1049 lines
41 KiB
Plaintext
1049 lines
41 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "a4246751",
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"metadata": {},
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"outputs": [],
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"source": [
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"from calculateDipoleTrapPotential import *\n",
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"%matplotlib notebook"
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]
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},
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{
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"cell_type": "markdown",
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"id": "c68468e4",
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"metadata": {},
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"source": [
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"## Plot ideal trap potential resulting for given parameters only"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "38c770ac",
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"metadata": {},
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"outputs": [],
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"source": [
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"Power = 1.07*u.W\n",
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"Wavelength = 1.064*u.um\n",
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"w_x, w_z = 30*u.um, 30*u.um # Beam Waists in the x and y directions\n",
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"\n",
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"#Power = 11*u.W\n",
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"#w_x, w_z = 67*u.um, 67*u.um # Beam Waists in the x and y directions\n",
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"\n",
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"options = {\n",
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" 'axis': 2, # axis referenced to the beam along which you want the dipole trap potential\n",
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" 'extent': 1e2, # range of spatial coordinates in one direction to calculate trap potential over\n",
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" 'crossed': False,\n",
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" 'delta': 70, # angle between arms in degrees\n",
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" 'modulation': False,\n",
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" 'aspect_ratio': 4, # required aspect ratio of modulated arm\n",
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" 'gravity': True,\n",
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" 'tilt_gravity': False,\n",
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" 'theta': 0.75, # gravity tilt angle in degrees\n",
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" 'tilt_axis': [1, 0, 0], # lab space coordinates are rotated about x-axis in reference frame of beam\n",
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" 'astigmatism': False,\n",
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" 'disp_foci': 2.5*u.mm, #0.9 * z_R(w_0 = np.asarray([30]), lamb = 1.064)[0]*u.um, # difference in position of the foci along the propagation direction (Astigmatism)\n",
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" 'extract_trap_frequencies': False\n",
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"}\n",
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"\n",
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"ComputedPotentials = [] \n",
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"Params = [] \n",
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"\n",
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"Positions, IdealTrappingPotential, TrappingPotential, TrapDepthsInKelvin, CalculatedTrapFrequencies, ExtractedTrapFrequencies = computeTrapPotential(w_x, w_z, Power, options)\n",
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"ComputedPotentials.append(IdealTrappingPotential)\n",
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"ComputedPotentials.append(TrappingPotential)\n",
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"Params.append([TrapDepthsInKelvin, CalculatedTrapFrequencies, ExtractedTrapFrequencies])\n",
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"\n",
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"cpots = np.asarray(ComputedPotentials)\n",
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"plotPotential(Positions, cpots, options, Params)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "fc9809de",
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"metadata": {},
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"source": [
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"## Plot harmonic fit for trap potential resulting for given parameters only"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0f3e80f7",
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"metadata": {},
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"outputs": [],
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"source": [
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"v, dv, popt, pcov = extractTrapFrequency(Positions, TrappingPotential, options['axis'])\n",
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"plotHarmonicFit(Positions, TrappingPotential, TrapDepthsInKelvin, options['axis'], popt, pcov)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "37b40607",
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"metadata": {},
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"source": [
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"## Plot trap potential resulting for given parameters (with one parameter being a list of values and the potential being computed for each of these values) only"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8504f99f",
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"metadata": {
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"scrolled": false
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},
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"outputs": [],
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"source": [
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"Potentials = [] \n",
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"Params = [] \n",
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"Power = [10, 30, 40]*u.W # Single Beam Power\n",
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"for p in Power: \n",
