diff --git a/ODTCalculations.ipynb b/ODTCalculations.ipynb index bcb7342..41dfee5 100644 --- a/ODTCalculations.ipynb +++ b/ODTCalculations.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "a4246751", "metadata": {}, "outputs": [], @@ -20,39 +20,16 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "38c770ac", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\Karthik\\anaconda3\\lib\\site-packages\\scipy\\optimize\\minpack.py:833: OptimizeWarning: Covariance of the parameters could not be estimated\n", - " warnings.warn('Covariance of the parameters could not be estimated',\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "Power = 1.07*u.W\n", - "Polarizability = 184.4 # in a.u, most precise measured value of Dy polarizability\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", "#Power = 11*u.W\n", - "#Polarizability = 184.4 # in a.u, most precise measured value of Dy polarizability\n", "#w_x, w_z = 67*u.um, 67*u.um # Beam Waists in the x and y directions\n", "\n", "options = {\n", @@ -74,7 +51,7 @@ "ComputedPotentials = [] \n", "Params = [] \n", "\n", - "Positions, IdealTrappingPotential, TrappingPotential, TrapDepthsInKelvin, CalculatedTrapFrequencies, ExtractedTrapFrequencies = computeTrapPotential(w_x, w_z, Power, Polarizability, options)\n", + "Positions, IdealTrappingPotential, TrappingPotential, TrapDepthsInKelvin, CalculatedTrapFrequencies, ExtractedTrapFrequencies = computeTrapPotential(w_x, w_z, Power, options)\n", "ComputedPotentials.append(IdealTrappingPotential)\n", "ComputedPotentials.append(TrappingPotential)\n", "Params.append([TrapDepthsInKelvin, CalculatedTrapFrequencies, ExtractedTrapFrequencies])\n", @@ -93,23 +70,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "0f3e80f7", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "v, dv, popt, pcov = extractTrapFrequency(Positions, TrappingPotential, options['axis'])\n", "plotHarmonicFit(Positions, TrappingPotential, TrapDepthsInKelvin, options['axis'], popt, pcov)" @@ -125,39 +89,18 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "8504f99f", "metadata": { "scrolled": false }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\Karthik\\anaconda3\\lib\\site-packages\\scipy\\optimize\\minpack.py:833: OptimizeWarning: Covariance of the parameters could not be estimated\n", - " warnings.warn('Covariance of the parameters could not be estimated',\n" - ] - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "Potentials = [] \n", "Params = [] \n", "Power = [10, 30, 40]*u.W # Single Beam Power\n", "for p in Power: \n", - " Positions, IdealTrappingPotential, TrappingPotential, TrapDepthsInKelvin, CalculatedTrapFrequencies, ExtractedTrapFrequencies = computeTrapPotential(w_x, w_z, p, Polarizability, options)\n", + " Positions, IdealTrappingPotential, TrappingPotential, TrapDepthsInKelvin, CalculatedTrapFrequencies, ExtractedTrapFrequencies = computeTrapPotential(w_x, w_z, p, options)\n", " Potentials.append(IdealTrappingPotential)\n", " Potentials.append(TrappingPotential)\n", " Params.append([TrapDepthsInKelvin, CalculatedTrapFrequencies, ExtractedTrapFrequencies])\n", @@ -181,14 +124,29 @@ "metadata": {}, "outputs": [], "source": [ + "Power = 