diferencias con b vs k

analisis/plots/20220615_CPTvariandocompensacion/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
+#from EITfit.MM_eightLevel_2repumps_python_scripts import CPTspectrum8levels
 import random
 from scipy.signal import savgol_filter as sf
 

analisis/plots/20220615_CPTvariandocompensacion/Data/EITfit/MM_eightLevel_2repumps_python_scripts.py

@@ -89,7 +89,7 @@ def LtempCalculus(beta, drivefreq, forma=1):
     
     ampg=beta*drivefreq
     ampr=beta*drivefreq*(397/866)  
-    #print('fixed')
+    print('fixed')
     Hint[0,0] = ampg
     Hint[1,1] = ampg
     Hint[4,4] = ampr

analisis/plots/20230421_CPTconmicromocion/CPT_plotter_20230421.py

@@ -110,7 +110,7 @@ plt.errorbar([2*f*1e-6 for f in Freqs_merged], Counts_merged, yerr=np.sqrt(np.ar
 
 
 #%%
-#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
 
 """

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

@@ -6,6 +6,9 @@ Created on Thu Jul  2 16:30:09 2020
 @author: oem
 """
 
+"""
+ESTE ES EL CODIGO QUE PLOTEA CPT CON MICROMOCION BIEN
+"""
 
 import os
 import numpy as np

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

@@ -6,6 +6,10 @@ Created on Tue Apr  7 22:30:01 2020
 @author: nico
 """
 
+"""
+ESTE ES EL CODIGO QUE PLOTEA CPT CON MICROMOCION BIEN
+"""
+
 #ESTE CODIGO ES EL PRINCIPAL PARA PLOTEAR CPT TEORICOS
 import numpy as np
 import time
@@ -90,7 +94,6 @@ def LtempCalculus(beta, drivefreq, forma=1):
     ampg=beta*drivefreq
     ampr=beta*drivefreq*(397/866)        
     #ampr=beta*drivefreq
-    
     Hint[0,0] = ampg
     Hint[1,1] = ampg
     Hint[4,4] = ampr
@@ -228,9 +231,13 @@ def dopplerBroadening(wlg, wlp, alpha, T, mcalcio = 6.655e-23*1e-3):
     que forman ambos láseres.
     """
     
-    kboltzmann = 1.38e-23 #J/K
+    kboltzmann = 1.380649e-23 #J/K
     
-    gammaD = (2*np.pi)*np.sqrt((1/(wlg*wlg)) + (1/(wlp*wlp)) - 2*(1/(wlg*wlp))*np.cos(alpha))*np.sqrt(kboltzmann*T/(2*mcalcio))
+    gammaD = 2*np.pi*np.sqrt((1/(wlg*wlg)) + (1/(wlp*wlp)) - 2*(1/(wlg*wlp))*np.cos(alpha))*np.sqrt(kboltzmann*T/(mcalcio))
+    
+    #gammaD = 2*np.sqrt((1/(wlg*wlg)) + (1/(wlp*wlp)) - 2*(1/(wlg*wlp))*np.cos(alpha))*np.sqrt(kboltzmann*T/(1*mcalcio))
+
+    #print('tuk')
 
     return gammaD
     
@@ -245,9 +252,9 @@ def FullL_MM(rabG, rabP, gPS = 0, gPD = 0, Detg = 0, Detp = 0, u = 0, lwg = 0, l
     
     
     db = dopplerBroadening(0.397e-6, 0.866e-6, alpha, T)
-    
-    lwg = np.sqrt(lwg**2 + db**2)
-    lwp = np.sqrt(lwp**2 + db**2)    
+
+    lwg = np.sqrt(lwg**2 + (0.83*db)**2)
+    lwp = np.sqrt(lwp**2 + (0.17*db)**2)    
     
     CC = EffectiveL(gPS, gPD, lwg, lwp)
     
@@ -283,7 +290,7 @@ def FullL_MM(rabG, rabP, gPS = 0, gPD = 0, Detg = 0, Detp = 0, u = 0, lwg = 0, l
     L0 = np.array(np.matrix(Lfullpartial) + M)
     
     #ESTA PARTE ES CUANDO AGREGAS MICROMOCION
-    nmax = 3
+    nmax = 5
     
     #print(nmax)
     Ltemp, Omega = LtempCalculus(beta, drivefreq)
@@ -324,7 +331,7 @@ def CPTspectrum8levels_MM(sg, sp, gPS, gPD, Detg, u, lwg, lwp, Temp, alpha, phid
     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
+    lwg, lwp = 2*np.pi*lwg*1e6, 2*np.pi*lwp*1e6
 
     rabG = sg*gPS
     rabP = sp*gPD

analisis/plots/20230920_CPT_TemperatureSens_v2/CPT_plotter_20230920.py

@@ -110,7 +110,7 @@ plt.xlabel('Frecuencia (MHz)')
 plt.ylabel('counts')
 plt.grid()
 plt.legend()
-
+plt.savefig('Ejemplo_CPT_temperaturas_distintas.png')
 #%%
 from EITfit.threeLevel_2repumps_AnalysisFunctions import CalculoTeoricoDarkResonances_8levels, GetMinimaInfo, GetPlotsofFluovsAngle_8levels, PerformExperiment_8levels, FindDRFrequencies, FindRelativeFluorescencesOfDR, GenerateNoisyCPT, SmoothNoisyCPT, GetFinalMaps, GenerateNoisyCPT_fixedRabi, GenerateNoisyCPT_fit
 from EITfit.threeLevel_2repumps_AnalysisFunctions import MeasureRelativeFluorescenceFromCPT, IdentifyPolarizationCoincidences, RetrieveAbsoluteCoincidencesBetweenMaps, GetClosestIndex

analisis/plots/20230920_CPT_TemperatureSens_v2/Data/EITfit/MM_eightLevel_2repumps_AnalysisFunctions.py

@@ -17,20 +17,82 @@ from MM_eightLevel_2repumps_python_scripts import CPTspectrum8levels,CPTspectrum
 from scipy.optimize import curve_fit
 import random
 from scipy.signal import savgol_filter as sf
+from scipy.stats import norm
+                             
 
+def prob_energia(E,T):
+    kboltz = 1.380649e-23
+    mcalcio = 6.655e-23*1e-3
+    prob =  np.exp(-E/(kboltz*T)) #*E**2 
+    return prob
 
