agrego ajustes de cpt con micromotion

analisis/plots/20220526_CPTvariandoB_v2/CPT_plotter_20220520.py

@@ -591,10 +591,10 @@ plt.fill_between(FreqsDRpi_15, FiltCounts15+ErrorCounts15, FiltCounts15-ErrorCou
 
 plt.xlim(-40,30)
 plt.ylim(-0.1,1.4)
-plt.xlabel('Repump detuning (MHz)', fontsize=12, fontname='STIXgeneral')
-plt.ylabel('Normalized fluorescence', fontsize=12, fontname='STIXgeneral')
-plt.xticks([-40, -20, 0, 20], fontsize=12, fontname='STIXgeneral')
-plt.yticks([0, 0.3, 0.6, 0.9, 1.2], fontsize=12, fontname='STIXgeneral')
+plt.xlabel('IR laser detuning (MHz)', fontsize=11, fontname='STIXgeneral')
+plt.ylabel('Normalized fluorescence', fontsize=11, fontname='STIXgeneral')
+plt.xticks([-40, -20, 0, 20], fontsize=11, fontname='STIXgeneral')
+plt.yticks([0, 0.3, 0.6, 0.9, 1.2], fontsize=11, fontname='STIXgeneral')
 visible_ticks = {
    "top": False,
    "right": False
@@ -605,7 +605,7 @@ plt.tick_params(axis="y", which="both", **visible_ticks)
 plt.grid()
 plt.tight_layout()
 #plt.savefig('/home/nico/Nextcloud/G_liaf/Publicaciones/Work/2022 B vs k race/Figuras/Figuras jpg trabajadas/CPT_exp.png',dpi=500)
-#plt.savefig('/home/nico/Nextcloud/G_liaf/Publicaciones/Papers/2022 B vs K eigenbasis/Figuras_finales/Finalesfinales/Fig3_final.pdf')
+plt.savefig('/home/nico/Nextcloud/G_liaf/Publicaciones/Papers/2022 B vs K eigenbasis/Figuras_finales/Finalesfinales/Fig4_final.pdf')
 
 #%%
 from scipy.optimize import curve_fit

analisis/plots/20220615_CPTvariandocompensacion/CPT_plotter_20220615.py

@@ -8,6 +8,10 @@ from scipy.optimize import curve_fit
 import os
 from scipy import interpolate
 
+"""
+Ajustes de un espectro cpt global de dos iones.
+Ajustamos con la contribucion de dos espectros individuales y da muy bien.
+"""
 
 #/home/nico/Documents/artiq_experiments/analisis/plots/20220615_CPTvariandocompensacion/Data
 
@@ -155,6 +159,10 @@ for dr in DR:
 from scipy.optimize import curve_fit
 import time
 
+"""
+AJUSTO LA CPT DE 2 IONES CON UN MODELO EN DONDE SUMO DOS ESPECTROS CON BETAS DISTINTOS
+"""
+
 phidoppler, titadoppler = 0, 90
 phirepump, titarepump = 0,  0
 phiprobe = 0
@@ -176,9 +184,9 @@ u = 32.5e6
 
 #B = (u/(2*np.pi))/c
 
-correccion = 6
+correccion = -1
 
-offsetxpi = 440+1+correccion
+offsetxpi = 427+correccion
 DetDoppler = -11.5-correccion
 
 gPS, gPD, = 2*np.pi*21.58e6, 2*np.pi*1.35e6 
@@ -187,39 +195,182 @@ alpha = 0
 
 drivefreq = 2*np.pi*22.135*1e6
 
-FreqsDR = [2*f*1e-6-offsetxpi+14 for f in Freqs[10]]
+FreqsDR = [2*f*1e-6-offsetxpi for f in Freqs[10]]
 CountsDR = Counts[10]
 
-freqslong = np.arange(min(FreqsDR), max(FreqsDR)+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
+freqslong = np.arange(min(FreqsDR)-20, max(FreqsDR)+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
 