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" Positions, IdealTrappingPotential, TrappingPotential, TrapDepthsInKelvin, CalculatedTrapFrequencies, ExtractedTrapFrequencies = computeTrapPotential(w_x, w_z, p, options)\n",
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" Potentials.append(IdealTrappingPotential)\n",
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" Potentials.append(TrappingPotential)\n",
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" Params.append([TrapDepthsInKelvin, CalculatedTrapFrequencies, ExtractedTrapFrequencies])\n",
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"\n",
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"cpots = np.asarray(Potentials)\n",
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"plotPotential(Positions, cpots, options, Params)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "951010c6",
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"metadata": {},
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"source": [
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"## Plot transverse intensity profile and trap potential resulting for given parameters only"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f3e4afd9",
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"metadata": {},
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"outputs": [],
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"source": [
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"Power = 40*u.W\n",
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"Wavelength = 1.064*u.um\n",
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"w_x, w_z = 30*u.um, 30*u.um # Beam Waists in the x and y directions\n",
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"\n",
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"options = {\n",
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" 'axis': 2, # axis referenced to the beam along which you want the dipole trap potential\n",
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" 'extent': 60, # range of spatial coordinates in one direction to calculate trap potential over\n",
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" 'crossed': False,\n",
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" 'delta': 70, # angle between arms in degrees\n",
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" 'modulation': True,\n",
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" 'modulation_function': 'arccos',\n",
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" 'modulation_amplitude': 2.16,\n",
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" 'aspect_ratio': 4, # required aspect ratio of modulated arm\n",
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" 'gravity': True,\n",
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" 'tilt_gravity': False,\n",
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" 'theta': 0.75, # gravity tilt angle in degrees\n",
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" 'tilt_axis': [1, 0, 0], # lab space coordinates are rotated about x-axis in reference frame of beam\n",
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" 'astigmatism': False,\n",
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" 'disp_foci': 2.5*u.mm, #0.9 * z_R(w_0 = np.asarray([30]), lamb = 1.064)[0]*u.um, # difference in position of the foci along the propagation direction (Astigmatism)\n",
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" 'extract_trap_frequencies': False\n",
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"}\n",
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"\n",
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"positions, waists, I, U, p = computeIntensityProfileAndPotentials(Power, [w_x, w_z], Wavelength, options)\n",
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"plotIntensityProfileAndPotentials(positions, waists, I, U)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "db0df307",
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"metadata": {},
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"source": [
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"## Plot gaussian fit for trap potential resulting from modulation for given parameters only"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7afa7d82",
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"metadata": {},
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"outputs": [],
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"source": [
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"x_Positions = positions[0].value\n",
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"z_Positions = positions[1].value\n",
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"x_Potential = U[:, np.where(z_Positions==0)[0][0]].value\n",
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"z_Potential = U[np.where(x_Positions==0)[0][0], :].value\n",
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"poptx, pcovx = p[0], p[1]\n",
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"poptz, pcovz = p[2], p[3]\n",
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"plotGaussianFit(x_Positions, x_Potential, poptx, pcovx)\n",
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"plotGaussianFit(z_Positions, z_Potential, poptz, pcovz)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "5e5b8123",
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"metadata": {},
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"source": [
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"## Calculate relevant parameters for evaporative cooling"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "95ab43bd",
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"metadata": {},
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"outputs": [],
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"source": [
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"Power = 40*u.W\n",
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"Wavelength = 1.064*u.um\n",
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"w_x, w_z = 30*u.um, 30*u.um # Beam Waists in the x and y directions\n",
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"\n",
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"AtomNumber = 1.00 * 1e7\n",
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"BField = 2.5 * u.G\n",
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"\n",
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"modulation_depth = 0.0\n",
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"Temperature = convert_modulation_depth_to_temperature(modulation_depth)[0] * u.uK\n",
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"n = particleDensity(w_x, w_z, Power, N = AtomNumber, T = Temperature).decompose().to(u.cm**(-3))\n",