40*u.W\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", "options = {\n", + " 'axis': 2, # axis referenced to the beam along which you want the dipole trap potential\n", " 'extent': 60, # 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': True,\n", " 'modulation_function': 'arccos',\n", - " 'modulation_amplitude': 2.16\n", + " 'modulation_amplitude': 2.16,\n", + " 'aspect_ratio': 4, # 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': False,\n", + " '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", + " 'extract_trap_frequencies': False\n", "}\n", "\n", - "positions, waists, I, U, p = computeIntensityProfileAndPotentials(Power, [w_x, w_z], Polarizability, Wavelength, options)\n", + "positions, waists, I, U, p = computeIntensityProfileAndPotentials(Power, [w_x, w_z], Wavelength, options)\n", "plotIntensityProfileAndPotentials(positions, waists, I, U)" ] }, @@ -227,27 +185,12 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "95ab43bd", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Particle Density = 4.63E+13 1 / cm3\n", - "Elastic Collision Rate = 2813.75 1 / s\n", - "PSD = 9.00E-05 \n", - "v_x = 2588.17 Hz\n", - "v_y = 20.66 Hz\n", - "v_z = 2588.17 Hz\n", - "a_s = 111.31 \n" - ] - } - ], + "outputs": [], "source": [ "Power = 40*u.W\n", - "Polarizability = 184.4 # in a.u, most precise measured value of Dy polarizability\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", @@ -256,17 +199,17 @@ "\n", "modulation_depth = 0.0\n", "Temperature = convert_modulation_depth_to_temperature(modulation_depth)[0] * u.uK\n", - "n = particleDensity(w_x, w_z, Power, Polarizability, N = AtomNumber, T = Temperature, m = 164*u.u).decompose().to(u.cm**(-3))\n", - "Gamma_elastic = calculateElasticCollisionRate(w_x, w_z, Power, Polarizability, N = AtomNumber, T = Temperature, B = BField)\n", - "PSD = calculatePSD(w_x, w_z, Power, Polarizability, N = AtomNumber, T = Temperature).decompose()\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))\n", "\n", - "v_x = calculateTrapFrequency(w_x, w_z, Power, Polarizability, dir = 'x')\n", - "v_y = calculateTrapFrequency(w_x, w_z, Power, Polarizability, dir = 'y')\n", - "v_z = calculateTrapFrequency(w_x, w_z, Power, Polarizability, dir = 'z')\n", + "v_x = calculateTrapFrequency(w_x, w_z, Power, dir = 'x')\n", + "v_y = calculateTrapFrequency(w_x, w_z, Power, dir = 'y')\n", + "v_z = calculateTrapFrequency(w_x, w_z, Power, 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", @@ -285,23 +228,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "dd7fc03d", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plotTemperatures(w_x, w_z, plot_against_mod_depth = True)" ] @@ -347,38 +264,28 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "0ddff726", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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5HsOqQatoXK6xuT+xe3e4fBkWLIAuXXJ07r/+gmbNICQE1q83q5MLIYS4lbsFnJiYGCZMmHDb9uLFi/PKK6/k6JwScNyEOwUcgGMXjtH2y7Zci7/Gr0N+pW7punD8ONx/P+zaBR99BCNH5ujcy5aZMcyPPAIzZ4Jy/uSSQgjh0twt4ERGRlIlnWb54OBgIiMjc3ROTwg4MgbHBQUXDWbV4FX4efvRcVZHDp47CBUrmjusunSBUaPMEg85uC2qWzcYPx5mz4aPP3Z87UIIIZwrJCQk3dukcxpuPIUEHBdVvXh1Vg5aSZJOouOsjhw9fxQKF4ZFi8wt5P/7n5n5uHJl8PIy/U5z5th17pdeMq04Y8eariohhBDC00jAcWF1StXh54E/czXuKh1ndeT4peNm9cwPP4SBA2HrVjNqOHm6zOHD7Qo5Xl6mBSc4GPr2NQvDCSGEEJ5EAo6La1i2ISsGruDc9XN0nNWRU1dOmQ/Wrr1952vXYNw4u85btCh89x1cugQPPHD73A1CCCGEO5OA4waalW/G8gHLOXHpBPfMuoez185CVFT6O2e0PR3168O0aaab6rnnHFSsEEII4QIk4LiJVpVa8UP/H/jr/F90mt2J89UrpL9j5crZOm+/fmZFiA8/hK++ckChQgghhAuQgONGOlTpwHcPfcfef/bS5dECXCqaZnrugAB47bVsn/ett8xkycOHmyl3hBBCCHcnAcfNdKnehQV9F/BH/DG6v1CJv+qVp90QOFUIGDIEBgzI9jl9fc38gcWKmaWvYmIcXbUQQgjhXBJw3FDP2j2ZEzqHDbGHaTdUsa6KFxO6BsLp0zk+Z5kysHChmU9wwIBcLWIuhBD5WvTlaNrNaJdyU4iwhAQcNzV40WCSdBInLp8gSSfxSd1rqAYRBLya8aqyWWnZEj74wCzIGR7uwGKFECIfmbh2Iuui1jHh19uXT8iNwYMHo5Ti3Xffvblt6NChKKWYNGlSusd06tQJpRRz5869ua1Lly4opfj6668dWp+rkaUa3FT05WieW/Ec3+z9hvikeAooX/ruiGdSv+mUfWBojs+rNQwbBl9+Cd9/b1aHEEKI/CTtMgVjfxzL9lPbszzut6jfSNK3zzDvpbxoW7ltpsc2KtuI97u8n+k+K1eu5J577qF58+Zs3ryZ+Ph4ypQpw6VLl/j7778pV67cbcfMnz+ffv360bVrV5YtW8aVK1coWbIkPj4+nD59moIF0191QZZqEJYpV7gcQQWCSNSmLylWxxOk/Sj7w+pcnVcpmDIFmjQx61UdOuSIaoUQwvM1L9+c0oGl8VLmV6uX8qJ0wdK0qNDCIefv0KEDlSpVYsuWLRw9epQVK1Zw/vx57rnnnnTDDUDv3r0pUaIEP//8M2fOnOHHH38kNjaWHj16ZBhuPIWP1QWInDt99TQjm47k2MVj/HLkF05WLw2f/wDx8WbkcA4FBEBEBDRtCr17w6ZNUKiQAwsXQgg3klXLSmqjloxi6h9T8ffxJy4xjj51+vBxd8cs/Ofl5cUjjzzCG2+8wYIFC9i7dy9guq4y4ufnx8CBA3n//feZN28eW7duBWBADm5IcTfSguPGIh6KYEr3KTzW5DFiE2N5qsFjcOECrFmT63MHB8PcubBvHzz2mOm6EkIIkbnkf3huGraJkU1HOnyg8aBBgwCYM2cOixcvJigoiF69emV6zGOPPQbAzJkzWbp0KSVKlODee+91aF2uSFpwPMC91e4l0DeQiKATdAwMNGswdOqU6/N26mSm1XnxRWjeHJ591gHFCiGEB4t4KOLm6yndpzj8/LVr1+bOO+/k999/B+DRRx8lICDzm0vq1q1LixYt2Lx5MwAjR47ENxet/O5CWnA8QKBvIF2rd+W7Qz+Q1K2rWXE86faBbjnx/POmm+o//3FIw5AQQohcSt0lldyik5XkVhyAhx9+2OE1uSIJOB4itE4o0Vei2dSlnlke3JbUc0spmDEDatSABx808+QIIYSwzujRo9Fao7WmXbt2dh1zv+2W2MqVK9OmTZu8LM9lSBeVh+heozu+Xr5ElD5HK19fM0r4X/9yyLmDgkyv1513Qp8+ZiHzAgUccmohhBC5FBMTw4QJt8+5U7x4cV555RWmT5/O0qVLARg1ahRKKWeXaAmZB8eDdJvTjf1n9/PXjzVRhw6be7wd+Ac5IsIEnBEj4NNPHXZaIYRwKRnNAeOqIiMjqVKlym3bg4ODiYyMJCQkhFOnTtGjRw+++uor/Pz8sjynzIMjXEponVCOXjjKjvubw19/wa5djj1/qBmT89lnMG2aQ08thBAih0JCQm52WaV+REZGAiYA3bhxgwULFtgVbjyFBBwP0rNWT7yUFxGVr5iWm4iIrA/KpldfhXvugdGjwTadghBCCOFyJOB4kFIFS3FX8F1ERK2ANm3MwBkH8/Ex8+OUKWNadP75x+GXEEIIy+WH4RsZSXLQXbhWk4DjYUJrh7Lnnz0c6NEadu40XVUOVrKkaRw6cwb694eEBIdfQgghLOPv78+5c+fyXcjRWhMXF8eJEyc8YhkHuYvKw/Sq3Yunf3yaiFqJvAimFee55xx+naZN4ZNP4NFH4aWX4M03HX4JIYSwRMWKFTl+/Dj/5MMmah8fH4oUKULJkiWtLiXX5C4qD9TiixYk6SR+/zTJ3M+9YUOeXWvkSDPo+NtvzR1WQgghPJfcRSUsFVo7lK0ntxLVqwNs3Ggm/ssjkydDixYwZIhZt0oIIYRwBRJwPFBonVAAvmtgW2tk0aI8u1aBAqb1JjDQLOlw8CC0awenHLu+nBBCCJEtEnA8UI0SNahfuj4RMRugZs08uV08tYoVYcECOHwYunSBdetg4sQ8vaQQQgiRKQk4Hiq0Tii/Rf3G6dDOZpXMmJg8vV67dvDyy3D0qFnn88svpRVHCCHyGxWupqtwdUaFq92ptjVS4WqTClfbVbjaqsJVc2fUIgHHQ4XWCUWj+b5ZIXMf95IleX7NU6fAy/YnKiFBWnGEECIfmgF0SbPtbSBch+lGwCu293lOAo6Hql+6PtWKVSPi+h+mDykPJv1LLTrarDqePD9UfDxMny6tOEIIkZ/oML0WSNtloIEg2+siwEln1JIv5sEpXrw4a9assboMp2tWsBkLjyxkycQPKRRzDVatSmlicbCoKHjtNUg768CKFVC5cp5cUgghhPP5KKVSL9QzVWs9NYtjxgI/qXA1CdOw0iqvikstXwScmJgY2rdvb3UZTudf3Z/50+ZzwT+K+/7vDVi40KyvkAcaN4bt22/fXrVqnkymLIQQwhoJWutm2TxmFPCMDtMLVbh6EJgG3OP40m4lXVQerHmF5pQvXJ4I9kGJEnl6N9Wff5rWm+THjRtQvz5cuWKWdBBCCJFvDQaSfwF9A8ggY5E7XsqL3rV78+NfP3G1Z1cz0DguzinXLlAAvv4aLl6Exx67vetKCCFEvnESaGd7fTdwyBkXlYDj4frU6cP1hOv81L6SSRurVzvt2vXqwVtvwQ8/wNSsemiFEEK4PRWu5gIbgVoqXB1X4WoY8DjwPxWudgCvA8OdUousReXZEpISKDupLF2qdOKrR5fAww+bxaOcJCkpZfK/P/+EWrWcdmkhhBAOJmtRCZfh4+VDz1o9+eGvZcR16wyLF0NiotOu7+Vlbh8PCIBHHjG3jwshhBB5TQJOPhBaJ5RLsZdYeW91OH3aLMDpROXLm0ajrVthwgSnXloIIUQ+JQEnH+hYtSOF/QoTUTQa/PzyfNK/9PTta1Ycf/11WL/e6ZcXQgiRz8gYnHyi/8L+/HLkF0792hzvPXvhyBFQyqk1XLoEjRqZ19u3Q1BQZnsLIYRwNTIGR7ic0NqhnL12lnXd6kJkZPqz8uWxoCD46is4dgzGjHH65YUQQuQjEnDyia41uuLv409E2Qtm5K8F3VQArVrBuHFm4PG331pSghBCiHxAuqjykV7zerEtehtRi6uizp6D3buzPigPxMdD69Zw+DDs2gUVKlhShhBCiGySLirhkkLrhHL80nG29mgGe/bAwYOW1OHra7qqYmPNwOPkFciFEEIIR5GAk4/cV/M+fLx8iKhyw2ywqJsKoGZNeO89+OUX+OADy8oQQgjhoaSLKp+5d/a9RF6I5MCsIJS3D2zaZFktWkOvXvDTT/D772ZxTiGEEK5LuqiEywqtE8qhmEPs6dUaNm+G48ctq0Up+OILKFoUBgwwK5ALIYQQjiABJ5/pWasnCkVEbdvAl0WLLK2nVCmYPt0MNh43ztJShBBCeBAJOPlMucLlaFWpFRH//AZ16lg6DidZt27wxBPw7ruwcqXV1QghhPAEEnDyodA6oew4vYO/ereHX3+Fc+esLol33jErjQ8eDDExVlcjhBDC3Tkl4ChFJaVYrRT7lGKPUoyxbS+uFD8rxSHbc7FUx7yoFIeV4oBSdE61valS7LJ99oFSOHe9AQ8QWicUgO8a+pmVxX/4weKKIDAQ5swxa4GOHGkGIAshhBA55awWnATg/7SmDtASGK0UdwAvACu1pgaw0vYe22f9gLpAF+BjpfC2nesTYDhQw/bo4qSfwWOEFA2hSbkmRFzeApUrQ0SE1SUB0LQpTJwI33xj5skRQgghcsopAUdrorXmD9vry8A+oALQE5hp220m0Mv2uicwT2titeYocBhorhTlgCCt2ag1GpiV6hiRDaG1Q9l4fCMnQjvBihVw5YrVJQHw739D27YwerRZMksIIYTICaePwVGKEKAxsBkoozXRYEIQUNq2WwXg71SHHbdtq2B7nXZ7OtdRw5VSW5VSWxMSEhz6M3iC5G6qRXcWNlMKL19ucUWGtzfMmmVuIR840PSgCSGEENnl1ICjFIWAhcBYrbmU2a7pbNOZbL99o9ZTtdbNtNbNfHx8sl+sh6tTqg61S9YmIn6HuVfbRbqpAEJCYMoUWLcO3nrL6mqEEEK4I6cFHKXwxYSbOVqT/Nv0tK3bCdvzGdv240ClVIdXBE7atldMZ7vIgdDaofx6bC1ne3eGpUtNS46LGDAAHnoIwsJg61arqxFCCOFunHUXlQKmAfu05t1UH30PDLa9HgwsTrW9n1IUUIoqmMHEW2zdWJeVoqXtnINSHSOyKbROKIk6kR9alYTLl11qEhql4JNPoGxZE3ZkpQ0hhBDZ4awWnNbAQOBupdhue3QD3gQ6KcUhoJPtPVqzB1gA7AV+BEZrTfJojFHAF5iBx38BrjF4xA01KdeE4CLBRHgfhMKFXWLSv9SKFTPjcQ4dMoOPhRBCCHvJYpv53LM/PcuU36dwdl8PCv/8K0RHm5G+LuTf/4ZJk2DJEuje3epqhBAi/5LFNoXbCK0TSlxiHMs6VIR//oH1660u6TavvgoNGsCjj8KZM1nvL4QQQkjAyef+VfFflClYhoUFj0GBAi51N1WyAgXMLMcXL8KwYTLLsRBCiKxJwMnnvL286VW7F8uOruB6545mHI4LJoh69cwt40uWwNSpVlcjhBDC1UnAEYTWCeVq/FV+7lwdoqLgjz+sLildTz0FnTrBM8/AgQNWVyOEEMKVScARtA9pT1H/okSUOGMGGLtgNxWAlxfMmAEBAfDIIxAfb3VFQgghXJUEHIGftx/317yf7yN/Ir59W5e7XTy18uXh88/N5H8TJlhdjRBCCFclAUcAppvq/I3z/Nq9HuzbB/v3W11ShkJDYehQeP11l7zpSwghhAuQgCMA6FytM4G+gURUsC0R5sKtOACTJ5s1qwYOhEuZrWomhBAiX5KAIwAI8A2gW41ufPf3CpJaNHfZcTjJCheG2bPh2DF4+mmrqxFCCOFqJOCIm0Jrh3Lqyik29mxiBrlERVldUqZatYKXXoKZM+Gbb6yuRgghhCuRgCNu6l6zO37efkRUsa0qvmiRpfXY46WXoHlzGDECTpywuhohhBCuQtaiErfo/nV39v6zlyOfB6JKloI1a6wuKUuHDkGjRqZF56efzO3kQgghHC+rtahUuJoO3Aec0WG6XqrtTwFPAgnAUh2m/5PXtcqvAnGL0NqhRF6IZHtoK/jtN7M+lYurUQPefx9++QU++MDqaoQQIl+bAXRJvUGFqw5AT6CBDtN1gUnOKEQCjrhFj1o98FJeRNQBkpLg+++tLskujz0GPXrACy/Arl1WVyOEEPmTDtNrgZg0m0cBb+owHWvbxynLJvs44yJWK168OGvcoKvFVTQIasDs4z/T8YMPzLpUbvLdPfUUdOxoGp7OngWlrK5ICCE8jo9Samuq91O11lmtEFgTaKvC1WvADeA5HaZ/z7MKbfJFwImJiaF9+/ZWl+E2hgUO46nlT1H2zB/U/uBr000VFGR1WXaJj4du3eDZZ+F//7O6GiGE8DgJWutm2TzGBygGtATuBBaocFVVh+XtIGDpohK36VW7FwARDX0hLg6WL7e2oGzo2hVGj4Z334UFC6BdOzh1yuqqhBAiXzsOROgwrXWY3gIkASXz+qIScMRtKgZVpEWFFkRc+wPKlHH5Sf/SevttqF0bHn0U1q2DiROtrkgIIfK1RcDdACpc1QT8gLN5fVEJOCJdoXVC2Ra9jWOhd8OyZXDjhtUl2S0w0NxVdfWqGSf95ZfSiiOEEM6gwtVcYCNQS4Wr4ypcDQOmA1VVuNoNzAMG53X3FNgxD45SygtoBjTG9KFdAP4EftdaJ+V1gY4g8+Bk36Fzh6j5UU3eCx7B2KGfwQ8/wH33WV2W3Z54AqZOhcRE8PY2EwFOmWJ1VUII4d6ymgfHQddwSO7IMOAopYoAzwHDgDLp7HIG+Bz4n9b6YnaKdzYJODnT4JMGFC1QhLXP7jJLeE+fbnVJdomOhqpVb2108vU1K0+ULWtdXUII4e7yMuA4OndkFnBigKLAZWAzsA+4BAQBdYAWQGEgRmud54OFckMCTs6MXzOeCb9OIPpIb8os/dX08/i4/o13TzwB06aZ8dGpde1qetuEEELkTB4HHIfmjszG4OwB+gKltNb3aq3HaK1ftj3fC5QCHrAVIDxQaJ1QNJrFbUvBuXNmghk3sHHj7eEG4McfzWdCCCFckkNzh6xFJTKktabmRzWpFhTCjyPXweOPu+1aCP/8A61bm5y2bh3UqWN1RUII4X6cMQbHUey6i0opNUgp1SnNtmZKqUF5U5ZwBUopQmuHsjJqDee7321uF09yi3HltylVyizE6ecHnTvD8eNWVySEECIjjsgd9t4mPgP4USk1PtW2AcCX9l5IuKfQOqEkJCWwpENFOHECtm7N+iAXVaWKGYNz4QJ06QLnz1tdkRBCiAzMIJe5Izvz4CjgZaXUF7ZbuEQ+cGeFO6lQuAIRQcfNAOPvvrO6pFxp3BgWLYJDh8zinNevW12REEKIDOQqd2TngG+AXcBQ4AegUHYvJtyPl/Kid+3e/Bi1iqt3tzXdVG4+buvuu2H2bFi/Hh5+GBISrK5ICCFEOnKVO7ITcE4AbYHVQFfbBUU+EFonlBsJN/ixS3U4eBD2uf+Ncw8+CJMnm9ac0aPdPrMJIYQnylXuyFaTj9b6MtAFmJPdY4X7ahvclhIBJYgofRaUcru1qTLy1FPw4otmxuPwcKurEUIIkVZucoe9s7YNBfbaLpYADFRKrQNkXth8wMfLh561evLtvm+J/VdzCnz3Hbz0ktVlOcRrr5n5C8PDzSzHI0daXZEQQggckDtkHhxhl2WHltH96+4sLfAo3V6cDkePQkiI1WU5REIC9OoFy5fDt99C795WVySEEK7JY+bBUUrFZPE456xChbU6VulIYb/CRFS8bDa4+d1Uqfn4wIIF0Lw59O8Pa9daXZEQQuRPjswdmbbgKKWymtVNa6297b2YVaQFxzEeXvgwPx/5meg55fAJKupxSeDcOWjTxizW+dtvUL++1RUJIYRryesWHEfmjqwG7HRI9VgI6DTb7rbnIsIzhNYJ5ey1s6zr1cSsd3D6tNUlOVSJEma9qoIFzcKcUVFWVySEEPmOw3JHpoOMtda/Jr9WSvVKu03kL12qd8Hfx5+IynG01xq+/96sT+VBgoNNyGnb1izpsG6dCT5CCCHyniNzh9zqLexWyK8Qnat1JuKftSRVq+oxt4unVb++yW5Hj8J998G1a1ZXJIQQIrsybcFRSvVI9baabdv9mOmTAdBaf583pQlXFFonlMUHFrO1zwCav7cALl6EIkWsLsvh7roLvv4aHngAHnrIjKn2sXdSBSGEEDniyNxhzyDjzO4j11prl/9rXwYZO8756+cpPak0/1e5H28O+QrmzDHrHXioTz+FUaPg0Ufhiy/MPIdCCJFfOWmQsUNyR1Y7RWVxIZHPFAsoxt1V7mbh+U28Ua4s6rvvPDrgjBxp7qqaMMFMBPjaa1ZXJIQQHs1huSOrQcYhjriI8CyhtUMZuXQku/s+SP1pS8yS3AEBVpeVZ8aPN7Mdv/66CTlPPWV1RUII4ZkcmTtkkLHItp61e6JQRDQqYEbgrlhhdUl5SimYMgV69oQxY8ykgEIIIVxbhgFHKfWrUqqnUso3g899lVK9lFKeNdubyFLZQmVpXbk1EbHboWhRj5rVOCM+PjB3LrRuDQMHwurVVlckhBCexdG5I8NBxkqp80AQcBnYBOyzvS4M1AFa2l5f0Fq79EwhMsjY8d7b+B7PrniWQ1G9qP7dr2bSP990/0x6lPPnzRw5UVFmIudGjayuSAghnCcvBxk7Ondk1kVVFXgbiAXuBcYAL9me7wXigLeA6jn8WYQb613HrEj5XYsg81vfw5ZtyEixYmYiwCJFzGzHR49aXZEQQngMh+aOLFcTV0r5AC2ABkAx4AKwE9istY7PyU/gbNKCkzeaTm2KHz5sfGY3DBliBqrkE3v3mnWrSpaE9euhVCmrKxJCiLznjNXEHZU7sgw4nkACTt54be1rvLT6Jf7e14WKv+2Ev/8Gr/wzbn3DBujY0cx8vGoVFCpkdUVCCJG3nBFwHCX//DYSDtfnjj4ALGpbGk6ehC1bLK7IuVq1gvnzYds26NsX4t2iPVMIIfIHCTgix2qXrE2dknWI8D9qbjPy0LWpMtOjB3z2Gfz0EwwbBklJVlckhBACJOCIXAqtE8qvJ9ZztnNbc7t4PujyTOuxx2DiRJg9G154wepqhBBCgJ0BRynll9eFCPcUWieUJJ3E9/dUgsOHYfduq0uyxLhxMHo0vPMOvPee1dUIIYR7c0TusLcF57RSappS6h6lZLlBkaJx2cYEFwkmoshJM+VvPpj0Lz1KweTJZizOs8+alciFEELkWK5zh70BpwgwFPgJOKGUelcpdWdOLig8i1KK0Dqh/HxiLZfqVIVXXzV3UoWEmJXG8xFvb9NN1a6duWv+55+trkgIIdxWrnOHvQGnHDASWA4UBcYCm5RSB5VSYUqpitm5qPAsoXVCiUuMY5lvpLmVSGs4dgyGD893IcffHxYvhjp1IDTU3GElhBAi23KdO7I9D45SqhLwBdAp1eY44DGt9VfZOpmTyDw4eSsxKZEKL/rR9mgS33yT5sPgYIiMtKIsS508aW4jv3bNzJdTXeb7FkJ4gKzmwVHhajpwH3BGh+l6aT57DngHKKXD9NlsXDNHucPuQcZKqb5KqUXAIeAe20frgReAk5jplUU+5O3lTe+9SSyrAdd90nwYFWVJTVYrX97cOp6UBJ07w6lTVlckhBBOMQPoknajCleVMAHFrl8Kjsgd9nZRnQLmAz0wUya/C9TRWrfVWr8NfAKUtfNcwgOFnivNNT9YUS3NB5UrW1KPK6hVC5YuNeGmWzc4eNCMz5GwI4TwVDpMrwVi0vnoPeA/gL3dRrnOHWn/vZ2RIpiBPl8A32utE9J8/jXgstPYFi9enDVr1lhdhkdT//chhXYP4eOBd1DEv7/Z6OVluqjy+Xc/dy4cOmQW6ezRA1asyNe5Twjh3nyUUltTvZ+qtZ6a2QEqXPUATugwvUOF231DVK5zh70BJ1hrfTyjD7XWJ4ATdp7L6WJiYmjfvr3VZXi80GMfsujsel45vI0F30LZydPMSFvB5MkwZox57e9vViEvK22eQgj3k6C1bmbvzipcBQLjMKuBZ0euc4e9XVRDlFJfKaW8AZRS3kqpWUqpcfYcrBTTleKMUuxOtW28UpxQiu22R7dUn72oFIeV4oBSdE61valS7LJ99oFSyJw8LiS023NcKqBZF6KY0A5z37QA4MCBlK/jxg0YOdLaeoQQwkmqAVWAHSpcRQIVgT9UuMrqn3i5yh1g511USqlTwBqtdb9U2+YAd2uty2V9PHcBV4BZWlPPtm08cEVrJqXZ9w5gLtAcKA/8AtTUmkSl2AKMATYBy4APtGZ5VteXu6jyXsBrAdxIuHHbdn8ff66Pu25BRa4jOhqqVjXBJrXnnoM335QcKIRwH/asJq7CVQiwJO1dVLbPIoFmWd1FldvcAfa34BQGYtNsS7Btz5LWZDToKD09gXlaE6s1R4HDQHOlKAcEac1GrdHALKCXnecUeezI00d4uN7DeJuwjT8+DNgJR7v+ZHFl1ps48fZFOL28YNIkucNKCOFZVLiaC2wEaqlwdVyFq2E5PFWucgfYPwbnCNBHKbUQ2Ay0APrYtufGk0oxCNgK/J/WnAcqYFpokh23bYu3vU67PV1KqeHAcAA/P1lKK6+VK1yOoAJBJGnzm/wGCQTFKcp+/T00ucvi6qy1cSPExd26LSkJKlWC9euhUSMzH2LHjpaUJ4QQDqPDdP8sPg+x81S5zh32tuB8AQQC32HuPf8OCLBtz6lPMH1zjYBo4H+27emNq9GZbE+X1nqq1rqZ1rqZj4+9OU7kxumrpxnVbBQP3PEACsWRWqVg5kyITRvC85c//zSTO6d9REXB779DsWLQqROEhUFiotXVCiGES8h17rA34HwEvAFcxQSNq7b3U7JR7C205rTWJGpNEvA5ZswNmJaZSql2rYj54Y7bXqfdLlxExEMRTOk+hXc7v4uvty+VqzWFs2fh+++tLs1l1asHW7fCoEEwYQLcc4+ZBVkIIfK5XOcOuwKO1jpRaz1Oax0ElNZaB2mtX9Ja5/jfm7YxNcl6w807rL4H+ilFAaWoAtQAtmhNNHBZKVra7p4aBCzO6fVF3qkYVJHHmzzOl2d/5ugd5eHzz60uyaUVLAgzZsCXX8KWLabLasUKq6sSQgjrOCJ32L0WlVKqGtAQKJSmiFlZH8tcoD1QEjgNhNneN8J0M0UCI2whBqUYBzyKGVA0NvlOKaVohpkGOgCzANdTtgHHmZK7qJzvxKUTVPugGo8k3sEX4/+EI0egShWry3J5e/fCgw+a5xdfhPBwkB5WIYSrsOcuKgdeK8e5A+y/Tfw54E3SGQejtXb5m1wl4Fjj6eVP8/HvH3Pw/USqPvmy6YMRWbp2DZ56CqZPh7Zt4euvoWKW6+YKIUTec1bAcUTusDfgnAZKYRbJukCqwb1a68b2lWsdCTjWOHn5JNU+qEb/kyWYvhizqrg0R9jtq6/MhID+/jB7NnTtanVFQoj8zokBJ9e5w95BxgARWusQrXUjrXXj5Ed2Chb5S/nC5RnRdASzSkdz+PoJs7y2sNsjj5gByOXLm8U6n38e4uOtrkoIIZwmV7nD3oDzPlBbKVUqRyWKfOv51s/j6+PHq/f6y2DjHKhdGzZvhuHD4e23oX17c3u5EEJ4uPfJZe6wt4vqKFAZSMQsYZ68qqfWWlfL6cWdRbqorPXsT88yeeP77P9YUWPHcShn1yzbIo158+Dxx8HPz9x1df/9VlckhMhvnNhFlevcYW8LTjBmoI8PZv6ZkFQPITL1fOvnKeBTgAltksxvZpEj/frBH39A5crQo4dZy0q6rIQQHirXucPeFpx2GX2mtf7V3otZRVpwrPfvFf/m3Q2T2Pt9JWptjTSLMYkcuXED/u//4OOPoUULmD8fgoOtrkoIkR84sQUn17nD7nlwbBf0B6pqrffafZALkIBjvTNXz1Dlf5XptSOWOU+ugg4drC7J7X3zDTz2mMmKM2ZAz55WVySE8HTOnAfHdr0c5w67/hmtlApQSk0DrgA7lVIhSqm/lFJPZfeCIn8qXbA0T945mrn1Yd/MSVaX4xEeeMB0WVWrBr16wdixty/qKYQQ7sgRucPefoKJwFDb/kprHQmcBwZks2aRj/273YsE4suEaz/CuXNWl+MRqlUzK5I/9RRMngxt2sDRo1ZXJYQQuZbr3GFvwOkLbMOsAJ5sB1DT3gsJUTKwJE/VGsj8O5LYM/Mdq8vxGAUKwAcfwMKFcPAgNG4MERFWVyWEELmS69xhb8ApBuwFUjeAB5DOFMpCZOa5nm9TMNGLCXs/gWyM/xJZCw2FP/+EmjWhTx/TqhMba3VVQgiRI7nOHfYGnP1AF6AOgFJqNNAL2GfvhYQAKBFYgqeLduabipfYvXKu1eV4nCpVYN06eOYZ+OgjaNUKDh+2uiohhMi2XOcOe28T7wEsgltW7lZAL63193aXaxG5i8q1xJw5Rsj7IXRODOGbt2TASF75/nsYMgQSEuCLL8wq5UIIkRtOvE0817nDrhYc28m6Aj9i0tNyoJs7hBvheoqXDmbMjYZ8GxjJziMbrS7HY/XoYbqs6taFhx6CUaPMHDpCCOHqHJE7sjUPjruSFhzXc/63FYQs60zHoo2JeP4Pq8vxaPHxMG4cvPMONGwICxZA4cJmZuT586FsWasrFEK4C2fPg5Mb9nZRTc/gI621HubYkhxPAo4L0pqwh8owoe4//DniTxqVbWR1RR5v6VIYPNgMPG7RAlavhpEjYcoUqysTQrgLJ3ZR5Tp32BtwkjD9YMmjl5Nfa621tz0XspIEHNd04b03CDnzX9pX6cCi4ausLidfOH7c3G31++/mvb+/mTdHWnGEEPZwYsDJde7wsfNa4aleewP1gR5ARglLiCwVHTScZx98mTD/1fwR/QdNyjWxuiSPV7EiNGliZkBOTDRjcu69F378EcqXt7o6IYS4Kde5I8djcJRSU4EKWuvuOTqBE0kLjuu6OKAPIZW/o23drnz/yFKry/F40dFQtertg439/ODxx+H556FSJWtqE0K4PivH4GQ3d9i7FlXlNI96QC2gdS5qFYIiw0bzfxs0P/y1jK0nt1pdjsebOBGSkm7d5utrlnyYOtU8jxwJkZGWlCeEEIBjcoe9E/0dTfPYAbQBIrNXshBptG/P06dDKB7vw/g1462uxuNt3Hj7gpzx8Wa5h0OHzOrkX34JNWqY10eOWFOnECLfy3XusDfgqDSP68AGYIjdpQqRHi8vggYP5//WJrD00FK2nNhidUUe7c8/zQoZaR9//gnBwfDxx/DXX2bOnK++Mss+DB1qwo8QQjhRrnOHzIMjrHfyJJerV6LKfwrQvEZ7lg1YZnVFAjNe55134NNPza3lDz9s5tOpXdvqyoQQVvHEeXCC7DmZ1vpSrivKAxJw3EDPnrwZt4oXW15h47CNtKzY0uqKhM3p0zBpkmnduX7dzIr80ktmhmQhRP7ixNvEc5077A04ifZdR9t727lTScBxA0uWcKXP/VR5OYgmIS356ZGfrK5IpPHPP/Duu2YRz6tXoW9fE3QaNLC6MiGEszgx4OQ6d+R0DE56D3vPJcTtunShUMny/PtoOVb8tYINf2+wuiKRRqlS8MYb5g6rcePgp5/M0g+hoWYMjxBCOFCuc4e9oWQEEI2ZZKc20NP2fiRQJdVDiJzx8YFHH2X0nIOU8i9B2JowqysSGShRwtxuHhkJYWGwapWZPLBHj5QZkoUQIpdynTvs7aI6BPyqtX4s1bYvgHZa6xo5rd5ZpIvKTRw9ClWr8r/x9/IcK/ht6G+0qdzG6qpEFi5ehA8/NN1X589D167wyivQUoZRCeFxnNhFlevcYW/AiQESgTHAQcxkO5MBL6118RzU7lQScNxIp05c+2s/VZ+Ip27puqwctNLqioSdLl0yA5EnTYJz56BTJ9PC01qmAxXCYzgx4OQ6d9jbRfUNUAKYDWwGZgHFgfnZrFmIzD3+OIFHj/N8yZ6sOrqKtcfWWl2RsFNQELzwgum6evtt2L4d2rSBjh3h11+trk4I4QwqXE1X4eqMCle7U217R4Wr/Spc7VTh6jsVroracapc5w57A85TwKuYGQRjgSPAREyyEsJxevaEEiUYuewfyhYqK2Nx3FChQvDvf5ug8+67sHcvtG8P7drBypVmYkEhhMeaAXRJs+1noJ4O0w0wrTEv2nGeXOcOuwKO1jpOa/2K1rqa1jpQa11Dax2mtY7L+mghsqFAARg8mIBFS3ih4WjWRK5hTeQaq6sSORAYCM88Y5Z7+OADOHwY7rkH2raFFSsk6AjhiXSYXgvEpNm2QofpBNvbTUDFLM/jgNxh97w1SqmBwCigGnAnMB6Yr7V2+QlLihcvzpo1a6wuQ9irUycoX57a/5SmhF8Jxiwaw/sN30cpZXVlIofq1zdLP5w9C6dOwa5dJviUL2+6tuLjzftq1cwNdUIIl+WjlEq9MvJUrfXUbBz/KHZ2M+U2d9j1V4lS6jEg+QfQWusopVR7oCzg8gEnJiaG9u3bW12GyI6JE+HcOcJmvsLTP45Bh2g6VOlgdVXCAWJjYeZMeP11OHYMmjY1c+ysWGFWMp8yxeoKhRCZSNBaN8vJgSpcjQMSgDlZ7uuA3GHvGJxngL+BH1Jt2ww0tvN4IbLn8cfhwAEev34HFQpXIGxNGPlh3bT8oEABGD7cLOA5bZqZIfnHHyEpCaZOlUkDhfBEKlwNBu4DBugwu/4yz3XusDfgBAMrMYN8kl0G7ForQohse+ABCArC/8vZvNjmRdZFreOXI79YXZVwIF9fePRRM29OcrdUQoKZNLBbN/j2W9PaI4RwbypcdQGeB3roMH3NzsNynTvsnQdnr+3lBmAo0AD4BTinta5n78WsIvPguKlRo2DmTGKjjlJ9djMqBVVi/aPrZSyOB4mOhqpV4caNlG0+PlCypBmrU6IEDBxoglD9+tbVKYQwspoHR4WruUB7oCRwGgjD3DVVADhn222TDtMjs7hOrnOHvQHn38BbQNqdn9daT7LnQlaSgOOmtm2DZs1gyhQ+be7FqKWj+HHAj3Su3tnqyoSDPPGE6aaKS3VfhJ+fCTQ9e8L06bBokRmE3KyZ2d6/PxQtalXFQuRvTpzoL9e5w96A4425H300UAi4CkwBxmmt7Vnx01IScNyU1qa/Qinift9EjQ9rUK5QOTYO2yitOB6icWMzIWBajRqljMU5exa+/toEoZ07wd/fLPD56KPQoQN4yTK/QjiNEwNOrnNHlgHHdpHWwCWt9XalVEmt9dlcVe5kEnDc2Mcfw+jRsHUrU9nGiCUjWPbwMrrW6Gp1ZcLJtDahZ/p0mDMHLlyA4GAYOhSGDDGvhRB5yxkBx1G5w94WnFhgltb68eyXaj0JOG7swgUzWcrgwcR9NJmaH9akdMHSbH5ss7Ti5GM3bpiuq+nT4Rfb2POOHU2rTq9eEBBgZXVCeC4ntuDkOnfY27j7K2aiHSGcq2hRc0fVnDn43Yjnpbte4veTv7Ps0DKrKxMW8veHfv3M3DlHj8L48Wam5IcfNnl49GgzhEtmFhDCbeU6d9jbgvMp8Ljtghsx60IAoLWekJsCnEFacNzcb7/BXXfBl18SP3AAtT6qRYnAEmx5bIu04oibkpJgzRrTqrNwoWnladDAtOoMGGDuzBJC5I4TW3BynTvsDThJqd4mH6DMdbS3vQVbRQKOm9Ma6tQxv6HWrWP6n9MZ9v0wvu/3PffXut/q6oQLunAB5s0zYef3382cOz17mrBz773g7fJ/awnhmpwYcHKdO+wNODO4/VYtc1Wth9pzIStJwPEAkyaZJar37CG+Vg1qT6lNkQJF2DZ8m7TiiEzt2gVffgmzZ5s7sipUgMGDzeDk6tWtrk4I9+LEgDODXOaOTAOOUioIiNVau/V8ohJwPMCZM1CxIjz1FPzvf8zYPoOhi4fy3UPf0at2L6urE24gLg6WLDGtOsuXmy6tu+4yrTp9+0JB21/Z0dFmfM/8+VC2rLU1C+Fq8jrgODJ3ZDXI+Dzwuu2iLyul/srtBYXIkdKlTR/DzJkQG8sjDR6hevHqjF8zniSdlPXxIt/z8zPz5yxZAlFR8MYbJswMGQLlypnlzzZuhAkTYN06s96rEMLpHJY7sgo4yvYAKA6E5PRCQuTaY4/BuXOweDE+Xj68ctcr7Di9g0X7F1ldmXAzFSrACy/AgQNmDHvfvjB3LrRqBZ99Zlp3pk83y0UIIZzKYblD5gAV7uOee6ByZfj8cwD61+9PzRI1pRVH5JhS0KaNCTPR0dC+fcpnN25AvXqmJWfPHrnlXAh3Y0/AKaWUagCUAlBK1VdKNUh+5G15QqTi7Q3DhpmZ3Y