 CircPr = 1
 alpha = 0
 
 
 def FitEIT_MM(freqs, SG, SP, SCALE1, SCALE2, OFFSET, BETA1, BETA2):
+#def FitEIT_MM(freqs, SG, SP, SCALE1, OFFSET, BETA1):
     #BETA = 1.8
     # SG = 0.6
     # SP = 8.1
-    TEMP = 1e-3
-    Detunings, Fluorescence1 = PerformExperiment_8levels(SG, SP, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe,  BETA1, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
-    Detunings, Fluorescence2 = PerformExperiment_8levels(SG, SP, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe,  BETA2, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
+    TEMP = 0.2e-3
+    
+    Detunings, Fluorescence1 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe,  BETA1, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
+    Detunings, Fluorescence2 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe,  BETA2, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
 
     ScaledFluo1 = np.array([f*SCALE1 + OFFSET for f in Fluorescence1])
     ScaledFluo2 = np.array([f*SCALE2 + OFFSET for f in Fluorescence2])
     return ScaledFluo1+ScaledFluo2
+    #return ScaledFluo1
 
 
-popt, pcov = curve_fit(FitEIT_MM, FreqsDR, CountsDR, p0=[0.8, 8, 1e3, 1e3, 1e4, 1, 1], bounds=((0, 0, 0, 0, 0, 0, 0), (2, 15, 1e5, 1e5, 1e5, 10, 10)))
+popt_2sp, pcov_2sp = curve_fit(FitEIT_MM, FreqsDR, CountsDR, p0=[0.9, 6.2, 3.5e4, 2.9e4, 1.34e3, 3.5, 0.1], bounds=((0, 0, 0, 0, 0, 0, 0), (2, 10, 5e4, 5e4, 4e3, 10, 2)))
+#popt, pcov = curve_fit(FitEIT_MM, FreqsDR, CountsDR, p0=[0.8, 8, 4e4, 3.5e3, 0], bounds=((0, 0, 0, 0, 0), (2, 15, 1e5, 1e5, 10)))
 
 #array([7.12876797e-01, 7.92474752e+00, 4.29735308e+04, 1.74240582e+04,
        #1.53401696e+03, 1.17073206e-06, 2.53804151e+00])
-FittedEITpi = FitEIT_MM(freqslong, *popt)
+#%%
+FittedEITpi_2sp = FitEIT_MM(freqslong, *popt_2sp)
+#FittedEITpi = FitEIT_MM(freqslong, 0.8, 8, 4e4, 3.5e3, 0)
+
+beta1 = popt_2sp[5]
+beta2 = popt_2sp[6]
+
+errbeta1 = np.sqrt(pcov_2sp[5,5])
+errbeta2 = np.sqrt(pcov_2sp[6,6])
+
+"""
+Estos params dan bien poniendo beta2=0 y correccion=0 y son SG, SP, SCALE1, SCALE2, OFFSET, BETA1
+#array([9.03123248e-01, 6.25865542e+00, 3.47684055e+04, 2.92076804e+04, 1.34556420e+03, 3.55045904e+00])
+"""
+
+"""
+Ahora considerando ambos betas, con los parametros iniciales dados por los que se obtuvieron con beta2=0
+y correccion=0 dan estos parametros que son los de antes pero con BETA2 incluido:
+array([8.52685426e-01, 7.42939084e+00, 3.61998310e+04, 3.40160472e+04, 8.62651715e+02, 3.89756335e+00, 7.64867601e-01])
+"""
+
+
+plt.figure()
+plt.errorbar(FreqsDR, CountsDR, yerr=2*np.sqrt(CountsDR), fmt='o', color='darkgreen', alpha=0.5, capsize=2, markersize=2)
+plt.plot(freqslong, FittedEITpi_2sp, color='darkgreen', linewidth=3)
+#plt.title(f'Sdop: {round(popt[0], 2)}, Spr: {round(popt[1], 2)}, T: {round(popt[2]*1e3, 2)} mK, detDop: {DetDoppler} MHz')
+plt.xlabel('Detuning (MHz)')
+plt.ylabel('Counts')
+plt.grid()
+
+#%%
+"""
+Vemos la contribucion de cada ion
+"""
+
+def SinglespectraFitEIT_MM(freqs, SG, SP, SCALE1, SCALE2, OFFSET, BETA1, BETA2):
+#def FitEIT_MM(freqs, SG, SP, SCALE1, OFFSET, BETA1):
+    #BETA = 1.8
+    # SG = 0.6
+    # SP = 8.1
+    TEMP = 0.2e-3
+    
+    Detunings, Fluorescence1 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe,  BETA1, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
+    Detunings, Fluorescence2 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe,  BETA2, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
+
+    ScaledFluo1 = np.array([f*SCALE1 + OFFSET for f in Fluorescence1])
+    ScaledFluo2 = np.array([f*SCALE2 + OFFSET for f in Fluorescence2])
+    return ScaledFluo1, ScaledFluo2
+
+
+FittedEITpi_2sp_ion1, FittedEITpi_2sp_ion2 = SinglespectraFitEIT_MM(freqslong, *popt_2sp)
+
+#%%
 