-def PerformExperiment_8levels(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobe, beta, drivefreq, freqMin, freqMax, freqStep, circularityprobe=1, plot=False, solvemode=1, detpvec=None):
+
+
+
+def PerformExperiment_8levels(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobe, betag, betap, drivefreq, freqMin, freqMax, freqStep, circularityprobe=1, plot=False, solvemode=1, detpvec=None, dephasing  = False, boltzmann = False):
     """
     solvemode=1: resuelve con np.linalg.solve
     solvemode=2: resuelve invirtiendo L con la funcion np.linalg.inv
     """
-    tinicial = time.time()
-    ProbeDetuningVectorL, Fluovector = CPTspectrum8levels(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()
+    kboltz = 1.380649e-23
+    m = 6.6551079e-26
+    kg = np.pi * 2/397 *1e9
+    kp = np.pi * 2/866 *1e9
+    if detpvec is None:
+        detpvec = np.arange(freqMin,freqMax,freqStep)    
+
+    if boltzmann == True:
+        FluorescencesVel = []
+        sigmaT = np.sqrt(kboltz*T/m)
+        
+        velvec = np.linspace(-4*sigmaT,4*sigmaT,100)
+        MBprobVec = norm.pdf(velvec,loc = 0, scale = sigmaT)
+        MBprobVec = MBprobVec/np.trapz(MBprobVec,velvec)
+        for i in range(len(velvec)):
+            detVel = detpvec - kp*velvec[i]/(2*np.pi*1e6)
+            _, Fluorescence = CPTspectrum8levels( sg, sp, gPS, gPD, DetDoppler-kg*velvec[i]/(2*np.pi*1e6),u, DopplerLaserLinewidth, ProbeLaserLinewidth, 0,alpha, phidoppler, titadoppler, phiprobe, titaprobe,circularityprobe, betag, betap, drivefreq, freqMin=freqMin, freqMax=freqMax, freqStep=freqStep, plot=False,detpvec=detVel)
+            
+            FluorescencesVel.append(Fluorescence)    
+        FluorescencesVel = np.array(FluorescencesVel)
+        MBprobMat = np.tile(MBprobVec,(FluorescencesVel.shape[1],1)).T
+        Fluorescence = np.trapz(FluorescencesVel*MBprobMat,velvec,axis = 0)
+        ProbeDetuningVectorL = np.arange(freqMin,freqMax,freqStep)
+
+    elif dephasing == True:  
+        tinicial = time.time()
+        ProbeDetuningVectorL, Fluorescence = CPTspectrum8levels(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobe, circularityprobe, betag, betap, drivefreq, freqMin=freqMin, freqMax=freqMax, freqStep=freqStep, detpvec = detpvec, plot=False, solvemode=1)
+        tfinal = time.time()
+        
+
+    else:
+        drivefreq =2*np.pi* 0.6e6
+        FluorescencesVel = []
+        sigmaT = np.sqrt(T*kboltz/m)
+        velvec = np.linspace(-4*sigmaT,4*sigmaT,100)
+        MBprobVec = norm.pdf(velvec,loc = 0, scale = sigmaT)
+        
+        Evec = np.linspace(0,8*kboltz*T,100)
+        velvec = np.zeros(2*len(Evec)) 
+        velvec= np.sqrt(2 * Evec/m)
+        
+        MBprobVec = prob_energia(Evec, T)
+        MBprobVec = MBprobVec/np.trapz(MBprobVec,Evec)
+        
+        betagVec = velvec*kg/drivefreq
+        betapVec = velvec*kp/drivefreq
+        for i in range(len(betagVec)): 
+            betag,betap = betagVec[i],betapVec[i]
+                                                         
+            Frequencies, Fluorescence = CPTspectrum8levels( sg, sp, gPS, gPD, DetDoppler,u, DopplerLaserLinewidth, ProbeLaserLinewidth, 0,alpha, phidoppler, titadoppler, phiprobe, titaprobe,circularityprobe, betag, betap, drivefreq, freqMin=freqMin, freqMax=freqMax, freqStep=freqStep, plot=False,detpvec=detpvec)
+            FluorescencesVel.append(Fluorescence)
+        FluorescencesVel = np.array(FluorescencesVel)
+        MBprobMat = np.tile(MBprobVec,(FluorescencesVel.shape[1],1)).T
+        Fluorescence = np.trapz(FluorescencesVel*MBprobMat,Evec,axis = 0)
+        ProbeDetuningVectorL = Frequencies
     
     #print('Done, Total time: ', round((tfinal-tinicial), 2), "s")   
           
-    return ProbeDetuningVectorL, Fluovector
+    return ProbeDetuningVectorL, Fluorescence
 
 def PerformExperiment_8levels_vel(velvect,titavect,phivect,velprob,sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobe, beta, drivefreq, freqMin, freqMax, freqStep, circularityprobe=1, plot=False, solvemode=1, detpvec=None):
     """
@@ -63,15 +125,25 @@ def SmoothNoisyCPT(Fluo, window=11, poly=3):
 
 
 
-def fitCPT_8levels_db(Freq,Fluo,sg,sp,gPS,gPD,DetDoppler,u,DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobe,beta, drivefreq, freqMin, freqMax, freqStep, circularityprobe=1, plot=False):
-
-    def SpectrumForFit(Freq,sg,sp,T,DetDoppler):
-        freq,spectra = PerformExperiment_8levels(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobe, beta, drivefreq, freqMin, freqMax, freqStep, circularityprobe=1, plot=False, solvemode=1, detpvec=None)
-        return spectra
+def fitCPT_8levels(Freq,Fluo,sg,sp,gPS,gPD,DetDoppler,u,DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobe,betag,betar, drivefreq, freqMin, freqMax, freqStep, circularityprobe=1, plot=False,dephasing = False, boltzmann = False ):
+    
+    def SpectrumForFit(Freq,sg,sp,T,DetDoppler,A,bgnd,f0):
+        Freq = Freq - f0
+        freq,spectra = PerformExperiment_8levels(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobe, betag,betar, drivefreq, freqMin, freqMax, freqStep,circularityprobe=1, plot=False, detpvec=Freq, dephasing  = dephasing, boltzmann = boltzmann)
+        return spectra*A + bgnd
 
