Added function to calculate trap frequency, corrected a plotting bug.
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@ -57,10 +57,19 @@ def single_gaussian_beam_potential_harmonic_approximation(positions: "np.ndarray
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U = - depth * (1 - (2 * (positions[0,:]/waists[0])**2) - (2 * (positions[2,:]/waists[1])**2) - (0.5 * positions[1,:]**2 * np.sum(np.reciprocal(z_R(waists, wavelength)))**2))
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U = - depth * (1 - (2 * (positions[0,:]/waists[0])**2) - (2 * (positions[2,:]/waists[1])**2) - (0.5 * positions[1,:]**2 * np.sum(np.reciprocal(z_R(waists, wavelength)))**2))
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return U
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return U
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def harmonic_potential(pos, v, offset):
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def harmonic_potential(pos, v, offset, m = 164*u.u):
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U_Harmonic = ((0.5 * 164*u.u * (2 * np.pi * v*u.Hz)**2 * (pos*u.um)**2)/ac.k_B).to(u.uK) + offset*u.uK
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U_Harmonic = ((0.5 * m * (2 * np.pi * v*u.Hz)**2 * (pos*u.um)**2)/ac.k_B).to(u.uK) + offset*u.uK
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return U_Harmonic.value
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return U_Harmonic.value
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def calculateTrapFrequency(w_x, w_z, Power, Polarizability, m = 164*u.u, dir = 'x'):
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TrapDepth = trap_depth(w_x, w_z, Power, alpha=Polarizability)
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TrapFrequency = np.nan
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if dir == 'x':
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TrapFrequency = ((1/(2 * np.pi)) * np.sqrt(4 * TrapDepth / (m*w_x**2))).decompose()
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elif dir == 'z':
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TrapFrequency = ((1/(2 * np.pi)) * np.sqrt(4 * TrapDepth/ (m*w_z**2))).decompose()
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return round(TrapFrequency.value, 2)*u.Hz
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def extractTrapFrequency(Positions, TrappingPotential, TrapDepthInKelvin, axis):
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def extractTrapFrequency(Positions, TrappingPotential, TrapDepthInKelvin, axis):
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tmp_pos = Positions[axis, :]
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tmp_pos = Positions[axis, :]
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center_idx = np.where(tmp_pos == 0)[0][0]
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center_idx = np.where(tmp_pos == 0)[0][0]
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@ -107,6 +116,9 @@ def plotPotential(Positions, Powers, ComputedPotentials, axis, TrapDepthLabels):
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dv = dv / 1e3 # in kHz
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dv = dv / 1e3 # in kHz
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unit = 'kHz'
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unit = 'kHz'
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tf_label = '\u03BD = %.1f \u00B1 %.2f %s'% tuple([v,dv,unit])
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tf_label = '\u03BD = %.1f \u00B1 %.2f %s'% tuple([v,dv,unit])
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if np.size(ComputedPotentials, 0) == len(Powers):
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plt.plot(Positions[axis], ComputedPotentials[i][axis], label = 'P = ' + str(Powers[i]) + ' W; ' + TrapDepthLabels[i] + '; ' + tf_label)
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else:
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if i % 2 == 0 and j < len(Powers):
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if i % 2 == 0 and j < len(Powers):
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plt.plot(Positions[axis], ComputedPotentials[i][axis], '--',label = 'P = ' + str(Powers[j]) + ' W; ' + TrapDepthLabels[j] + '; ' + tf_label)
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plt.plot(Positions[axis], ComputedPotentials[i][axis], '--',label = 'P = ' + str(Powers[j]) + ' W; ' + TrapDepthLabels[j] + '; ' + tf_label)
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elif i % 2 != 0 and j < len(Powers):
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elif i % 2 != 0 and j < len(Powers):
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@ -129,7 +141,7 @@ def plotPotential(Positions, Powers, ComputedPotentials, axis, TrapDepthLabels):
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if __name__ == '__main__':
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if __name__ == '__main__':
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# Powers = [0.1, 0.5, 2]
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# Powers = [0.1, 0.5, 2]
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# Powers = [5, 10, 20, 30, 40]
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# Powers = [5, 20, 40]
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Powers = [40]
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Powers = [40]
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Polarizability = 184.4 # in a.u, most precise measured value of Dy polarizability
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Polarizability = 184.4 # in a.u, most precise measured value of Dy polarizability
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w_x, w_z = 34*u.um, 27.5*u.um # Beam Waists in the x and y directions
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w_x, w_z = 34*u.um, 27.5*u.um # Beam Waists in the x and y directions
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@ -143,14 +155,14 @@ if __name__ == '__main__':
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ComputedPotentials = []
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ComputedPotentials = []
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TrapDepthLabels = []
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TrapDepthLabels = []
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gravity = False
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gravity = True
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astigmatism = True
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astigmatism = True
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tilt_gravity = True
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tilt_gravity = True
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theta = 1 # in degrees
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theta = 5 # in degrees
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tilt_axis = [1, 0, 0] # lab space coordinates are rotated about x-axis in reference frame of beam
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tilt_axis = [1, 0, 0] # lab space coordinates are rotated about x-axis in reference frame of beam
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disp_foci = 1.5 * z_R(w_0 = np.asarray([30]), lamb = 1.064)[0]*u.um # difference in position of the foci along the propagation direction (Astigmatism)
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disp_foci = 3 * z_R(w_0 = np.asarray([30]), lamb = 1.064)[0]*u.um # difference in position of the foci along the propagation direction (Astigmatism)
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for p in Powers:
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for p in Powers:
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@ -214,11 +226,13 @@ if __name__ == '__main__':
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else:
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else:
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TrappingPotential = IdealTrappingPotential
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TrappingPotential = IdealTrappingPotential
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# v_x = calculateTrapFrequency(w_x, w_z, Power, Polarizability, dir = 'x')
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# v_z = calculateTrapFrequency(w_x, w_z, Power, Polarizability, dir = 'z')
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# v, dv, popt, pcov = extractTrapFrequency(Positions, TrappingPotential, TrapDepthInKelvin, axis)
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# v, dv, popt, pcov = extractTrapFrequency(Positions, TrappingPotential, TrapDepthInKelvin, axis)
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# plotHarmonicFit(Positions, TrappingPotential, TrapDepthInKelvin, axis, popt, pcov)
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# plotHarmonicFit(Positions, TrappingPotential, TrapDepthInKelvin, axis, popt, pcov)
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ComputedPotentials.append(TrappingPotential)
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ComputedPotentials.append(TrappingPotential)
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# print(np.shape(ComputedPotentials))
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ComputedPotentials = np.asarray(ComputedPotentials)
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ComputedPotentials = np.asarray(ComputedPotentials)
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plotPotential(Positions, Powers, ComputedPotentials, axis, TrapDepthLabels)
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plotPotential(Positions, Powers, ComputedPotentials, axis, TrapDepthLabels)
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