 plt.figure()
-plt.errorbar(FreqsDR, CountsDR, yerr=2*np.sqrt(CountsDR), fmt='o', capsize=2, markersize=2)
-plt.plot(freqslong, FittedEITpi)
+#plt.errorbar(FreqsDR, CountsDR, yerr=2*np.sqrt(CountsDR), fmt='o', color='darkgreen', alpha=0.5, capsize=2, markersize=2)
+plt.plot(freqslong, FittedEITpi_2sp_ion2, color='darkolivegreen', linewidth=3, label='ion 1')
+plt.plot(freqslong, FittedEITpi_2sp_ion1,  color='lawngreen', linewidth=3, label='ion 2')
 #plt.title(f'Sdop: {round(popt[0], 2)}, Spr: {round(popt[1], 2)}, T: {round(popt[2]*1e3, 2)} mK, detDop: {DetDoppler} MHz')
+plt.xlabel('Detuning (MHz)')
+plt.ylabel('Counts')
+plt.legend(loc='upper left', fontsize=20)
+plt.grid()
+
+
+#%%
+#from EITfit.MM_eightLevel_2repumps_AnalysisFunctions import PerformExperiment_8levels
+from scipy.optimize import curve_fit
+import time
+
+"""
+AHORA AJUSTO LA CPT DE 2 IONES CON UN SOLO ESPECTRO PARA VER QUE
+EFECTIVAMENTE DOS ESPECTROS SUMADOS DAN MEJOR
+"""
 
+phidoppler, titadoppler = 0, 90
+phirepump, titarepump = 0,  0
+phiprobe = 0
+titaprobe = 90
+
+Temp = 0.5e-3
+
+sg = 0.544
+sp = 4.5
+sr = 0
+DetRepump = 0
+
+
+lw = 0.1
+DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth = lw, lw, lw #ancho de linea de los laseres
+
+
+u = 32.5e6
+
+#B = (u/(2*np.pi))/c
+
+correccion = -1
+
+offsetxpi = 427+correccion
+DetDoppler = -11.5-correccion
+
+gPS, gPD, = 2*np.pi*21.58e6, 2*np.pi*1.35e6 
+alpha = 0
+
+
+drivefreq = 2*np.pi*22.135*1e6
+
+FreqsDR = [2*f*1e-6-offsetxpi for f in Freqs[10]]
+CountsDR = Counts[10]
+
+freqslong = np.arange(min(FreqsDR), max(FreqsDR)+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
+
+CircPr = 1
+alpha = 0
+
+
+def FitEIT_MM(freqs, SG, SP, SCALE1, OFFSET, BETA1):
+#def FitEIT_MM(freqs, SG, SP, SCALE1, OFFSET, BETA1):
+    #BETA = 1.8
+    # SG = 0.6
+    # SP = 8.1
+    TEMP = 0.2e-3
+    
+    Detunings, Fluorescence1 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe,  BETA1, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
+
+    ScaledFluo1 = np.array([f*SCALE1 + OFFSET for f in Fluorescence1])
+    return ScaledFluo1
+    #return ScaledFluo1
+
+
+popt_1sp, pcov_1sp = curve_fit(FitEIT_MM, FreqsDR, CountsDR, p0=[0.9, 6.2, 3e4, 1.34e3, 2], bounds=((0, 0, 0, 0, 0), (2, 10, 5e4, 5e4, 10)))
+
+#array([7.12876797e-01, 7.92474752e+00, 4.29735308e+04, 1.74240582e+04,
+       #1.53401696e+03, 1.17073206e-06, 2.53804151e+00])
+
+FittedEITpi_1sp = FitEIT_MM(freqslong, *popt_1sp)
+#FittedEITpi_1sp = FitEIT_MM(freqslong, 0.9, 6.2, 4e4, 2.9e3, 2)
+
+
+plt.figure()
+plt.errorbar(FreqsDR, CountsDR, yerr=2*np.sqrt(CountsDR), fmt='o', color='darkgreen', alpha=0.5, capsize=2, markersize=2)
+plt.plot(freqslong, FittedEITpi_1sp, color='darkgreen', linewidth=3)
+#plt.title(f'Sdop: {round(popt[0], 2)}, Spr: {round(popt[1], 2)}, T: {round(popt[2]*1e3, 2)} mK, detDop: {DetDoppler} MHz')
+plt.xlabel('Detuning (MHz)')
+plt.ylabel('Counts')
+plt.grid()
 