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"Gamma_elastic = calculateElasticCollisionRate(w_x, w_z, Power, N = AtomNumber, T = Temperature, B = BField)\n",
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"PSD = calculatePSD(w_x, w_z, Power, N = AtomNumber, T = Temperature).decompose()\n",
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"\n",
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"print('Particle Density = %.2E ' % (n.value) + str(n.unit))\n",
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"print('Elastic Collision Rate = %.2f ' % (Gamma_elastic.value) + str(Gamma_elastic.unit))\n",
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"print('PSD = %.2E ' % (PSD.value))\n",
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"\n",
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"v_x = calculateTrapFrequency(w_x, w_z, Power, dir = 'x')\n",
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"v_y = calculateTrapFrequency(w_x, w_z, Power, dir = 'y')\n",
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"v_z = calculateTrapFrequency(w_x, w_z, Power, dir = 'z')\n",
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"\n",
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"print('v_x = %.2f ' %(v_x.value) + str(v_x.unit))\n",
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"print('v_y = %.2f ' %(v_y.value) + str(v_y.unit))\n",
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"print('v_z = %.2f ' %(v_z.value) + str(v_z.unit))\n",
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"\n",
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"print('a_s = %.2f ' %(scatteringLength(BField)[0] / ac.a0))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ff252fbe",
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"metadata": {},
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"source": [
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"## Plot alphas"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "dd7fc03d",
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"metadata": {},
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"outputs": [],
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"source": [
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"plotAlphas()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "c09cb260",
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"metadata": {},
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"source": [
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"## Plot Temperatures"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "5c79840e",
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"metadata": {},
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"outputs": [],
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"source": [
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"plotTemperatures(w_x, w_z, plot_against_mod_depth = True)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "063879ee",
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"metadata": {},
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"source": [
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"## Calculate and Plot calculated trap frequencies"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0ddff726",
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"metadata": {},
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"outputs": [],
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"source": [
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"AtomNumber = 1.00 * 1e7\n",
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"BField = 1.4 * u.G\n",
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"Wavelength = 1.064*u.um\n",
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"w_x, w_z = 30*u.um, 30*u.um # Beam Waists in the x and y directions\n",
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"modulation_depth = np.arange(0, 1.0, 0.08)\n",
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"\n",
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"w_xs = w_x * convert_modulation_depth_to_alpha(modulation_depth)[0]\n",
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"new_aspect_ratio = w_xs / w_z\n",
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"\n",
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"v_x = np.zeros(len(modulation_depth))\n",
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"v_y = np.zeros(len(modulation_depth))\n",
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"v_z = np.zeros(len(modulation_depth))\n",
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"\n",
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"for i in range(len(modulation_depth)):\n",
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" v_x[i] = calculateTrapFrequency(w_xs[i], w_z, Power, dir = 'x').value\n",
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" v_y[i] = calculateTrapFrequency(w_xs[i], w_z, Power, dir = 'y').value\n",
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" v_z[i] = calculateTrapFrequency(w_xs[i], w_z, Power, dir = 'z').value\n",
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"\n",
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"plotTrapFrequencies(v_x, v_y, v_z, modulation_depth, new_aspect_ratio, plot_against_mod_depth = True)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "76ff8301",
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"metadata": {},
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"source": [
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"## Plot measured trap frequencies"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7a85ec41",
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"metadata": {},
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"outputs": [],
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"source": [
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"modulation_depth_radial = [0, 0.5, 0.3, 0.7, 0.9, 0.8, 1.0, 0.6, 0.4, 0.2, 0.1]\n",
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"fx = [3.135, 0.28, 0.690, 0.152, 0.102, 0.127, 0.099, 0.205, 0.404, 1.441, 2.813]\n",
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"dfx = [0.016, 0.006, 0.005, 0.006, 0.003, 0.002, 0.002,0.002, 0.003, 0.006, 0.024]\n",
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"fz = [2.746, 1.278, 1.719, 1.058, 0.923, 0.994, 0.911, 1.157, 1.446, 2.191, 2.643]\n",
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"dfz = [0.014, 0.007, 0.009, 0.007, 0.005, 0.004, 0.004, 0.005, 0.007, 0.009, 0.033]\n",
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"\n",
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"modulation_depth_axial = [1, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1]\n",
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"fy = [3.08, 3.13, 3.27, 3.46, 3.61, 3.82, 3.51, 3.15, 3.11, 3.02]\n",
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"dfy = [0.03, 0.04, 0.04, 0.05, 0.07, 0.06, 0.11, 0.07, 0.1, 1.31]\n",
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"\n",
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"plotMeasuredTrapFrequencies(fx, dfx, fy, dfy, fz, dfz, modulation_depth_radial, modulation_depth_axial, w_x, w_z, plot_against_mod_depth = True)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4a4843d2",
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"metadata": {},
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"source": [
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"## Plot ratio of measured to calculated trap frequencies"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "58cf3f64",
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"metadata": {},
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"outputs": [],
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"source": [
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"modulation_depth = [0.5, 0.3, 0.7, 0.9, 0.8, 1.0, 0.6, 0.4, 0.2, 0.1]\n",
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"w_xs = w_x * convert_modulation_depth_to_alpha(modulation_depth)[0]\n",
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"\n",
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"v_x = np.zeros(len(modulation_depth))\n",
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"v_y = np.zeros(len(modulation_depth))\n",
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"v_z = np.zeros(len(modulation_depth))\n",
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"\n",
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"for i in range(len(modulation_depth)):\n",
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" v_x[i] = calculateTrapFrequency(w_xs[i], w_z, Power, dir = 'x').value / 1e3\n",
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" v_y[i] = calculateTrapFrequency(w_xs[i], w_z, Power, dir = 'y').value\n",
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" v_z[i] = calculateTrapFrequency(w_xs[i], w_z, Power, dir = 'z').value / 1e3\n",
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"\n",
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"fx = [0.28, 0.690, 0.152, 0.102, 0.127, 0.099, 0.205, 0.404, 1.441, 2.813]\n",
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"dfx = [0.006, 0.005, 0.006, 0.003, 0.002, 0.002,0.002, 0.003, 0.006, 0.024]\n",
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"fy = [3.08, 3.13, 3.27, 3.46, 3.61, 3.82, 3.51, 3.15, 3.11, 3.02]\n",
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"dfy = [0.03, 0.04, 0.04, 0.05, 0.07, 0.06, 0.11, 0.07, 0.1, 1.31]\n",
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"fz = [1.278, 1.719, 1.058, 0.923, 0.994, 0.911, 1.157, 1.446, 2.191, 2.643]\n",
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"dfz = [0.007, 0.009, 0.007, 0.005, 0.004, 0.004, 0.005, 0.007, 0.009, 0.033]\n",
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"\n",
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"plotRatioOfTrapFrequencies(fx, fy, fz, dfx, dfy, dfz, v_x, v_y, v_z, modulation_depth, w_x, w_z, plot_against_mod_depth = True)\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "44e92099",
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"metadata": {},
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"source": [
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"## Plot Feshbach Resonances"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d15205ff",
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"metadata": {},
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"outputs": [],
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"source": [
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"plotScatteringLengths(B_range = [0, 3.6])"
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]
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},
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{
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"cell_type": "markdown",
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"id": "1a2e113f",
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"metadata": {},
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"source": [
|
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"## Calculate and Plot Collision Rates and PSD"
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]
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},
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{
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"cell_type": "code",
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|
"execution_count": null,
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"id": "86e9ba21",
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|
"metadata": {
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"scrolled": false
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|
},
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"outputs": [],
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"source": [
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"AtomNumber = 1.00 * 1e7\n",
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"BField = 1.4 * u.G\n",
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"Power = 40*u.W\n",
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"Wavelength = 1.064*u.um\n",
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"w_x, w_z = 30*u.um, 30*u.um # Beam Waists in the x and y directions\n",
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"modulation_depth = np.arange(0, 1.0, 0.08)\n",
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"\n",
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"w_xs = w_x * convert_modulation_depth_to_alpha(modulation_depth)[0]\n",
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"new_aspect_ratio = w_xs / w_z\n",
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"Temperatures = convert_modulation_depth_to_temperature(modulation_depth)[0] * u.uK\n",
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"\n",
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"# n = np.zeros(len(modulation_depth))\n",
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"Gamma_elastic = np.zeros(len(modulation_depth))\n",
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"PSD = np.zeros(len(modulation_depth))\n",
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"\n",
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"for i in range(len(modulation_depth)):\n",