     
-    popt,pcov = curve_fit(SpectrumForFit,Freq,Fluo,p0 = [sg,sp,T,DetDoppler],bounds = ([0.01,0.01,0.00001,-50e6],[1,20,1,30e6]))
+    popt,pcov = curve_fit(SpectrumForFit,Freq,Fluo,p0 = [sg,sp,T,DetDoppler,20000,800,432],bounds = ([0.1,1,0.5e-3,-30,10000,0,420],[0.8,10,10e-3,0,100000,1000,500]))
     fitted_spectra = SpectrumForFit(Freq,*popt)
     return Freq, fitted_spectra,popt,pcov
 
 
+def try_fitCPT_8levels(A,bgnd,f0,Freq,Fluo,sg,sp,gPS,gPD,DetDoppler,u,DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobe,betag,betar, drivefreq, freqMin, freqMax, freqStep, circularityprobe=1, plot=False,dephasing = False, boltzmann = False ):
+    def SpectrumForFit(Freq,sg,sp,T,DetDoppler,A,bgnd,f0):
+        Freq = Freq - f0
+        freq,spectra = PerformExperiment_8levels(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobe, betag,betar, drivefreq, freqMin, freqMax, freqStep,circularityprobe=1, plot=False, detpvec=Freq, dephasing  = dephasing, boltzmann = boltzmann)
+        return spectra*A + bgnd
+    return SpectrumForFit(Freq, sg, sp, T, DetDoppler, A, bgnd, f0)
+    
+    
+    
\ No newline at end of file

analisis/plots/20230920_CPT_TemperatureSens_v2/Data/EITfit/MM_eightLevel_2repumps_python_scripts.py

@@ -105,12 +105,12 @@ def HImatrix(rabG, rabP, phidoppler, titadoppler, phiprobe, titaprobe, circulari
     return HI
 
 
-def LtempCalculus(beta, drivefreq, forma=1):
+def LtempCalculus(betag,betap, drivefreq, forma=1):
     Hint = np.zeros((8, 8), dtype=np.complex_)
     
-    ampg=beta*drivefreq
-    ampr=beta*drivefreq        
-    
+    ampg=betag*drivefreq
+    ampr=betap*drivefreq        
+
     Hint[0,0] = ampg
     Hint[1,1] = ampg
     Hint[4,4] = ampr
@@ -250,13 +250,13 @@ def dopplerBroadening(wlg, wlp, alpha, T, mcalcio = 6.655e-23*1e-3):
     
     kboltzmann = 1.38e-23 #J/K
     
-    gammaD = (2*np.pi)*np.sqrt((1/(wlg*wlg)) + (1/(wlp*wlp)) - 2*(1/(wlg*wlp))*np.cos(alpha))*np.sqrt(kboltzmann*T/(2*mcalcio))
+    gammaD = (2*np.pi)*np.sqrt((1/(wlg*wlg)) + (1/(wlp*wlp)) - 2*(1/(wlg*wlp))*np.cos(alpha))*np.sqrt(kboltzmann*T/(mcalcio))
 
     return gammaD
     
 
 def FullL(rabG, rabP, gPS = 0, gPD = 0, Detg = 0, Detp = 0, u = 0, lwg = 0, lwp = 0, 
-          phidoppler=0, titadoppler=0, phiprobe=0, titaprobe=0, beta=0, drivefreq=2*np.pi*22.135*1e6, T = 0, alpha = 0, circularityprobe=1):
+          phidoppler=0, titadoppler=0, phiprobe=0, titaprobe=0, betag=0,betap = 0, drivefreq=2*np.pi*22.135*1e6, T = 0, alpha = 0, circularityprobe=1):
 
     """
     Calcula el Liouvilliano total de manera explícita índice a índice. Suma aparte las componentes de las matrices M.
@@ -264,11 +264,17 @@ def FullL(rabG, rabP, gPS = 0, gPD = 0, Detg = 0, Detp = 0, u = 0, lwg = 0, lwp
     """
     
     
-    db = dopplerBroadening(0.397e-6, 0.866e-6, alpha, T)
+    kg = 397e9
+    kp = 866e9
+    
+    fg = kg**2/(kg**2+kp**2)
+    fp = kp**2/(kg**2+kp**2)
     
-    lwg = np.sqrt(lwg**2 + (db/2)**2)/2
-    lwp = np.sqrt(lwp**2 + (db/2)**2)/2    
+    db = dopplerBroadening(0.397e-6, 0.866e-6, alpha, T)
     
+    lwg = np.sqrt(lwg**2 + (fg*db)**2)
+    lwp = np.sqrt(lwp**2 + (fp*db)**2)    
+
 
     
 
@@ -306,15 +312,18 @@ def FullL(rabG, rabP, gPS = 0, gPD = 0, Detg = 0, Detp = 0, u = 0, lwg = 0, lwp
     M = CalculateSingleMmatrix(gPS, gPD, lwg, lwp) 
     L0 = np.array(np.matrix(Lfullpartial) + M)
     
-    #ESTA PARTE ES CUANDO AGREGAS MICROMOCION
-    nmax = 7
-    #print(nmax)
-    Ltemp, Omega = LtempCalculus(beta, drivefreq)
-    #print(factor)
-    L1 = GetL1(Ltemp, L0, Omega, nmax)
-    Lfull = L0 + L1 #ESA CORRECCION ESTA EN L1
-    #HASTA ACA
     
+    if betag !=0 and betap !=0:
+        #ESTA PARTE ES CUANDO AGREGAS MICROMOCION
+        nmax = 2*int(betag)
+        #print(nmax)
+        Ltemp, Omega = LtempCalculus(betag,betap, drivefreq)
+        #print(factor)
+        L1 = GetL1(Ltemp, L0, Omega, nmax)
+        Lfull = L0 + L1 #ESA CORRECCION ESTA EN L1
+        #HASTA ACA
+    else:
+        Lfull = L0
     #NORMALIZACION DE RHO
     i = 0 
     while i < 64:
@@ -334,8 +343,6 @@ def FullLvel(vel,tita,phi,rabG, rabP, gPS = 0, gPD = 0, Detg = 0, Detp = 0, u =
     Calcula el Liouvilliano total de manera explícita índice a índice. Suma aparte las componentes de las matrices M.
     Es la más eficiente hasta ahora.
     """
-    
-    
 
 
     db = dopplerBroadening(0.397e-6, 0.866e-6, alpha, T)
@@ -406,7 +413,7 @@ Scripts para correr un experimento y hacer el análisis de los datos
 """
 