 
 

analisis/plots/20230421_CPTconmicromocion/CPT_plotter_20230421.py

@@ -143,7 +143,7 @@ u = 33.5e6
 
 beta = 0
 
-drivefreq = 22.135e6
+drivefreq = 2*np.pi*22.135e6
 
 correccion = 12
 
@@ -159,27 +159,44 @@ freqslongpi = np.arange(min(FreqsDRpi), max(FreqsDRpi)+FreqsDRpi[1]-FreqsDRpi[0]
 
 def FitEITpi(freqs, SG, SP, BETA, scale, offset):
     temp = 1e-3
-    MeasuredFreq, MeasuredFluo = GenerateNoisyCPT_MM_fit(SG, SP, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, temp, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA, drivefreq, freqs, plot=False, solvemode=1, detpvec=None, noiseamplitude=noiseamplitude)
+    MeasuredFreq, MeasuredFluo = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, temp, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA, drivefreq, min(freqs), max(freqs), freqs[1]-freqs[0])
+    #MeasuredFreq, MeasuredFluo = GenerateNoisyCPT_MM_fit(SG, SP, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, temp, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA, drivefreq, freqs, plot=False, solvemode=1, detpvec=None, noiseamplitude=noiseamplitude)
     #scale = 0.3*2e+04
     #offset = 0.3*2e+03
     FinalFluo = [f*scale + offset for f in MeasuredFluo]
     return FinalFluo
 
-popt_fullcpt, pcov_fullcpt = curve_fit(FitEITpi, FreqsDRpi, CountsDRpi, p0=[0.5, 4.5, 1, 1e4, 1e3], bounds=((0, 0, 0, 1e1, 0), (2, 10, 1000, 1e5, 1e5)))
+popt_fullcpt, pcov_fullcpt = curve_fit(FitEITpi, FreqsDRpi[1:], CountsDRpi, p0=[0.5, 4.5, 1, 1e4, 1e3], bounds=((0, 0, 0, 1e1, 0), (2, 10, 1000, 1e5, 1e5)))
 
 #print(f'Temperatura: ({round(1e3*popt_fullcpt[-1],2)} +- {round(1e3*np.sqrt(pcov_fullcpt[-1][-1]),2)}) mK')
 
 
 print(popt_fullcpt)
+#%%
 
-
-FittedEITpi = FitEITpi(freqslongpi, popt_fullcpt[0], popt_fullcpt[1], 20, popt_fullcpt[3],popt_fullcpt[4])
+FittedEITpi = FitEITpi(freqslongpi, popt_fullcpt[0], popt_fullcpt[1], 4, popt_fullcpt[3], popt_fullcpt[4])
 #FittedEITpi = FitEITpi(freqslongpi, *popt_fullcpt)
 