|
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" # n[i] = particleDensity(w_xs[i], w_z, Power, N = AtomNumber, T = Temperatures[i]).decompose().to(u.cm**(-3))\n",
|
|
" Gamma_elastic[i] = calculateElasticCollisionRate(w_xs[i], w_z, Power, N = AtomNumber, T = Temperatures[i], B = BField).value\n",
|
|
" PSD[i] = calculatePSD(w_xs[i], w_z, Power, N = AtomNumber, T = Temperatures[i]).decompose().value\n",
|
|
"\n",
|
|
"\n",
|
|
"plotCollisionRatesAndPSD(Gamma_elastic, PSD, modulation_depth, new_aspect_ratio, plot_against_mod_depth = True)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "74d353c9",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Plot Collision Rates and PSD from only measured trap frequencies"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "6c81d9da",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"AtomNumber = 1.00 * 1e7\n",
|
|
"BField = 1.4 * u.G\n",
|
|
"Wavelength = 1.064*u.um\n",
|
|
"w_x, w_z = 30*u.um, 30*u.um # Beam Waists in the x and y directions\n",
|
|
"\n",
|
|
"fin_mod_depth = [0.5, 0.3, 0.7, 0.9, 0.8, 1.0, 0.6, 0.4, 0.2, 0.1]\n",
|
|
"v_x = [0.28, 0.690, 0.152, 0.102, 0.127, 0.099, 0.205, 0.404, 1.441, 2.813] * u.kHz\n",
|
|
"dv_x = [0.006, 0.005, 0.006, 0.003, 0.002, 0.002,0.002, 0.003, 0.006, 0.024] * u.kHz\n",
|
|
"v_z = [1.278, 1.719, 1.058, 0.923, 0.994, 0.911, 1.157, 1.446, 2.191, 2.643] * u.kHz\n",
|
|
"dv_z = [0.007, 0.009, 0.007, 0.005, 0.004, 0.004, 0.005, 0.007, 0.009, 0.033] * u.kHz\n",
|
|
"sorted_modulation_depth, sorted_v_x = zip(*sorted(zip(fin_mod_depth, v_x)))\n",
|
|
"sorted_modulation_depth, sorted_dv_x = zip(*sorted(zip(fin_mod_depth, dv_x)))\n",
|
|
"sorted_modulation_depth, sorted_v_z = zip(*sorted(zip(fin_mod_depth, v_z)))\n",
|
|
"sorted_modulation_depth, sorted_dv_z = zip(*sorted(zip(fin_mod_depth, dv_z)))\n",
|
|
"\n",
|
|
"fin_mod_depth = [1, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1] \n",
|
|
"v_y = [3.08, 3.13, 3.27, 3.46, 3.61, 3.82, 3.51, 3.15, 3.11, 3.02] * u.Hz\n",
|
|
"dv_y = [0.03, 0.04, 0.04, 0.05, 0.07, 0.06, 0.11, 0.07, 0.1, 1.31] * u.Hz\n",
|
|
"sorted_modulation_depth, sorted_v_y = zip(*sorted(zip(fin_mod_depth, v_y)))\n",
|
|
"sorted_modulation_depth, sorted_dv_y = zip(*sorted(zip(fin_mod_depth, dv_y)))\n",
|
|
"\n",
|
|
"fin_mod_depth = [1.0, 0.8, 0.6, 0.4, 0.2, 0.9, 0.7, 0.5, 0.3, 0.1]\n",
|
|
"T_x = [22.1, 27.9, 31.7, 42.2, 145.8, 27.9, 33.8, 42.4, 61.9, 136.1] * u.uK\n",
|
|
"dT_x = [1.7, 2.6, 2.4, 3.7, 1.1, 2.2, 3.2, 1.7, 2.2, 1.2] * u.uK\n",
|
|
"T_y = [13.13, 14.75, 18.44, 26.31, 52.55, 13.54, 16.11, 21.15, 35.81, 85.8] * u.uK\n",
|
|
"dT_y = [0.05, 0.05, 0.07, 0.16, 0.28, 0.04, 0.07, 0.10, 0.21, 0.8] * u.uK\n",
|
|
"\n",
|
|
"sorted_modulation_depth, sorted_T_x = zip(*sorted(zip(fin_mod_depth, T_x)))\n",
|
|
"sorted_modulation_depth, sorted_dT_x = zip(*sorted(zip(fin_mod_depth, dT_x)))\n",
|
|
"sorted_modulation_depth, sorted_T_y = zip(*sorted(zip(fin_mod_depth, T_y)))\n",
|
|
"sorted_modulation_depth, sorted_dT_y = zip(*sorted(zip(fin_mod_depth, dT_y)))\n",
|
|
"\n",
|
|
"modulation_depth = sorted_modulation_depth\n",
|
|
"\n",
|
|
"pd, dpd, T, dT, new_aspect_ratio = calculateParticleDensityFromMeasurements(sorted_v_x, sorted_dv_x, sorted_v_y, sorted_dv_y, sorted_v_z, sorted_dv_z, w_x, w_z, sorted_T_x, sorted_T_y, sorted_dT_x, sorted_dT_y, sorted_modulation_depth, AtomNumber, m = 164*u.u)\n",
|
|
"\n",
|
|
"Gamma_elastic = [(pd[i] * scatteringCrossSection(BField) * meanThermalVelocity(T[i]) / (2 * np.sqrt(2))).decompose() for i in range(len(pd))]\n",
|
|
"Gamma_elastic_values = [(Gamma_elastic[i]).value for i in range(len(Gamma_elastic))]\n",
|
|
"dGamma_elastic = [(Gamma_elastic[i] * ((dpd[i]/pd[i]) + (dT[i]/(2*T[i])))).decompose() for i in range(len(Gamma_elastic))]\n",
|
|
"dGamma_elastic_values = [(dGamma_elastic[i]).value for i in range(len(dGamma_elastic))]\n",
|
|
"\n",
|
|
"PSD = [((pd[i] * thermaldeBroglieWavelength(T[i])**3).decompose()).value for i in range(len(pd))]\n",
|
|
"dPSD = [((PSD[i] * ((dpd[i]/pd[i]) - (1.5 * dT[i]/T[i]))).decompose()).value for i in range(len(Gamma_elastic))]\n",
|
|
"\n",
|
|
"fig, ax1 = plt.subplots(figsize=(8, 6))\n",
|
|
"ax2 = ax1.twinx()\n",
|
|
"ax1.errorbar(modulation_depth, Gamma_elastic_values, yerr = dGamma_elastic_values, fmt = 'ob', markersize=5, capsize=5)\n",
|
|
"ax2.errorbar(modulation_depth, PSD, yerr = dPSD, fmt = '-^r', markersize=5, capsize=5)\n",
|
|
"ax2.yaxis.set_major_formatter(mtick.FormatStrFormatter('%.1e'))\n",
|
|
"ax1.set_xlabel('Modulation depth', fontsize= 12, fontweight='bold')\n",
|
|
"ax1.set_ylabel('Elastic Collision Rate (' + str(Gamma_elastic[0].unit) + ')', fontsize= 12, fontweight='bold')\n",
|
|
"ax1.tick_params(axis=\"y\", labelcolor='b')\n",
|
|
"ax2.set_ylabel('Phase Space Density', fontsize= 12, fontweight='bold')\n",
|
|
"ax2.tick_params(axis=\"y\", labelcolor='r')\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.grid(visible=1)\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "9329ee37",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Investigate deviation in alpha"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "7b8191f2",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"Power = 40*u.W\n",
|
|
"Wavelength = 1.064*u.um\n",
|
|
"w_x, w_z = 30*u.um, 30*u.um\n",
|
|
"\n",
|
|
"options = {\n",
|
|
" 'axis': 0, # axis referenced to the beam along which you want the dipole trap potential\n",
|
|
" 'extent': 3e2, # range of spatial coordinates in one direction to calculate trap potential over\n",
|
|
" 'crossed': False,\n",
|
|
" 'delta': 70, # angle between arms in degrees\n",
|
|
" 'modulation': False,\n",
|
|
" 'aspect_ratio': 5, # required aspect ratio of modulated arm\n",
|
|
" 'gravity': True,\n",
|
|
" 'tilt_gravity': False,\n",
|
|
" 'theta': 0.75, # gravity tilt angle in degrees\n",
|
|
" 'tilt_axis': [1, 0, 0], # lab space coordinates are rotated about x-axis in reference frame of beam\n",
|
|
" 'astigmatism': True,\n",
|
|
" 'foci_disp_single': 2.5*u.mm, #0.9 * z_R(w_0 = np.asarray([30]), lamb = 1.064)[0]*u.um, # difference in position of the foci along the propagation direction\n",
|
|
" 'foci_disp_crossed': [2.5*u.mm, 1.5*u.mm], # astigmatism of each of the two beams in the cODT\n",
|
|
" 'foci_shift': [0.0*u.mm, 0.0*u.mm],\n",
|
|
" 'beam_disp': [[0.0, 0.0, 0.0]*u.mm, [0, 0, 0.03]*u.mm],\n",
|
|
" 'extract_trap_frequencies': False # Flag to extract trap frequencies by fitting the computed potential\n",
|
|
"}\n",
|
|
"\n",
|
|
"modulation_depth = np.arange(0, 1.1, 0.1)\n",
|
|
"Alphas, fin_mod_dep, meas_alpha_x, meas_alpha_z, dalpha_x, dalpha_z = convert_modulation_depth_to_alpha(modulation_depth) \n",
|
|
"meas_alpha_deviation = [(g - h) for g, h in zip(meas_alpha_x, meas_alpha_z)]\n",