 
-def CPTspectrum8levels(sg, sp, gPS, gPD, Detg, u, lwg, lwp, Temp, alpha, phidoppler, titadoppler, phiprobe, titaprobe, Circularityprobe, beta, drivefreq, freqMin=-100, freqMax=100, freqStep=1e-1, detpvec = None,plot=False, solvemode=1):
+def CPTspectrum8levels(sg, sp, gPS, gPD, Detg, u, lwg, lwp, Temp, alpha, phidoppler, titadoppler, phiprobe, titaprobe, Circularityprobe, betag,betap, drivefreq, freqMin=-100, freqMax=100, freqStep=1e-1, detpvec = None,plot=False, solvemode=1):
 
     """
     ESTA ES LA FUNCION QUE ESTAMOS USANDO
@@ -418,12 +425,16 @@ def CPTspectrum8levels(sg, sp, gPS, gPD, Detg, u, lwg, lwp, Temp, alpha, phidopp
     phidoppler, titadoppler = phidoppler*(np.pi/180), titadoppler*(np.pi/180) 
     phiprobe, titaprobe = phiprobe*(np.pi/180), titaprobe*(np.pi/180)
     
-    if detpvec == None:
+    if detpvec is None:
     
         DetProbeVector = 2*np.pi*np.arange(freqMin*1e6, freqMax*1e6, freqStep*1e6)
     else: 
         DetProbeVector = detpvec*1e6 * 2*np.pi
     
+    
+
+    
+   
     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
@@ -440,7 +451,7 @@ def CPTspectrum8levels(sg, sp, gPS, gPD, Detg, u, lwg, lwp, Temp, alpha, phidopp
     for Detp in DetProbeVector:
         
         
-        L = FullL(rabG, rabP, gPS, gPD, Detg, Detp, u, lwg, lwp, phidoppler, titadoppler, phiprobe, titaprobe, beta, drivefreq, Temp, alpha, Circularityprobe)
+        L = FullL(rabG, rabP, gPS, gPD, Detg, Detp, u, lwg, lwp, phidoppler, titadoppler, phiprobe, titaprobe, betag,betap, drivefreq, Temp, alpha, Circularityprobe)
         
         if solvemode == 1:
             rhovectorized = np.linalg.solve(L, np.array([int(i==0) for i in range(64)]))
@@ -464,7 +475,7 @@ def CPTspectrum8levels(sg, sp, gPS, gPD, Detg, u, lwg, lwp, Temp, alpha, phidopp
         plt.plot(DetProbeVectorMHz, [100*f for f in Fluovector], label=str(titaprobe) + 'º, T: ' + str(Temp*1e3) + ' mK')
         plt.legend()
         
-    return DetProbeVectorMHz, Fluovector
+    return DetProbeVectorMHz, np.array(Fluovector)
 
 
 def CPTspectrum8levels_vel(velvect,titavec,phivec,probvel,sg, sp, gPS, gPD, Detg, u, lwg, lwp, Temp, alpha, phidoppler, titadoppler, phiprobe, titaprobe, Circularityprobe, beta, drivefreq, freqMin=-100, freqMax=100, freqStep=1e-1, plot=False, solvemode=1):
@@ -614,7 +625,7 @@ def CPTspectrum8levels_vel(velvect,titavec,phivec,probvel,sg, sp, gPS, gPD, Detg
         plt.plot(DetProbeVectorMHz, [100*f for f in Fluovector], label=str(titaprobe) + 'º, T: ' + str(Temp*1e3) + ' mK')
         plt.legend()
         
-    return DetProbeVectorMHz, Fluovector
+    return DetProbeVectorMHz, np.array(Fluovector)
 
 
 if __name__ == "__main__":

analisis/plots/20231123_CPTconmicromocion3/Data/EITfit/MM_eightLevel_2repumps_AnalysisFunctions.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Thu Jul  2 16:30:09 2020
+
+@author: oem
+"""
+
+"""
+ESTE ES EL CODIGO QUE PLOTEA CPT CON MICROMOCION BIEN
+"""
+
+import os
+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
+import random
+from scipy.signal import savgol_filter as sf
+
+
+def PerformExperiment_8levels_MM(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobe, beta, drivefreq, freqMin, freqMax, freqStep, circularityprobe=1, plot=False, solvemode=1, detpvec=None):
+    """
+    solvemode=1: resuelve con np.linalg.solve
+    solvemode=2: resuelve invirtiendo L con la funcion np.linalg.inv
+    """
+    #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()
+    
+    #print('Done, Total time: ', round((tfinal-tinicial), 2), "s")   
+          
+    return ProbeDetuningVectorL, Fluovector
+
+
+def GenerateNoisyCPT_MM(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobeVec, kg, kr, v0, drivefreq, freqMin, freqMax, freqStep, circularityprobe=1, plot=False, solvemode=1, detpvec=None, noiseamplitude=0.001):
+    Frequencyvector, Fluovector = PerformExperiment_8levels_MM(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobeVec, kg, kr, v0, drivefreq, freqMin, freqMax, freqStep, circularityprobe, plot=False, solvemode=1, detpvec=None)
+    NoisyFluovector = [fluo+noiseamplitude*(2*random.random()-1) for fluo in Fluovector]
+    return Frequencyvector, NoisyFluovector
+
+def GenerateNoisyCPT_MM_fit(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobeVec, beta, drivefreq, freqs, circularityprobe=1, plot=False, solvemode=1, detpvec=None, noiseamplitude=0.001):
+    
+    Frequencyvector, Fluovector = PerformExperiment_8levels_MM(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobeVec, beta, drivefreq, freqs[0], freqs[-1], freqs[1]-freqs[0], circularityprobe, plot=False, solvemode=1, detpvec=None)
+    #NoisyFluovector = [fluo+noiseamplitude*(2*random.random()-1) for fluo in Fluovector]
+    return Frequencyvector, Fluovector
+
+
+def SmoothNoisyCPT(Fluo, window=11, poly=3):
+    SmoothenFluo = sf(Fluo, window, poly)
+    return SmoothenFluo
+
+
+
+
+
+