 """
 Ploteo la CPT de referencia junto al ajuste y a la resonancia oscura de interes
 I plot the reference CPT along with the fit to the model and the dark resonance of interest
 """
+
+DRs = [-26.5, -18, -11.5, -3]
+
+plt.figure()
+plt.errorbar(FreqsDRpi, Counts_merged, yerr=np.sqrt(np.array(Counts_merged)), fmt='o', capsize=2, markersize=2)
+for dr in DRs:
+    plt.axvline(dr, color='black', alpha=0.5)
+    plt.axvline(dr-22.1, color='red', alpha=0.5)
+    plt.axvline(dr+22.1, color='blue', alpha=0.2)
+
+plt.plot(freqslongpi, FittedEITpi[1:])
+
+
+#%%
+#ignorar de aca para abajo por ahora
+
 #%%
 #i_DR = 955
 

analisis/plots/20230720_EspectrosCristal2iones/Espectroscpt_cristal.py

@@ -131,4 +131,108 @@ plt.legend()
 
 
 
+#%%
+#from EITfit.MM_eightLevel_2repumps_AnalysisFunctions import PerformExperiment_8levels_MM, GenerateNoisyCPT_MM_fit
+from scipy.optimize import curve_fit
+from time import time as titi
+
+"""
+Ajusto un cpt para obtener todos los parámetros relevantes primero.
+I fit a cpt curve to retrieve all the relevant parameters first.
+"""
+
+phidoppler, titadoppler = 0, 90
+phirepump, titarepump = 0,  0
+phiprobe = 0
+titaprobe = 90
+
+gPS, gPD, = 2*np.pi*21.58e6, 2*np.pi*1.35e6 
+alpha = 0
+noiseamplitude = 0
+
+T = 0.6e-3
+
+sg = 0.544
+sp = 4.5
+sr = 0
+DetRepump = 0
+
+
+lw = 0.1
+DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth = lw, lw, lw #ancho de linea de los laseres
+
+
+u = 33.5e6
+
+beta = 0
+
+drivefreq = 2*np.pi*22.135e6
+
+correccion = 6 #probe de 1 a 12 y 6 es la mejor
+
+
+offsetxpi = 450+correccion
+#DetDoppler = -20.5   -correccion
+
+
+FreqsDRpi = [2*f*1e-6-offsetxpi for f in IR1_Freqs[0][1:]]
+CountsDRpi = CountsRois[0][1:]
+
+freqslongpi = np.arange(min(FreqsDRpi), max(FreqsDRpi)+FreqsDRpi[1]-FreqsDRpi[0], 0.1*(FreqsDRpi[1]-FreqsDRpi[0]))
+
+#[1.71811842e+04 3.34325038e-17]
+
+def FitEITpi(freqs, DetDoppler, SG, SP, temp, BETA):
+    #temp = 1e-3
+    #BETA=0
+    DetDoppler
+    MeasuredFreq, MeasuredFluo = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, temp, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA, drivefreq, min(freqs), max(freqs), freqs[1]-freqs[0])
+    scale = 2.77115328e+05
+    offset = 1.43353974e+04
+    FinalFluo = [f*scale + offset for f in MeasuredFluo]
+    return FinalFluo
+
+t1 = titi()
+popt_fullcpt, pcov_fullcpt = curve_fit(FitEITpi, FreqsDRpi, CountsDRpi, p0=[-21, 0.5, 8, 1e-3, 1], bounds=((-40, 0, 0, 0, 0), (0, 2, 20, 15e-3, 5)))
+t2 = titi()
+
+
+#print(f'Temperatura: ({round(1e3*popt_fullcpt[-1],2)} +- {round(1e3*np.sqrt(pcov_fullcpt[-1][-1]),2)}) mK')
+
+
+print('done', correccion, f', took {round(t2-t1)} seconds')
+
+#popt_fullcpt = array([1.17888250e+05, 1.92746338e+03, 6.15041437e-01, 7.41895643e+00, 1.97990392e-04, 7.14734207e-01]) #este anda bien
+
+#FittedEITpi = FitEITpi(freqslongpi, 3.4e4, 1.6e4, 0.5, 8, 1e-3, 0)
+FittedEITpi = FitEITpi(freqslongpi, *popt_fullcpt)
+
+"""
+Ploteo la CPT de referencia junto al ajuste y a la resonancia oscura de interes
+I plot the reference CPT along with the fit to the model and the dark resonance of interest
+"""
+
+
+
+#i_DR = 955
+
+DRs = [-42.5, -33.5, -27, -19]
+
+plt.figure()
+plt.errorbar(FreqsDRpi, CountsDRpi, yerr=0.1*np.sqrt(CountsDRpi), color='purple', alpha=0.6, fmt='o', capsize=2, markersize=2)
+plt.plot(freqslongpi, FittedEITpi[1:], linewidth=2, color='purple')
+# for dr in DRs:
+#     dr = dr
+#     plt.axvline(dr, color='black',alpha=0.5)
+#     plt.axvline(dr+22.135, color='blue',alpha=0.3)
+#     plt.axvline(dr-22.135, color='red',alpha=0.3)
+#plt.axvline(DetDoppler-22.135)
+#plt.axvline(DetDoppler+22.135)
+#plt.plot(freqslongpi[i_DR], FittedEITpi[i_DR],'o', color='red', markersize=12)
+plt.xlabel('Detuning (MHz)', fontsize=15)
+plt.ylabel('Counts', fontsize=15)
+plt.grid()
+#plt.title(f'correccion: {correccion}')
+#plt.title(f'Sdop: {round(popt[0], 2)}, Spr: {round(popt[1], 2)}, T: {round(popt[2]*1e3, 2)} mK, detDop: {DetDoppler} MHz')
+
 