|
|
"sorted_fin_mod_dep, sorted_meas_alpha_deviation = zip(*sorted(zip(fin_mod_dep, meas_alpha_deviation)))\n",
|
|
"avg_alpha = [(g + h) / 2 for g, h in zip(meas_alpha_x, meas_alpha_z)]\n",
|
|
"sorted_fin_mod_dep, new_aspect_ratio = zip(*sorted(zip(fin_mod_dep, (w_x * avg_alpha) / w_z)))\n",
|
|
"\n",
|
|
"current_ar = w_x/w_z\n",
|
|
"aspect_ratio = np.arange(current_ar, 10*current_ar, 0.8)\n",
|
|
"w_x = w_x * (aspect_ratio / current_ar)\n",
|
|
"\n",
|
|
"v_x = np.zeros(len(w_x))\n",
|
|
"#v_y = np.zeros(len(w_x))\n",
|
|
"v_z = np.zeros(len(w_x))\n",
|
|
"\n",
|
|
"for i in range(len(w_x)):\n",
|
|
" \n",
|
|
" options['axis'] = 0\n",
|
|
" ExtractedTrapFrequencies = computeTrapPotential(w_x[i], w_z, Power, options)[5]\n",
|
|
" tmp = ExtractedTrapFrequencies[0][0]\n",
|
|
" v_x[i] = tmp if not np.isinf(tmp) else np.nan\n",
|
|
" \n",
|
|
" # options['axis'] = 1\n",
|
|
" # ExtractedTrapFrequencies = computeTrapPotential(w_x[i], w_z, Power, options)[5]\n",
|
|
" # tmp = ExtractedTrapFrequencies[1][0]\n",
|
|
" # v_y[i] = tmp if not np.isinf(tmp) else np.nan\n",
|
|
" \n",
|
|
" options['axis'] = 2\n",
|
|
" ExtractedTrapFrequencies = computeTrapPotential(w_x[i], w_z, Power, options)[5]\n",
|
|
" tmp = ExtractedTrapFrequencies[0][0]\n",
|
|
" v_z[i] = tmp if not np.isinf(tmp) else np.nan\n",
|
|
"\n",
|
|
" #v_x[i] = calculateTrapFrequency(w_x[i], w_z, Power, dir = 'x').value\n",
|
|
" #v_y[i] = calculateTrapFrequency(w_x[i], w_z, Power, dir = 'y').value\n",
|
|
" #v_z[i] = calculateTrapFrequency(w_x[i], w_z, Power, dir = 'z').value\n",
|
|
"\n",
|
|
"alpha_x = [(v_x[0]/v)**(2/3) for v in v_x]\n",
|
|
"alpha_z = [(v_z[0]/v)**2 for v in v_z]\n",
|
|
"\n",
|
|
"calc_alpha_deviation = [(g - h) for g, h in zip(alpha_x, alpha_z)]\n",
|
|
"\n",
|
|
"plt.figure()\n",
|
|
"plt.plot(aspect_ratio, alpha_x, '-o', label = 'From horz TF')\n",
|
|
"plt.plot(aspect_ratio, alpha_z, '-^', label = 'From vert TF')\n",
|
|
"plt.xlabel('Aspect Ratio', fontsize= 12, fontweight='bold')\n",
|
|
"plt.ylabel('$\\\\alpha$', fontsize= 12, fontweight='bold')\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.grid(visible=1)\n",
|
|
"plt.legend(prop={'size': 12, 'weight': 'bold'})\n",
|
|
"plt.show()\n",
|
|
"\n",
|
|
"plt.figure()\n",
|
|
"plt.plot(aspect_ratio, calc_alpha_deviation, '--ob', label = 'Extracted')\n",
|
|
"plt.plot(new_aspect_ratio, sorted_meas_alpha_deviation, '-or', label = 'Measured')\n",
|
|
"plt.xlabel('Aspect Ratio', fontsize= 12, fontweight='bold')\n",
|
|
"plt.ylabel('$\\\\Delta \\\\alpha$', fontsize= 12, fontweight='bold')\n",
|
|
"plt.ylim([-0.5, 1])\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.grid(visible=1)\n",
|
|
"plt.legend(prop={'size': 12, 'weight': 'bold'})\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "29a1cf87",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Quick calculation of PSD and elastic collision rate"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "3950f1b5",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"Power = 9.5*u.W\n",
|
|
"Wavelength = 1.064*u.um\n",
|
|
"w_x, w_z = 50*u.um, 45*u.um # Beam Waists in the x and y directions\n",
|
|
"\n",
|
|
"NCount = 11000\n",
|
|
"AtomNumber = calculateAtomNumber(NCount, pixel_size = 3.45 * u.um, magnification = 0.5, eta = 0.5)\n",
|
|
"#AtomNumber = calculateAtomNumber(NCount, pixel_size = 5.86 * u.um, magnification = 0.5, eta = 0.5)\n",
|
|
"\n",
|
|
"BField = 3.75 * u.G\n",
|
|
"modulation_depth = 0.00\n",
|
|
"\n",
|
|
"w_x = w_x * convert_modulation_depth_to_alpha(modulation_depth)[0]\n",
|
|
"new_aspect_ratio = w_x / w_z\n",
|
|
"Temperature = 33 * u.uK\n",
|
|
"\n",
|
|
"n = particleDensity(w_x, w_z, Power, N = AtomNumber, T = Temperature).decompose().to(u.cm**(-3))\n",
|
|
"Gamma_elastic = calculateElasticCollisionRate(w_x, w_z, Power, N = AtomNumber, T = Temperature, B = BField)\n",
|
|
"PSD = calculatePSD(w_x, w_z, Power, N = AtomNumber, T = Temperature).decompose()\n",
|
|
"\n",
|
|
"print('Particle Density = %.2E ' % (n.value) + str(n.unit))\n",
|
|
"print('Elastic Collision Rate = %.2f ' % (Gamma_elastic.value) + str(Gamma_elastic.unit))\n",
|
|
"print('PSD = %.2E ' % (PSD.value))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "d975586b",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Plot measured PSDs and collision rates"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "b11b6aae",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"Gamma_elastic = [96.01, 82.53, 102.95, 143.5, 110.92, 471.77, 908.46]\n",
|
|
"PSD = [8.95e-05, 4.19e-04, 2.94e-04, 2.17e-04, 8.98e-04, 5.52e-04, 6.10e-04]\n",
|
|
"\n",
|
|
"fig, ax1 = plt.subplots(figsize=(8, 6))\n",
|
|
"ax2 = ax1.twinx()\n",
|
|
"\n",
|
|
"ax1.plot(Gamma_elastic, '-ob')\n",
|
|
"ax2.plot(PSD, '-*r')\n",
|
|
"ax2.yaxis.set_major_formatter(mtick.FormatStrFormatter('%.1e'))\n",
|
|
"\n",
|
|
"ax1.set_xlabel('Optimization Steps', fontsize= 12, fontweight='bold')\n",
|
|
"ax1.set_ylabel('Elastic Collision Rate', fontsize= 12, fontweight='bold')\n",
|
|
"ax1.tick_params(axis=\"y\", labelcolor='b')\n",
|
|
"ax2.set_ylabel('Phase Space Density', fontsize= 12, fontweight='bold')\n",
|
|
"ax2.tick_params(axis=\"y\", labelcolor='r')\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.grid(visible=1)\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "da1a3346",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Plot crossed beam trap potential resulting for given parameters only"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "f17a4d01",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"Powers = [1, 11] * u.W\n",
|
|
"Wavelength = 1.064*u.um\n",
|
|
"w_x = [27, 67]*u.um # Beam Waists in the x direction\n",
|
|
"w_z = [31, 67]*u.um # Beam Waists in the y direction\n",
|
|
"\n",
|
|
"options = {\n",
|
|
" 'axis':2, # axis referenced to the beam along which you want the dipole trap potential\n",
|
|
" 'extent': 3e2, # range of spatial coordinates in one direction to calculate trap potential over\n",
|
|
" 'crossed': True, # Flag for either a crossed beam configuration or a single focussed beam\n",
|
|
" 'delta': 70, # angle between arms in degrees\n",
|
|
" 'modulation': False, # Flag for spatial modulation of a single beam\n",
|
|
" 'aspect_ratio': 5, # required aspect ratio of modulated arm\n",
|
|
" 'gravity': False, # Flag for adding levitation/gravitation potential\n",
|
|
" 'tilt_gravity': False, # Flag for tilt of the beam wrt to gravity axis\n",
|
|
" 'theta': 0.75, # gravity tilt angle in degrees\n",
|
|
" 'tilt_axis': [1, 0, 0], # lab space coordinates are rotated about x-axis in reference frame of beam\n",
|
|
" 'astigmatism': False, # Flag for astigmatism of beam\n",
|
|
" 'foci_disp_single': 2.5*u.mm, #0.9 * z_R(w_0 = np.asarray([30]), lamb = 1.064)[0]*u.um, # difference in position of the foci along the propagation direction\n",
|
|
" 'foci_disp_crossed': [2.5*u.mm, 2.8*u.mm], # astigmatism of each of the two beams in the cODT\n",
|
|
" 'foci_shift': [0.0*u.mm, 0.0*u.mm],\n",
|
|
" 'beam_disp': [[0.0, 0.0, 0.05]*u.mm, [0.0, 0.0, 0.0]*u.mm], # shift arm 1 along x, z; shift arm 2 along y, z\n",
|
|
" 'extract_trap_frequencies': True # Flag to extract trap frequencies by fitting the computed potential\n",
|
|
"}\n",
|
|
"\n",
|
|
"Positions, IdealTrappingPotential, TrappingPotential, TrapDepthsInKelvin, CalculatedTrapFrequencies, ExtractedTrapFrequencies = computeTrapPotential(w_x, w_z, Powers, options)\n",
|
|
"\n",
|
|
"EffectiveTrapDepthInKelvin = TrapDepthsInKelvin[1]\n",
|
|
"v = ExtractedTrapFrequencies[1][0]\n",
|
|
"dv = ExtractedTrapFrequencies[1][1]\n",
|
|
"\n",
|
|
"plt.figure(figsize=(9, 7))\n",
|
|
"plt.plot(Positions[options['axis']], TrappingPotential[options['axis']], label = 'Effective Trap Depth = ' + str(round(EffectiveTrapDepthInKelvin.value, 2)) + ' ' + str(EffectiveTrapDepthInKelvin.unit) + '; ' + generate_label(v, dv)) \n",
|
|
"#plt.plot(Positions[options['axis']], TrappingPotential[options['axis']]) \n",
|
|
"axis = options['axis']\n",
|
|
"if axis == 0:\n",
|
|
" dir = 'X - Horizontal'\n",
|
|
"elif axis == 1:\n",
|
|
" dir = 'Y - Propagation'\n",
|
|
"else:\n",
|
|
" dir = 'Z - Vertical'\n",
|
|
" \n",
|
|
"plt.ylim(top = 0)\n",
|
|
"plt.xlabel(dir + ' Direction (um)', fontsize= 12, fontweight='bold')\n",
|
|
"plt.ylabel('Trap Potential (uK)', fontsize= 12, fontweight='bold')\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.grid(visible=1)\n",
|
|
"plt.legend(loc=1, prop={'size': 12, 'weight': 'bold'})"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "1a28b820",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Calculate trap frequencies in a crossed beam trap for given parameters"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "09149423",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"Powers = [1, 11] * u.W\n",
|
|
"w_x = [27, 67]*u.um # Beam Waists in the x direction\n",
|
|
"w_z = [31, 67]*u.um # Beam Waists in the y direction\n",
|
|
"\n",
|
|
"options = {\n",
|
|
" 'axis': 1, # axis referenced to the beam along which you want the dipole trap potential\n",
|
|
" 'extent': 1e3, # range of spatial coordinates in one direction to calculate trap potential over\n",
|
|
" 'crossed': True, # Flag for either a crossed beam configuration or a single focussed beam\n",
|
|
" 'delta': 70, # angle between arms in degrees\n",
|
|
" 'modulation': False, # Flag for spatial modulation of a single beam\n",
|
|
" 'aspect_ratio': 5, # required aspect ratio of modulated arm\n",
|
|
" 'gravity': False, # Flag for adding levitation/gravitation potential\n",
|
|
" 'tilt_gravity': False, # Flag for tilt of the beam wrt to gravity axis\n",
|
|
" 'theta': 0.75, # gravity tilt angle in degrees\n",
|
|
" 'tilt_axis': [1, 0, 0], # lab space coordinates are rotated about x-axis in reference frame of beam\n",
|
|
" 'astigmatism': False, # Flag for astigmatism of beam\n",
|
|
" 'foci_disp_single': 2.5*u.mm, #0.9 * z_R(w_0 = np.asarray([30]), lamb = 1.064)[0]*u.um, # difference in position of the foci along the propagation direction\n",
|
|
" 'foci_disp_crossed': [2.5*u.mm, 1.5*u.mm], # astigmatism of each of the two beams in the cODT\n",
|
|
" 'foci_shift': [0.01*u.mm, 0.20*u.mm],\n",
|
|
" 'beam_disp': [[0, 0, 0.0]*u.mm, [0, 0, 0.0]*u.mm],\n",
|
|
" 'extract_trap_frequencies': False # Flag to extract trap frequencies by fitting the computed potential\n",
|
|
"}\n",
|
|
"\n",
|
|
"v_x = calculateCrossedBeamTrapFrequency(options['delta'], [w_x, w_z], Powers, dir = 'x')\n",
|
|
"v_y = calculateCrossedBeamTrapFrequency(options['delta'], [w_x, w_z], Powers, dir = 'y')\n",
|
|
"v_z = calculateCrossedBeamTrapFrequency(options['delta'], [w_x, w_z], Powers, dir = 'z')\n",
|
|
"\n",
|
|
"print('v_x = %.2f ' %(v_x.value) + str(v_x.unit))\n",
|
|
"print('v_y = %.2f ' %(v_y.value) + str(v_y.unit))\n",
|
|
"print('v_z = %.2f ' %(v_z.value) + str(v_z.unit))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "3cf7eb64",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Calculate trap frequencies, trap depths in a crossed beam trap for different shifts of Arm 2 along Y and Z"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "fc585c24",
|
|
"metadata": {
|
|
"scrolled": false
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"Powers = [1, 11] * u.W\n",
|
|
"Wavelength = 1.064*u.um\n",
|
|
"w_x = [27, 67]*u.um # Beam Waists in the x direction\n",
|
|
"w_z = [31, 67]*u.um # Beam Waists in the y direction\n",
|
|
"\n",
|
|
"options = {\n",
|
|
" 'axis':1, # axis referenced to the beam along which you want the dipole trap potential\n",
|
|
" 'extent': 2e3, # range of spatial coordinates in one direction to calculate trap potential over\n",
|
|
" 'crossed': True, # Flag for either a crossed beam configuration or a single focussed beam\n",
|
|
" 'delta': 70, # angle between arms in degrees\n",
|
|
" 'modulation': False, # Flag for spatial modulation of a single beam\n",
|
|
" 'aspect_ratio': 5, # required aspect ratio of modulated arm\n",
|
|
" 'gravity': False, # Flag for adding levitation/gravitation potential\n",
|
|
" 'tilt_gravity': False, # Flag for tilt of the beam wrt to gravity axis\n",
|
|
" 'theta': 0.75, # gravity tilt angle in degrees\n",
|
|
" 'tilt_axis': [1, 0, 0], # lab space coordinates are rotated about x-axis in reference frame of beam\n",
|
|
" 'astigmatism': False, # Flag for astigmatism of beam\n",
|
|
" 'foci_disp_single': 2.5*u.mm, #0.9 * z_R(w_0 = np.asarray([30]), lamb = 1.064)[0]*u.um, # difference in position of the foci along the propagation direction\n",
|
|
" 'foci_disp_crossed': [2.5*u.mm, 2.8*u.mm], # astigmatism of each of the two beams in the cODT\n",
|
|
" 'foci_shift': [0.0*u.mm, 0.0*u.mm],\n",
|
|
" 'beam_disp': [[0.0, 0.0, 0.0]*u.mm, [0.0, 0.0, 0.0]*u.mm],\n",
|
|
" 'extract_trap_frequencies': True # Flag to extract trap frequencies by fitting the computed potential\n",
|
|
"}\n",
|
|
"\n",
|
|
"disp_range = 100\n",
|
|
"yvals = np.arange(-disp_range, disp_range, 5) \n",
|
|
"zvals = np.arange(-disp_range, disp_range, 5)\n",
|
|
"\n",
|
|
"TrapDepths = np.zeros((len(yvals), len(zvals))) * u.uK\n",
|
|
"TrapFrequencies = np.zeros((len(yvals), len(zvals)))\n",
|
|
"\n",
|
|
"idx = 0\n",
|
|
"if options['extract_trap_frequencies']:\n",
|
|
" idx = 1\n",
|
|
" \n",
|
|
"for i in range(len(yvals)):\n",
|
|
" options['beam_disp'][1][1] = yvals[i] * u.um\n",
|
|
" for j in range(len(zvals)):\n",
|
|
" options['beam_disp'][1][2] = zvals[j] * u.um\n",
|
|