analisis/plots/20231123_CPTconmicromocion3/Data/EITfit/MM_eightLevel_2repumps_CPTPlotter.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Sep  1 17:58:39 2020
+
+@author: nico
+"""
+
+
+
+import os
+import numpy as np
+#os.chdir('/home/oem/Nextcloud/G_liaf/liaf-TrampaAnular/Código General/EIT-CPT/Buenos Aires/Experiment Simulations/CPT scripts/Eight Level 2 repumps')
+#from MM_eightLevel_2repumps_AnalysisFunctions import PerformExperiment_8levels, GenerateNoisyCPT, SmoothNoisyCPT
+import matplotlib.pyplot as plt
+import time
+#from threeLevel_2repumps_AnalysisFunctions import MeasureRelativeFluorescenceFromCPT, IdentifyPolarizationCoincidences, RetrieveAbsoluteCoincidencesBetweenMaps, GetClosestIndex
+import seaborn as sns
+
+#C:\Users\Usuario\Nextcloud\G_liaf\liaf-TrampaAnular\Código General\EIT-CPT\Buenos Aires\Experiment Simulations\CPT scripts\Eight Level 2 repumps
+
+ub = 9.27e-24 #magneton de bohr
+h = 6.63e-34 #cte de planck
+c = (ub/h)*1e-4 #en unidades de MHz/G
+
+u = 2e6 #proportional to the magnetic field of around 5 G
+
+B = (u/(2*np.pi))/c
+
+gPS, gPD, = 2*np.pi*21.58e6, 2*np.pi*1.35e6 #anchos de linea de las transiciones
+
+lw = 0. #linewidth of the lasers, 0.1 MHz are the actual linewidths of both lasers
+DopplerLaserLinewidth, ProbeLaserLinewidth = lw, lw #ancho de linea de los laseres
+
+
+TempVec = [0e-3] #Temperature vector
+alpha = 0 #angle between lasers, which is zero
+
+#Polarization angles (we can keep it fixed in 90)
+phidoppler, titadoppler = 0, 90
+titaprobe = 90
+phiprobe = 0
+
+#este es el desfasaje exp(i.phi) de la componente de la polarizacion y respecto a la x. Con 1 la polarizacion es lineal
+CircPr = 1  #this has to do with the circularity of the polarizations and since both are linear it is one
+
+#Simulation parameters
+center = -10
+span = 200
+freqMin = center-span*0.5
+freqMax = center+span*0.5
+freqStep = 2e-1
+
+noiseamplitude = 0 #i dont know what it is
+
+#parametros de saturacion de los laseres. g: doppler. p: probe (un rebombeo que scanea), r: repump (otro rebombeo fijo)
+
+"""
+Good case: sg=0.6, sp=9, DetDoppler=-15
+"""
+
+DetDoppler = -25 #nice range: -30 to 0 
+sgvec = [0.6] #nice range: 0.1 to 10 #g is for green but is the doppler
+sp = 8 #nice range: 0.1 to 20 #p is for probe but is the repump
+
+
+
+drivefreq=2*np.pi*22.135*1e6 #ignore it
+#betavec = np.arange(0,1.1,0.1) #ignore it
+betavec=[0] #ignore it
+alphavec = [0] #ignore it
+
+
+
+fig1, ax1 = plt.subplots()
+
+FrequenciesVec = []
+FluorescencesVec = []
+
+for sg in sgvec:
+    for T in TempVec:
+        for alpha in alphavec:
+            for beta in betavec:
+                Frequencies, Fluorescence = PerformExperiment_8levels(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobe,  beta, drivefreq, freqMin, freqMax, freqStep, circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
+                
+                FrequenciesVec.append(Frequencies)
+                FluorescencesVec.append(Fluorescence)
+                
+                ax1.plot(Frequencies, [100*f for f in Fluorescence], label=fr'$\alpha={int(alpha*180/np.pi)}°$')  
+                ax1.set_xlabel('Detuning Rebombeo (MHz)')
+                ax1.set_ylabel('Fluorescencia (AU)')
+                ax1.set_title(f'Sdop: {sg}, Spr: {sp}, Temp: {int(T*1e3)} mK')
+                #ax1.legend()
+ax1.grid()
+
+#%%
+import seaborn as sns
+
+paleta=sns.color_palette('mako')
+
+plt.figure()
+plt.plot(Frequencies, [100*f for f in Fluorescence], color=paleta[1], linewidth=3)  
+plt.grid()
+plt.axvline(-25,color=paleta[2], linestyle='dashed')
+plt.xlabel(r'$\Delta_2$ (MHz)', fontsize=25, fontname='STIXgeneral')
+plt.ylabel('Fluorescence', fontsize=18, fontname='STIXgeneral')
+#%%
+#Este bloque ajusta a las curvas con un beta de micromocion de 0
+
+from scipy.optimize import curve_fit
+
+def FitEIT_MM(freqs, Temp):
+    BETA = 0
+    scale=1
+    offset=0
+    Detunings, Fluorescence = PerformExperiment_8levels(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, Temp, alpha, phidoppler, titadoppler, phiprobe, titaprobe,  BETA, drivefreq, freqMin, freqMax, freqStep, circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
+    ScaledFluo = [f*scale + offset for f in Fluorescence]
+    return ScaledFluo
+
+TempMedidas = []
+FittedEIT_fluosVec = []
+
+for j in range(len(betavec)):
+    SelectedFluo = FluorescencesVec[j]
+    SelectedFreqs = FrequenciesVec[j]
+    
+    popt_mm, pcov_mm = curve_fit(FitEIT_MM, SelectedFreqs, SelectedFluo, p0=[1e-3], bounds=((0), (10e-3)))
+    
+    TempMedidas.append(1e3*popt_mm[2])
+    
+    print(popt_mm)
+    
+    FittedEIT_fluo = FitEIT_MM(SelectedFreqs, *popt_mm)
+    
+    FittedEIT_fluosVec.append(FittedEIT_fluo)
+    
+    plt.figure()
+    plt.plot(SelectedFreqs, SelectedFluo, 'o')
+    plt.plot(SelectedFreqs, FittedEIT_fluo)
+
+plt.figure()
+for i in range(len(FluorescencesVec)):
+    plt.plot(SelectedFreqs, FluorescencesVec[i], 'o', markersize=3)
+    plt.plot(SelectedFreqs, FittedEIT_fluosVec[i])    
+
+
+plt.figure()
+plt.plot(betavec, TempMedidas, 'o', markersize=10)
+plt.xlabel('Beta')
+plt.ylabel('Temperatura medida (mK)')
+plt.axhline(T*1e3, label='Temperatura real', linestyle='--', color='red')
+plt.legend()
+plt.grid()
\ No newline at end of file