analisis/plots/20230906_CPTconmicromocion2/CPT_plotter_20230906.py

@@ -12,7 +12,7 @@ from scipy import interpolate
 
 #C:\Users\Usuario\Documents\artiq\artiq_experiments\analisis\plots\20220106_CPT_DosLaseres_v08_TISA_DR\Data
 
-#os.chdir('/home/nico/Documents/artiq_experiments/analisis/plots/20230421_CPTconmicromocion/Data/')
+os.chdir('/home/nico/Documents/artiq_experiments/analisis/plots/20230906_CPTconmicromocion2/Data/')
 
 CPT_FILES = """000015243-IR_Scan_withcal_optimized
 """ 
@@ -73,14 +73,15 @@ plt.ylabel('counts')
 plt.grid()
 for dr in drs:
     plt.axvline(dr)
-    plt.axvline(dr+drive)
+    #plt.axvline(dr+drive)
 plt.legend()
 
 
 
 #%%
-from EITfit.MM_eightLevel_2repumps_AnalysisFunctions import PerformExperiment_8levels_MM, GenerateNoisyCPT_MM_fit
+#from EITfit.MM_eightLevel_2repumps_AnalysisFunctions import PerformExperiment_8levels_MM, GenerateNoisyCPT_MM_fit
 from scipy.optimize import curve_fit
+from time import time as titi
 
 """
 Ajusto un cpt para obtener todos los parámetros relevantes primero.
@@ -112,11 +113,20 @@ u = 33.5e6
 
 beta = 0
 
-drivefreq = 22.135e6
+drivefreq = 2*np.pi*22.135e6
 
-correccion = -12
+correccion = 6 #probe de 1 a 12 y 6 es la mejor
 
-offsetxpi = 458+correccion
+
+SGs = []
+SPs = []
+Temps = []
+Betas = []
+Scales = []
+Offsets = []
+ErrorBetas = []
+
+offsetxpi = 423+correccion
 DetDoppler = -20.5   -correccion
 
 FreqsDRpi = [2*f*1e-6-offsetxpi for f in Freqs[0]]
@@ -126,49 +136,64 @@ freqslongpi = np.arange(min(FreqsDRpi), max(FreqsDRpi)+FreqsDRpi[1]-FreqsDRpi[0]
 
 #[1.71811842e+04 3.34325038e-17]
 
-def FitEITpi(freqs, SG, SP, scale, offset):
-    temp = 1e-3
-    BETA=0
+def FitEITpi(freqs, scale, offset, SG, SP, temp, BETA):
+    #temp = 1e-3
+    #BETA=0
     MeasuredFreq, MeasuredFluo = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, temp, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA, drivefreq, min(freqs), max(freqs), freqs[1]-freqs[0])
-    #scale = 0.3*2e+04
-    #offset = 0.3*2e+03
+    # scale = 5.69952745e+04
+    # offset = 2.91686628e+03
     FinalFluo = [f*scale + offset for f in MeasuredFluo]
     return FinalFluo
 