" Positions, IdealTrappingPotential, TrappingPotential, TrapDepthsInKelvin, CalculatedTrapFrequencies, ExtractedTrapFrequencies = computeTrapPotential(w_x, w_z, Powers, options)\n",
|
|
" TrapDepths[i][j] = TrapDepthsInKelvin[1] \n",
|
|
" try:\n",
|
|
" if np.isnan(ExtractedTrapFrequencies[idx][0].value):\n",
|
|
" TrapFrequencies[i][j] = np.nan\n",
|
|
" else:\n",
|
|
" TrapFrequencies[i][j] = ExtractedTrapFrequencies[idx][0] \n",
|
|
" except:\n",
|
|
" TrapFrequencies[i][j] = ExtractedTrapFrequencies[idx][0] "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "e060601f",
|
|
"metadata": {
|
|
"scrolled": false
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"fig, ax = plt.subplots()\n",
|
|
"axis = options['axis']\n",
|
|
"if axis == 0:\n",
|
|
" dir = 'X'\n",
|
|
"elif axis == 1:\n",
|
|
" dir = 'Y'\n",
|
|
"else:\n",
|
|
" dir = 'Z'\n",
|
|
"plt.title('Trap Frequency along ' + dir)\n",
|
|
"c = ax.matshow(np.asarray(TrapFrequencies), origin='lower', cmap = 'coolwarm', aspect = 1)\n",
|
|
"x_pos = np.arange(len(zvals))\n",
|
|
"plt.xticks(x_pos, zvals)\n",
|
|
"#plt.xticks(np.arange(min(zvals.value), max(zvals.value), 30))\n",
|
|
"ax.xaxis.set_ticks_position('bottom')\n",
|
|
"y_pos = np.arange(len(yvals))\n",
|
|
"plt.yticks(y_pos, yvals)\n",
|
|
"#plt.yticks(np.arange(min(yvals.value), max(yvals.value), 30))\n",
|
|
"plt.xlabel('Z - shift (um)', fontsize= 12, fontweight='bold')\n",
|
|
"plt.ylabel('Y - shift (um)', fontsize= 12, fontweight='bold')\n",
|
|
"plt.setp(ax.get_xticklabels(), rotation=45, horizontalalignment='right')\n",
|
|
"fig.colorbar(c, ax = ax)\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.grid(visible=1)\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "1fe6e6de",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Calculate trap frequencies, trap depths in a crossed beam trap for different shifts of Arm 1 along X and Z"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "faf6d746",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"Powers = [1, 11] * u.W\n",
|
|
"Wavelength = 1.064*u.um\n",
|
|
"w_x = [27, 67]*u.um # Beam Waists in the x direction\n",
|
|
"w_z = [31, 67]*u.um # Beam Waists in the y direction\n",
|
|
"\n",
|
|
"options = {\n",
|
|
" 'axis':2, # axis referenced to the beam along which you want the dipole trap potential\n",
|
|
" 'extent': 3e3, # range of spatial coordinates in one direction to calculate trap potential over\n",
|
|
" 'crossed': True, # Flag for either a crossed beam configuration or a single focussed beam\n",
|
|
" 'delta': 70, # angle between arms in degrees\n",
|
|
" 'modulation': False, # Flag for spatial modulation of a single beam\n",
|
|
" 'aspect_ratio': 5, # required aspect ratio of modulated arm\n",
|
|
" 'gravity': False, # Flag for adding levitation/gravitation potential\n",
|
|
" 'tilt_gravity': False, # Flag for tilt of the beam wrt to gravity axis\n",
|
|
" 'theta': 0.75, # gravity tilt angle in degrees\n",
|
|
" 'tilt_axis': [1, 0, 0], # lab space coordinates are rotated about x-axis in reference frame of beam\n",
|
|
" 'astigmatism': False, # Flag for astigmatism of beam\n",
|
|
" 'foci_disp_single': 2.5*u.mm, #0.9 * z_R(w_0 = np.asarray([30]), lamb = 1.064)[0]*u.um, # difference in position of the foci along the propagation direction\n",
|
|
" 'foci_disp_crossed': [2.5*u.mm, 2.8*u.mm], # astigmatism of each of the two beams in the cODT\n",
|
|
" 'foci_shift': [0.0*u.mm, 0.0*u.mm],\n",
|
|
" 'beam_disp': [[0.0, 0.0, 0.0]*u.mm, [0.0, 0.0, 0.0]*u.mm],\n",
|
|
" 'extract_trap_frequencies': True # Flag to extract trap frequencies by fitting the computed potential\n",
|
|
"}\n",
|
|
"\n",
|
|
"disp_range = 100\n",
|
|
"xvals = np.arange(-disp_range, disp_range, 5) \n",
|
|
"zvals = np.arange(-disp_range, disp_range, 5)\n",
|
|
"\n",
|
|
"TrapDepths = np.zeros((len(xvals), len(zvals))) * u.uK\n",
|
|
"TrapFrequencies = np.zeros((len(xvals), len(zvals)))\n",
|
|
"\n",
|
|
"idx = 0\n",
|
|
"if options['extract_trap_frequencies']:\n",
|
|
" idx = 1\n",
|
|
" \n",
|
|
"for i in range(len(xvals)):\n",
|
|
" options['beam_disp'][0][0] = xvals[i] * u.um\n",
|
|
" for j in range(len(zvals)):\n",
|
|
" options['beam_disp'][0][2] = zvals[j] * u.um\n",
|
|
" Positions, IdealTrappingPotential, TrappingPotential, TrapDepthsInKelvin, CalculatedTrapFrequencies, ExtractedTrapFrequencies = computeTrapPotential(w_x, w_z, Powers, options)\n",
|
|
" TrapDepths[i][j] = TrapDepthsInKelvin[1] \n",
|
|
" try:\n",
|
|
" if np.isnan(ExtractedTrapFrequencies[idx][0].value):\n",
|
|
" TrapFrequencies[i][j] = np.nan\n",
|
|
" else:\n",
|
|
" TrapFrequencies[i][j] = ExtractedTrapFrequencies[idx][0] \n",
|
|
" except:\n",
|
|
" TrapFrequencies[i][j] = ExtractedTrapFrequencies[idx][0] "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "387ec0a1",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"fig, ax = plt.subplots()\n",
|
|
"axis = options['axis']\n",
|
|
"if axis == 0:\n",
|
|
" dir = 'X'\n",
|
|
"elif axis == 1:\n",
|
|
" dir = 'Y'\n",
|
|
"else:\n",
|
|
" dir = 'Z'\n",
|
|
"plt.title('Trap Frequency along ' + dir)\n",
|
|
"\n",
|
|
"c = ax.matshow(np.asarray(TrapFrequencies), origin='lower', cmap = 'coolwarm', aspect = 1)\n",
|
|
"\n",
|
|
"x_pos = np.arange(len(zvals))\n",
|
|
"plt.xticks(x_pos, zvals)\n",
|
|
"#plt.xticks(np.arange(min(zvals.value), max(zvals.value), 30))\n",
|
|
"ax.xaxis.set_ticks_position('bottom')\n",
|
|
"x_pos = np.arange(len(xvals))\n",
|
|
"plt.yticks(x_pos, xvals)\n",
|
|
"#plt.yticks(np.arange(min(yvals.value), max(yvals.value), 30))\n",
|
|
"plt.xlabel('Z - shift (um)', fontsize= 12, fontweight='bold')\n",
|
|
"plt.ylabel('X - shift (um)', fontsize= 12, fontweight='bold')\n",
|
|
"plt.setp(ax.get_xticklabels(), rotation=45, horizontalalignment='right')\n",
|
|
"fig.colorbar(c, ax = ax)\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.grid(visible=1)\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "bc9b993e",
|
|
"metadata": {},
|
|
"source": [
|
|
"# Heating Rate in ODT Arm 1"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"id": "8cc8af09",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"72.24875133898384 uK\n",
|
|
"0.7083124629372112 1 / s\n",
|
|
"24.353209421520113 nK / s\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"w_x = 27 * u.um\n",
|
|
"w_y = 31 * u.um\n",
|
|
"P = 2.29 * u.W\n",
|
|
"linewidth = 32.2 * u.MHz\n",
|
|
"detuning = 4.3e+14 * u.Hz \n",
|
|
"\n",
|
|
"HeatingRate, T_recoil, Gamma_sr, U = calculateHeatingRate(w_x, w_y, P, linewidth, detuning, wavelength = 1.064*u.um)\n",
|
|
"\n",
|
|
"print((U/ac.k_B).to(u.uK))\n",
|
|
"print(Gamma_sr)\n",
|
|
"print(HeatingRate.to(u.nK/u.s))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "56bef045",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.9.7"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|