analisis/plots/20231123_CPTconmicromocion3/Data/EITfit/threeLevel_2repumps_CPTPlotter.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Sep  1 17:58:39 2020
+
+@author: oem
+"""
+
+
+
+import os
+import numpy as np
+#os.chdir('/home/oem/Nextcloud/G_liaf/liaf-TrampaAnular/Código General/EIT-CPT/Buenos Aires/Experiment Simulations/CPT scripts/Eight Level 2 repumps')
+from threeLevel_2repumps_AnalysisFunctions import CalculoTeoricoDarkResonances_8levels, GetMinimaInfo, GetPlotsofFluovsAngle_8levels, PerformExperiment_8levels, FindDRFrequencies, FindRelativeFluorescencesOfDR, GenerateNoisyCPT, SmoothNoisyCPT, GetFinalMaps, GenerateNoisyCPT_fixedRabi, GenerateNoisyCPT_fit
+import matplotlib.pyplot as plt
+import time
+from threeLevel_2repumps_AnalysisFunctions import MeasureRelativeFluorescenceFromCPT, IdentifyPolarizationCoincidences, RetrieveAbsoluteCoincidencesBetweenMaps, GetClosestIndex
+
+#C:\Users\Usuario\Nextcloud\G_liaf\liaf-TrampaAnular\Código General\EIT-CPT\Buenos Aires\Experiment Simulations\CPT scripts\Eight Level 2 repumps
+
+ub = 9.27e-24
+h = 6.63e-34
+c = (ub/h)*1e-4 #en unidades de MHz/G
+
+#u = 1e6
+u = 33.5e6
+
+B = (u/(2*np.pi))/c
+
+
+#sg, sp = 0.6, 5  #parámetros de control, saturación del doppler y repump
+#rabG, rabP = sg*gPS, sp*gPD #frecuencias de rabi
+
+gPS, gPD, = 2*np.pi*21.58e6, 2*np.pi*1.35e6 #anchos de linea de las transiciones
+
+
+
+lw = 0.1
+DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth = lw, lw, lw #ancho de linea de los laseres
+
+DetDoppler = -36 #42
+DetRepumpVec = [DetDoppler+29.6]
+
+Tvec = [0.7] #temperatura en mK
+alpha = 0*(np.pi/180) #angulo entre los láseres
+
+
+phidoppler, titadoppler = 0, 90
+phirepump, titarepump = 0,  0
+phiprobe = 0
+titaprobe = 90
+
+#Calculo las resonancias oscuras teóricas
+#ResonanciasTeoricas, DRPositivas = CalculoTeoricoDarkResonances_8levels(u/(2*np.pi*1e6), titadoppler, DetDoppler, DetRepump)
+
+#Parametros de la simulacion cpt
+center = -45
+span = 80
+freqMin = center-span*0.5
+freqMax = center+span*0.5
+
+""" parametros para tener espectros coherentes
+freqMin = -56
+freqMax = 14
+"""
+freqStep = 1e-1
+
+noiseamplitude = 0
+
+RelMinMedido0Vector = []
+RelMinMedido1Vector = []
+RelMinMedido2Vector = []
+RelMinMedido3Vector = []
+RelMinMedido4Vector = []
+
+#Sr = np.arange(0, 10, 0.2)
+
+#Sg = np.arange(0.01, 1, 0.05)
+#Sp = np.arange(0.1, 6.1, 1)
+
+#Sg = [0.6**2]
+#Sp = [2.3**2]
+
+
+Sg = [1.4]
+Sp = [6]
+
+Sr = [11]
+
+
+
+
+i = 0
+
+save = False
+
+
+showFigures = True
+
+if not showFigures:
+    plt.ioff()
+else:
+    plt.ion()
+    
+fig1, ax1 = plt.subplots()
+
+offsetx = 464
+
+ax1.plot([f-offsetx for f in FreqsDR], CountsDR, 'o')
+
+run = True
+
+Scale = 730
+Offset = 600 #600 para 20k cuentas aprox
+
+MaxCoherenceValue = []
+
+for sg in Sg:
+    for sp in Sp:
+        rabG, rabP = sg*gPS, sp*gPD
+        for Ti in Tvec:
+            T = Ti*1e-3
+            for DetRepump in DetRepumpVec:
+                print(T)
+                for sr in Sr:
+                
+                    rabR = sr*gPD
+                    
+                    #MeasuredFreq, MeasuredFluo = GenerateNoisyCPT(rabG, rabR, rabP, gPS, gPD, DetDoppler, DetRepump, u, DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, [titaprobe], phirepump, titarepump, freqMin, freqMax, freqStep, plot=False, solvemode=1, detpvec=None, noiseamplitude=noiseamplitude)
+                    if run:
+                        MeasuredFreq4, MeasuredFluo4 = GenerateNoisyCPT_fixedRabi(sg, sr, sp, gPS, gPD, DetDoppler, DetRepump, u, DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, [titaprobe], phirepump, titarepump, freqMin, freqMax, freqStep, plot=False, solvemode=1, detpvec=None, noiseamplitude=noiseamplitude)
+                    
+                    #SmoothFluo = SmoothNoisyCPT(MeasuredFluo, window=9, poly=2)
+                    SmoothFluo4 = MeasuredFluo4
+                    
+                    #Scale = max(BestC)/max([100*s for s in SmoothFluo4])
+                    ax1.plot(MeasuredFreq4, [Scale*100*f + Offset for f in SmoothFluo4], label=f'Sr = {sr}')
+                    ax1.axvline(DetDoppler, linestyle='--', linewidth=1)
+                    #if sr != 0:
+                        #ax1.axvline(DetRepump, linestyle='--', linewidth=1)
+
+                    MaxCoherenceValue.append(np.max(SmoothFluo4))
+
+                    #print(titaprobe)
+                    ax1.set_xlabel('Detuning Rebombeo (MHz)')
+                    ax1.set_ylabel('Fluorescencia (AU)')
+                    ax1.set_title(f'B: {round(B, 2)} G, Sdop: {round(sg, 2)}, Sp: {round(sp, 2)}, Sr: {round(sr, 2)}, lw: {lw} MHz, T: {Ti} mK')
+                    #ax1.set_ylim(0, 8)
+                    #ax1.axvline(DetDoppler, linestyle='dashed', color='red', linewidth=1)
+                    #ax1.axvline(DetRepump, linestyle='dashed', color='black', linewidth=1)
+                    #ax1.set_title('Pol Doppler y Repump: Sigma+ Sigma-, Pol Probe: PI')
+                    #ax1.legend()
+                    ax1.grid()
+                    print (f'{i+1}/{len(Sg)*len(Sp)}')
+                    i = i + 1
+                    if save:
+                        plt.savefig(f'Mapa_plots_100k_1mk/CPT_SMSM_sdop{round(sg, 2)}_sp{round(sp, 2)}_sr{round(sr, 2)}.jpg')
+                    ax1.legend()
+                    
+"""
+plt.figure()
+plt.plot(Sr, MaxCoherenceValue, 'o')
+plt.xlabel('Sr')
+plt.ylabel('Coherence')
+"""
+
+"""
+                        
+plt.figure()
+plt.plot(MeasuredFreq, [100*f for f in SmoothFluo], color='darkred')
+plt.xlabel('Desintonía 866 (MHz)')
+plt.ylabel('Fluorescencia (A.U.)')
+plt.axvline(-30, color='darkblue', linewidth=1.2, linestyle='--')
+plt.yticks(np.arange(0.4, 1.8, 0.2))
+plt.ylim(0.5, 1.6)
+plt.grid()
+              
+
+
+plt.figure()
+plt.plot(MeasuredFreq4, [100*f for f in SmoothFluo4], color='darkred')
+plt.xlabel('Desintonía 866 (MHz)')
+plt.ylabel('Fluorescencia (A.U.)')
+plt.axvline(-30, color='darkblue', linewidth=1.2, linestyle='--')
+plt.yticks(np.arange(0.8, 2.4, 0.4))
+plt.grid()
+              
+"""
+
+
+
+
+#%%
+from scipy.optimize import curve_fit
+
+T = 0.5e-3
+
+sg = 0.7
+sp = 6
+sr = 0
+DetDoppler = -14
+DetRepump = 0
+
+FitsSp = []
+FitsOffset = []
+
+Sg = [0.87]
+
+def FitEIT(freqs, SP, offset):
+    MeasuredFreq, MeasuredFluo = GenerateNoisyCPT_fit(0.87, sr, SP, gPS, gPD, DetDoppler, DetRepump, u, DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, [titaprobe], phirepump, titarepump, freqs, plot=False, solvemode=1, detpvec=None, noiseamplitude=noiseamplitude)
+    FinalFluo = [f*43000 + 2685 for f in MeasuredFluo]
+    return FinalFluo
+
+freqs = [f-offsetx+32 for f in FreqsDR]
+freqslong = np.arange(min(freqs), max(freqs)+freqs[1]-freqs[0], 0.1*(freqs[1]-freqs[0]))
+
+popt, pcov = curve_fit(FitEIT, freqs, CountsDR, p0=[5, 700], bounds=(0, [10, 1e6]))
+
+FitsSp.append(popt[0])
+FitsOffset.append(popt[1])
+
+print(popt)
+
+FittedEIT = FitEIT(freqslong, *popt)
+
+
+plt.figure()
+plt.errorbar(freqs, CountsDR, yerr=2*np.sqrt(CountsDR), fmt='o', capsize=2, markersize=2)
+plt.plot(freqslong, FitEIT(freqslong, *popt))
+plt.title(f'Sdop: {round(popt[0], 2)}, Spr: {round(popt[1], 2)}, T: {T*1e3} mK, detDop: {DetDoppler} MHz')
+
+np.savetxt('CPT_measured.txt', np.transpose([freqs, CountsDR]))
+np.savetxt('CPT_fitted.txt', np.transpose([freqslong, FittedEIT]))