-popt_fullcpt, pcov_fullcpt = curve_fit(FitEITpi, FreqsDRpi, CountsDRpi[1:], p0=[0.5, 4.5,1e4, 4e3], bounds=((0, 0, 1e1, 0), (2, 10, 1e5, 1e5)))
+t1 = titi()
+popt_fullcpt, pcov_fullcpt = curve_fit(FitEITpi, FreqsDRpi, CountsDRpi, p0=[5e4, 3e3, 0.5, 8, 5e-3, 1], bounds=((0, 0, 0, 0, 0, 0), (1e6, 1e5, 2, 20, 15e-3, 5)))
+t2 = titi()
+
+Scales.append(popt_fullcpt[0])
+Offsets.append(popt_fullcpt[1])
+SGs.append(popt_fullcpt[2])
+SPs.append(popt_fullcpt[3])
+Temps.append(1e3*popt_fullcpt[4])
+Betas.append(popt_fullcpt[5])
+
+ErrorBetas.append(np.sqrt(pcov_fullcpt[5,5]))
 
 #print(f'Temperatura: ({round(1e3*popt_fullcpt[-1],2)} +- {round(1e3*np.sqrt(pcov_fullcpt[-1][-1]),2)}) mK')
 
 
-print(popt_fullcpt)
+print('done', correccion, f', took {round(t2-t1)} seconds')
 
+#popt_fullcpt = array([1.17888250e+05, 1.92746338e+03, 6.15041437e-01, 7.41895643e+00, 1.97990392e-04, 7.14734207e-01]) #este anda bien
 
-FittedEITpi = FitEITpi(freqslongpi, popt_fullcpt[0], popt_fullcpt[1], 20, popt_fullcpt[3],popt_fullcpt[4])
-#FittedEITpi = FitEITpi(freqslongpi, *popt_fullcpt)
+#FittedEITpi = FitEITpi(freqslongpi, 0.5, 8, 6e4, 4e3)
+FittedEITpi = FitEITpi(freqslongpi, popt_fullcpt[0], popt_fullcpt[1], popt_fullcpt[2], popt_fullcpt[3], popt_fullcpt[4], popt_fullcpt[5])
 
 """
 Ploteo la CPT de referencia junto al ajuste y a la resonancia oscura de interes
 I plot the reference CPT along with the fit to the model and the dark resonance of interest
 """
-#%%
+
+
+
 #i_DR = 955
 
-DRs = [-31, -22, -16.5, -8]
+DRs = [-42.5, -33.5, -27, -19]
 
 plt.figure()
-plt.errorbar(FreqsDRpi, CountsDRpi, yerr=2*np.sqrt(CountsDRpi), fmt='o', capsize=2, markersize=2)
-plt.plot(freqslongpi[:-1], FittedEITpi)
-for dr in DRs:
-    dr = dr+4.7
-    plt.axvline(dr, color='red',alpha=0.2)
-    plt.axvline(dr+22.1, color='green',alpha=0.2)
-    plt.axvline(dr-22.1, color='black',alpha=0.2)
-#plt.axvline(DetDoppler-22.1)
-#plt.axvline(DetDoppler+22.1)
+plt.errorbar(FreqsDRpi, CountsDRpi, yerr=2*np.sqrt(CountsDRpi), color='purple', alpha=0.6, fmt='o', capsize=2, markersize=2)
+plt.plot(freqslongpi, FittedEITpi, linewidth=2, color='purple')
+# for dr in DRs:
+#     dr = dr
+#     plt.axvline(dr, color='black',alpha=0.5)
+#     plt.axvline(dr+22.135, color='blue',alpha=0.3)
+#     plt.axvline(dr-22.135, color='red',alpha=0.3)
+#plt.axvline(DetDoppler-22.135)
+#plt.axvline(DetDoppler+22.135)
 #plt.plot(freqslongpi[i_DR], FittedEITpi[i_DR],'o', color='red', markersize=12)
-plt.xlabel('Detuning (MHz)')
-plt.ylabel('Counts')
-
+plt.xlabel('Detuning (MHz)', fontsize=15)
+plt.ylabel('Counts', fontsize=15)
+plt.grid()
+#plt.title(f'correccion: {correccion}')
 #plt.title(f'Sdop: {round(popt[0], 2)}, Spr: {round(popt[1], 2)}, T: {round(popt[2]*1e3, 2)} mK, detDop: {DetDoppler} MHz')
 
