' + timestampsuffix)
actual_count_rep /= np.max(actual_count_rep)
# %%
def _ExpDecay(t, tau):
return np.exp(-t/tau)
(popt, pcov, infodict, mesg, ier) = optimize.curve_fit(_ExpDecay, time_scan, actual_count_rep,
# p0 = [0, 1.88, 1.94, 5.5],
full_output=True)
# (popt, pcov, infodict, mesg, ier)
# %%
plt.figure(131, figsize=[9,6], dpi=100)
plt.clf()
# plt.plot(time_scan, raw_count_rep, '.-b', label= 'raw counts' )
plt.plot(time_scan, actual_count_rep, '.-r', label='Experiment' )
plt.plot(time_scan, _ExpDecay(time_scan, *popt), '--b', label='Fitted $T_1$ = {:.2f} ms'.format(popt[0]) )
plt.grid()
plt.legend(loc=1)
plt.title('$T_1$ measurement')
plt.xlabel('Detection delay time/ms')
plt.ylabel('Actual photon counts (normalized)')
plt.tight_layout()
plt.savefig( MAIN_EXP_folder + 'fitted_T1_{:.0f}ms{:}.jpg'.format(popt[0], timestampsuffix[:-4]) )
plt.show()
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# -*- coding: utf-8 -*-
"""
Created on Wed Feb 5 13:08:12 2025
@author: shen_t2
"""
import os
# os.chdir(os.path.abspath(os.path.dirname(__file__)))
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 14})
from scipy.fftpack import fft, ifft, fftfreq
# %%
MAIN_EXP_folder = 'C:/RE_qubit_TS/202503_Pulse_echo_sample2/02_thicker_Cu_plate/61_left3_left_splitting/run21_Rabi_smallApt_1500ns_noEOM_count10ms_avg100/'
os.chdir(MAIN_EXP_folder)
timestampsuffix = '_04102217.npy'
time_scan = np.load('excitation_time_x_axis_0-0ms_Pulse_Rabi' + timestampsuffix) # in [us]
raw_count_sum = np.zeros(len(time_scan))
actual_count_sum = np.zeros(len(time_scan))
total_average = 35
for ii in range(total_average):
raw_count_rep = np.load('raw_counts_B1000Gs_rep{:d}_count10ms'.format(ii) + timestampsuffix)
raw_count_sum += raw_count_rep
actual_count_rep = np.load('actual_counts_B1000Gs_rep{:d}_count10ms'.format(ii) + timestampsuffix)
actual_count_sum += actual_count_rep
raw_count = raw_count_sum / total_average
actual_count = actual_count_sum / total_average
# %% FFT
time_step = time_scan[1] - time_scan[0] # [us]
fs = 1e6 / time_step # Hz
x, y = time_scan, actual_count
fft_x = fftfreq(len(x)) * fs
fft_y = fft(y)
# %%
plt.figure(1320, figsize=[9,6], dpi=100)
plt.clf()
plt.plot(time_scan * 1e3, raw_count, '.-b', label= 'raw counts' )
plt.plot(time_scan * 1e3, actual_count, '.-r', label='Experiment' )
plt.grid()
plt.legend(loc=2)
plt.title('Total average = {:d}'.format(total_average))
plt.xlabel('Excitation time (ns)')
plt.ylabel('Actual photon counts (cps)')
# plt.xscale('log')
plt.tight_layout()
# plt.savefig( MAIN_EXP_folder + 'plot_{:}Averaged.jpg'.format(total_average) )
plt.show()
# %%
plt.figure(1321, figsize=[9,6], dpi=100)
plt.clf()
# plt.plot(time_scan, raw_count, '.-b', label= 'raw counts' )
# plt.plot(time_scan, actual_count, '.-r', label='Experiment' )
# plt.plot(fft_x, abs(fft_y), '.-b', label='FFT')
plt.plot(fft_x[:len(fft_x)//2], abs(fft_y)[:len(fft_x)//2] / len(x) * 2, '.-r', label='FFT')
plt.grid()
plt.legend(loc=1)
# plt.title('Rabi measurement')
plt.xlabel('Frequency (Hz)')
plt.ylabel('FFT')
plt.yscale('log')
plt.tight_layout()
# plt.savefig( MAIN_EXP_folder + 'plot_FFT.jpg' )
plt.show()
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# -*- coding: utf-8 -*-
"""
Created on Wed Feb 5 13:08:12 2025
@author: shen_t2
"""
import os
# os.chdir(os.path.abspath(os.path.dirname(__file__)))
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 14})
from scipy.fftpack import fft, ifft, fftfreq
# %%
MAIN_EXP_folder = 'C:/RE_qubit_TS/202503_Pulse_echo_sample2/02_thicker_Cu_plate/19_echo_halfpi_population/run1_2us_noEOM_avg100/'
os.chdir(MAIN_EXP_folder)
timestampsuffix = '_04071904.npy'
time_scan = np.load('half_pi_x_axis_300-1500ns_Pulse_echo_halfpi' + timestampsuffix) # in [us]
raw_count_sum = np.zeros(len(time_scan))
actual_count_sum = np.zeros(len(time_scan))
total_average = 55
for ii in range(total_average):
raw_count_rep = np.load('raw_counts_B680Gs_rep{:d}_tau500ns_count3ms'.format(ii) + timestampsuffix)
raw_count_sum += raw_count_rep
actual_count_rep = np.load('actual_counts_B680Gs_rep{:d}_tau500ns_count3ms'.format(ii) + timestampsuffix)
actual_count_sum += actual_count_rep
raw_count = raw_count_sum / total_average
actual_count = actual_count_sum / total_average
# %% FFT
time_step = 1/409.6 # [us]
fs = 1e6 / time_step # Hz
x, y = time_scan, actual_count
fft_x = fftfreq(len(x)) * fs
fft_y = fft(y)
# %%
plt.figure(1330, figsize=[9,6], dpi=100)
plt.clf()
# plt.plot(time_scan, raw_count, '.-b', label= 'raw counts' )
plt.plot(time_scan, actual_count, '.-r', label='Experiment' )
plt.grid()
plt.legend(loc=1)
# plt.title('Rabi measurement')
plt.xlabel('Excitation time (us)')
plt.ylabel('Actual photon counts (cps)')
plt.tight_layout()
# plt.savefig( MAIN_EXP_folder + 'fitted_T1_{:.0f}ms{:}.jpg'.format(popt[0], timestampsuffix[:-4]) )
plt.show()
# %%
plt.figure(1331, figsize=[9,6], dpi=100)
plt.clf()
# plt.plot(time_scan, raw_count, '.-b', label= 'raw counts' )
# plt.plot(time_scan, actual_count, '.-r', label='Experiment' )
# plt.plot(fft_x, abs(fft_y), '.-b', label='FFT')
plt.plot(fft_x[:len(fft_x)//2], abs(fft_y)[:len(fft_x)//2] / len(x) * 2, '.-r', label='FFT')
plt.grid()
plt.legend(loc=1)
# plt.title('Rabi measurement')
plt.xlabel('Frequency (Hz)')
plt.ylabel('FFT')
plt.yscale('log')
plt.tight_layout()
# plt.savefig( MAIN_EXP_folder + 'fitted_T1_{:.0f}ms{:}.jpg'.format(popt[0], timestampsuffix[:-4]) )
plt.show()
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