analisis/plots/20231212_Bstability/Data/EITfit/MM_eightLevel_2repumps_AnalysisFunctions.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Thu Jul  2 16:30:09 2020
+
+@author: oem
+"""
+
+"""
+ESTE ES EL CODIGO QUE PLOTEA CPT CON MICROMOCION BIEN
+"""
+
+import os
+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
+import random
+from scipy.signal import savgol_filter as sf
+
+
+def PerformExperiment_8levels_MM(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobe, beta, drivefreq, freqMin, freqMax, freqStep, circularityprobe=1, plot=False, solvemode=1, detpvec=None):
+    """
+    solvemode=1: resuelve con np.linalg.solve
+    solvemode=2: resuelve invirtiendo L con la funcion np.linalg.inv
+    """
+    #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()
+    
+    #print('Done, Total time: ', round((tfinal-tinicial), 2), "s")   
+          
+    return ProbeDetuningVectorL, Fluovector
+
+
+def GenerateNoisyCPT_MM(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobeVec, kg, kr, v0, drivefreq, freqMin, freqMax, freqStep, circularityprobe=1, plot=False, solvemode=1, detpvec=None, noiseamplitude=0.001):
+    Frequencyvector, Fluovector = PerformExperiment_8levels_MM(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobeVec, kg, kr, v0, drivefreq, freqMin, freqMax, freqStep, circularityprobe, plot=False, solvemode=1, detpvec=None)
+    NoisyFluovector = [fluo+noiseamplitude*(2*random.random()-1) for fluo in Fluovector]
+    return Frequencyvector, NoisyFluovector
+
+def GenerateNoisyCPT_MM_fit(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobeVec, beta, drivefreq, freqs, circularityprobe=1, plot=False, solvemode=1, detpvec=None, noiseamplitude=0.001):
+    
+    Frequencyvector, Fluovector = PerformExperiment_8levels_MM(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobeVec, beta, drivefreq, freqs[0], freqs[-1], freqs[1]-freqs[0], circularityprobe, plot=False, solvemode=1, detpvec=None)
+    #NoisyFluovector = [fluo+noiseamplitude*(2*random.random()-1) for fluo in Fluovector]
+    return Frequencyvector, Fluovector
+
+
+def SmoothNoisyCPT(Fluo, window=11, poly=3):
+    SmoothenFluo = sf(Fluo, window, poly)
+    return SmoothenFluo
+
+
+
+
+
+