 

analisis/plots/20230906_CPTconmicromocion2/Data/EITfit/MM_eightLevel_2repumps_AnalysisFunctions.py

@@ -12,7 +12,7 @@ import numpy as np
 import time
 import matplotlib.pyplot as plt
 from scipy.signal import argrelextrema
-from EITfit.MM_eightLevel_2repumps_python_scripts import CPTspectrum8levels_MM
+#from EITfit.MM_eightLevel_2repumps_python_scripts import CPTspectrum8levels_MM
 import random
 from scipy.signal import savgol_filter as sf
 
@@ -22,9 +22,9 @@ def PerformExperiment_8levels_MM(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLi
     solvemode=1: resuelve con np.linalg.solve
     solvemode=2: resuelve invirtiendo L con la funcion np.linalg.inv
     """
-    tinicial = time.time()
+    #tinicial = time.time()
     ProbeDetuningVectorL, Fluovector = CPTspectrum8levels_MM(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobe, circularityprobe, beta, drivefreq, freqMin=freqMin, freqMax=freqMax, freqStep=freqStep, plot=False, solvemode=1)
-    tfinal = time.time()
+    #tfinal = time.time()
     
     #print('Done, Total time: ', round((tfinal-tinicial), 2), "s")   
           

analisis/plots/20230906_CPTconmicromocion2/Data/EITfit/MM_eightLevel_2repumps_python_scripts.py

@@ -88,7 +88,8 @@ def LtempCalculus(beta, drivefreq, forma=1):
     Hint = np.zeros((8, 8), dtype=np.complex_)
     
     ampg=beta*drivefreq
-    ampr=beta*drivefreq        
+    ampr=beta*drivefreq*(397/866)        
+    #ampr=beta*drivefreq
     
     Hint[0,0] = ampg
     Hint[1,1] = ampg
@@ -283,6 +284,7 @@ def FullL_MM(rabG, rabP, gPS = 0, gPD = 0, Detg = 0, Detp = 0, u = 0, lwg = 0, l
     
     #ESTA PARTE ES CUANDO AGREGAS MICROMOCION
     nmax = 3
+    
     #print(nmax)
     Ltemp, Omega = LtempCalculus(beta, drivefreq)
     #print(factor)
@@ -319,7 +321,7 @@ def CPTspectrum8levels_MM(sg, sp, gPS, gPD, Detg, u, lwg, lwp, Temp, alpha, phid
     phidoppler, titadoppler = phidoppler*(np.pi/180), titadoppler*(np.pi/180) 
     phiprobe, titaprobe = phiprobe*(np.pi/180), titaprobe*(np.pi/180)
     
-    DetProbeVector = 2*np.pi*np.arange(freqMin*1e6, freqMax*1e6, freqStep*1e6)
+    DetProbeVector = 2*np.pi*np.arange(freqMin*1e6, freqMax*1e6+0*freqStep*1e6, freqStep*1e6)
     Detg = 2*np.pi*Detg*1e6
     #lwg, lwr, lwp = 2*np.pi*lwg*1e6, 2*np.pi*lwr*1e6, 2*np.pi*lwp*1e6
     lwg, lwp = lwg*1e6, lwp*1e6
@@ -359,7 +361,7 @@ def CPTspectrum8levels_MM(sg, sp, gPS, gPD, Detg, u, lwg, lwp, Temp, alpha, phid
         
     return DetProbeVectorMHz, Fluovector
 
-
+#%%
 if __name__ == "__main__":
     ub = 9.27e-24
     h = 6.63e-34