analisis/plots/20231212_Bstability/Data/EITfit/MM_eightLevel_2repumps_CPTPlotter.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Sep  1 17:58:39 2020
+
+@author: nico
+"""
+
+
+
+import os
+import numpy as np
+#os.chdir('/home/oem/Nextcloud/G_liaf/liaf-TrampaAnular/Código General/EIT-CPT/Buenos Aires/Experiment Simulations/CPT scripts/Eight Level 2 repumps')
+#from MM_eightLevel_2repumps_AnalysisFunctions import PerformExperiment_8levels, GenerateNoisyCPT, SmoothNoisyCPT
+import matplotlib.pyplot as plt
+import time
+#from threeLevel_2repumps_AnalysisFunctions import MeasureRelativeFluorescenceFromCPT, IdentifyPolarizationCoincidences, RetrieveAbsoluteCoincidencesBetweenMaps, GetClosestIndex
+import seaborn as sns
+
+#C:\Users\Usuario\Nextcloud\G_liaf\liaf-TrampaAnular\Código General\EIT-CPT\Buenos Aires\Experiment Simulations\CPT scripts\Eight Level 2 repumps
+
+ub = 9.27e-24 #magneton de bohr
+h = 6.63e-34 #cte de planck
+c = (ub/h)*1e-4 #en unidades de MHz/G
+
+u = 2e6 #proportional to the magnetic field of around 5 G
+
+B = (u/(2*np.pi))/c
+
+gPS, gPD, = 2*np.pi*21.58e6, 2*np.pi*1.35e6 #anchos de linea de las transiciones
+
+lw = 0. #linewidth of the lasers, 0.1 MHz are the actual linewidths of both lasers
+DopplerLaserLinewidth, ProbeLaserLinewidth = lw, lw #ancho de linea de los laseres
+
+
+TempVec = [0e-3] #Temperature vector
+alpha = 0 #angle between lasers, which is zero
+
+#Polarization angles (we can keep it fixed in 90)
+phidoppler, titadoppler = 0, 90
+titaprobe = 90
+phiprobe = 0
+
+#este es el desfasaje exp(i.phi) de la componente de la polarizacion y respecto a la x. Con 1 la polarizacion es lineal
+CircPr = 1  #this has to do with the circularity of the polarizations and since both are linear it is one
+
+#Simulation parameters
+center = -10
+span = 200
+freqMin = center-span*0.5
+freqMax = center+span*0.5
+freqStep = 2e-1
+
+noiseamplitude = 0 #i dont know what it is
+
+#parametros de saturacion de los laseres. g: doppler. p: probe (un rebombeo que scanea), r: repump (otro rebombeo fijo)
+
+"""
+Good case: sg=0.6, sp=9, DetDoppler=-15
+"""
+
+DetDoppler = -25 #nice range: -30 to 0 
+sgvec = [0.6] #nice range: 0.1 to 10 #g is for green but is the doppler
+sp = 8 #nice range: 0.1 to 20 #p is for probe but is the repump
+
+
+
+drivefreq=2*np.pi*22.135*1e6 #ignore it
+#betavec = np.arange(0,1.1,0.1) #ignore it
+betavec=[0] #ignore it
+alphavec = [0] #ignore it
+
+
+
+fig1, ax1 = plt.subplots()
+
+FrequenciesVec = []
+FluorescencesVec = []
+
+for sg in sgvec:
+    for T in TempVec:
+        for alpha in alphavec:
+            for beta in betavec:
+                Frequencies, Fluorescence = PerformExperiment_8levels(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, titaprobe,  beta, drivefreq, freqMin, freqMax, freqStep, circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
+                
+                FrequenciesVec.append(Frequencies)
+                FluorescencesVec.append(Fluorescence)
+                
+                ax1.plot(Frequencies, [100*f for f in Fluorescence], label=fr'$\alpha={int(alpha*180/np.pi)}°$')  
+                ax1.set_xlabel('Detuning Rebombeo (MHz)')
+                ax1.set_ylabel('Fluorescencia (AU)')
+                ax1.set_title(f'Sdop: {sg}, Spr: {sp}, Temp: {int(T*1e3)} mK')
+                #ax1.legend()
+ax1.grid()
+
+#%%
+import seaborn as sns
+
+paleta=sns.color_palette('mako')
+
+plt.figure()
+plt.plot(Frequencies, [100*f for f in Fluorescence], color=paleta[1], linewidth=3)  
+plt.grid()
+plt.axvline(-25,color=paleta[2], linestyle='dashed')
+plt.xlabel(r'$\Delta_2$ (MHz)', fontsize=25, fontname='STIXgeneral')
+plt.ylabel('Fluorescence', fontsize=18, fontname='STIXgeneral')
+#%%
+#Este bloque ajusta a las curvas con un beta de micromocion de 0
+
+from scipy.optimize import curve_fit
+
+def FitEIT_MM(freqs, Temp):
+    BETA = 0
+    scale=1
+    offset=0
+    Detunings, Fluorescence = PerformExperiment_8levels(sg, sp, gPS, gPD, DetDoppler, u, DopplerLaserLinewidth, ProbeLaserLinewidth, Temp, alpha, phidoppler, titadoppler, phiprobe, titaprobe,  BETA, drivefreq, freqMin, freqMax, freqStep, circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
+    ScaledFluo = [f*scale + offset for f in Fluorescence]
+    return ScaledFluo
+
+TempMedidas = []
+FittedEIT_fluosVec = []
+
+for j in range(len(betavec)):
+    SelectedFluo = FluorescencesVec[j]
+    SelectedFreqs = FrequenciesVec[j]
+    
+    popt_mm, pcov_mm = curve_fit(FitEIT_MM, SelectedFreqs, SelectedFluo, p0=[1e-3], bounds=((0), (10e-3)))
+    
+    TempMedidas.append(1e3*popt_mm[2])
+    
+    print(popt_mm)
+    
+    FittedEIT_fluo = FitEIT_MM(SelectedFreqs, *popt_mm)
+    
+    FittedEIT_fluosVec.append(FittedEIT_fluo)
+    
+    plt.figure()
+    plt.plot(SelectedFreqs, SelectedFluo, 'o')
+    plt.plot(SelectedFreqs, FittedEIT_fluo)
+
+plt.figure()
+for i in range(len(FluorescencesVec)):
+    plt.plot(SelectedFreqs, FluorescencesVec[i], 'o', markersize=3)
+    plt.plot(SelectedFreqs, FittedEIT_fluosVec[i])    
+
+
+plt.figure()
+plt.plot(betavec, TempMedidas, 'o', markersize=10)
+plt.xlabel('Beta')
+plt.ylabel('Temperatura medida (mK)')
+plt.axhline(T*1e3, label='Temperatura real', linestyle='--', color='red')
+plt.legend()
+plt.grid()
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