4evdmKs+vMLiL2RVhdnXBzV67Apk23Bpnz5+GVV0zQqVMH/vtfmV9HCCdwSO7IapBxEhmMYrbRWmsfey9mFRlk7EH+/htCQsxvmokTSUxKpN4n9fDx8mHHyB14KWmUFDmT0cKf/ftDixYQEQGrV0NiolkWIjTUPFq1kvWwRP7hhEHGDssd9vxvqTJ5yP/WwrkqVYIuXUyfQkIC3l7evHLXK+w+s5tv935rdXXCjW3ceGu4AfN+xw4YNQp+/hlOnza3nNevD1OmQNu2ZjzPqFGmYTE+3prahfAwDskdds2D4+6kBcfDfPed+afzDz/AffeRmJRI/U/qo5Ri58ideHvJLG4i7126BMuWmVmTly2Da9egeHHo0cP88ezUySwpIYQncdY8OI4gAUe4n/h405LTogUsXgzA/N3z6bewH3P7zKVfvX4WFyjym+vX4aefTDfW99/DxYtQqBB07w59+kDXrua9EO5OAo6LkYDjgV54wcxuHBUF5cuTpJNo8EkDEnUiu0ftllYcYZm4ODNWZ+FCs+L5P/+YlpzOnU3Lzv33Q7FiVlcpRM64U8CRMTTCPQ0bZkZ7zpwJgJfyIqxdGPvP7mfe7nkWFyfyMz8/E2amTjW3nq9ZYyYR3LrVLBFRunTK52fOWF2tEJ5LWnCE++rQwbTgHDoEXl4k6SQafdqI2MRY9jyxBx8vl7/BT+QjSUkm5CxcaB5//WXuvmrTxnRj9e5tel6FcGUe24KjlApUStVQSgXmVUFC2O2xx+DIEfNPZFJacQ6eO8jcXXOtrU2INLy8oHlzeOstk8l37ICXX4aYGBgzxsxh2aKF+fzw4ZTjoqOhXTuZVVnkT7nJHfauJl4MmAqEptocAYzQWsdk96LOJi04Hur6dShf3tw2PtcEmiSdRJPPmnA1/ir7Ru+TVhzhFg4eNAOUFy40rTxgbkXv0wf27oVvv4WRI82t6UJYyYmriec6d9gbcCKAXmk2a2Cx1jr09iNciwQcD/b002bxoJMnoUQJABbtX0Tv+b2Z0XMGgxsNtrhAIbInKsqEnYgIs05WMm9v+N//TFdW5crW1SfyNycGnFznDnsDziXgH6A3sB+oA3wHlNRaB2V9PNOB+4AzWlPPtq04MB+zkFYk8KDWnLd99iIwDEgEntaan2zbmwIzgABgGTBG60xnPAQk4Hi0nTuhYUN4/33Tzg9orWk6tSkx12OoXKQyCx5YQNlCZa2tU4gcGDIEvvrKjKdPrXp1uPtu8+jQwQxcFsIZnBhwcpU7wP4xOJHAaq31Tq11nNZ6B7AaOJz5YTfNALqk2fYCsFJragArbe9RijuAfkBd2zEfK0XyPb+fAMOBGrZH2nOK/KZBAzOw4fPPby4QpJRifPvxHLt4jHVR65jw6wSLixQi+6KjYf78W8NNgQIwYQLccQfMmwf9+kGZMqY7a8wYMy3UhQuWlSyEI0WSu9yBvQMUvgLGKaW2k5Kk+gDjlVJ3Je+ktV6b3sFas1ap25Y87wm0t72eCawBnrdtn6c1scBRpTgMNFeKSCBIazYCKMUsTPPVcjt/BuGpHnsMhg+HzZuhZUsCXgvgRsINADSaT7Z+widbP8Hfx5/r465bXKwQ9pk40dx5lZrWZrDx4sWQkAB//gkrV8KqVSbjf/CBGczcpAl07GhaeFq3hoJucc+LELfIVe4A+7uoslr8ynadjBfAsgWcJam6qC5oTdFUn5/XmmJK8RGwSWu+sm2fhgkxkcCbWnOPbXtb4HmtuS+DmodjWnvw8/NrGhsbm+XPKdzU5ctQrhw89BBMm0b05WieW/EcC/ctJDYxFm/lzUN1H+J/nf8nXVXCbTRuDNu33769USMTbNKKjTUZf9Uq89i0yUz67esLLVumdGm1aGFagoTICSd2UeU6d9jbghNlx4UcRaWzTWeyPV1a66mYEdgULFjQ8yf7yc8KFzZt9XPnwnvvUS6oHEEFgohPisfHy4eEpAR2nt5JmYJlrK5UCLulF2IyU6AA3HWXeYwfD1evwvr1KYFn4kQID4eAADP3TnLgadIEfORmQ+F6cp077PpjrbUOyc1FMnBaKcppTbRSlAOS5/Q8DqSe7qoicNK2vWI624Uw3VTTpplBC48/zumrpxnZdCTDmw5n8KLB7Di9g7fXv83zbZ63ulIhnKJgQbj3XvMAMzZn7VoTdlauhBdfNNuLFDHz7CQHnrp1TTeXEFZyRO7I1kzGSqmyQClStaZorXfad+xtXVTvAOe05k2leAEorjX/UYq6wNdAc6A8ZgByDa1JVIrfgaeAzZi7qD7UmmVZXVvuosoHtDYDjgMCYMuWWz5K0kkMiBjAvN3zmNVrFgMbDrSoSCFcx+nTZo7M5Bae5MkFS5Uyd2YlB57q1UHZ/saPjjaNpfPnQ1np7c2XnD2Tca5yh51jcOphbumuneajTPu/Uo5nLmZAcUngNBAGLAIWAJUxTVEPaE2Mbf9xwKNAAjBWazOQWCmakXKb+HLgKblNXNw0eTKMHWsGLjRseMtHsQmxdJ3Tld+ifmPZw8voVK2TJSUK4aqioswiocktPCdOmO0VK5qg07Ej/PwzfP21TDqYnzlxDE6ucgfYH3BWAh3S+UhrrV1+2WYJOPnEuXNmZuPhw+HDD2/7+OKNi7T9si1HLxxl7ZC1NC7X2IIihXB9WpsWneTWnVWr4OzZlM+9vODJJ83g5fr1oVYtM5hZeD4nBpxc547sTPS3DdgFjAbKAiuA17XW39hdsUUk4OQjDz8My5ebmY0DAm77+MSlE7Sa3oq4xDg2PLqBKsWqWFCkEO4lKQn69zdLSSTPy6PUzamn8PU1Iad+fahXL+U5OFjG83gaJ0/0l6vcYW/AuQF8DlwB/gMUBT4A7tZaB+ekeGeSgJOPrFpl2tJnz4ZHHkl3l33/7KP19NaUKliK9Y+up2RgSScXKYR7iY6GqlXhxo2UbQEBsHSp+Wz3bti1yzyOHUvZp1AhM2g5dfCpX9+M8xHuyYkBJ9e5w96A8zdmIr7NtgvsxMwkHK+1Lpr90p1LAk4+kpQENWuagQO2VcbTsy5qHffMuofG5RqzctBKAn2zvVCtEPnGE0+YmxTj4lK2+fmZmxfTjsW5dAn27EkJPcnPqbu4Spe+vbWnbl0TiIRrc2LAyXXusDfgfI25dfsh4ACQ/MN9obUent3CnU0CTj7zxhvw3//CgQMm7GQgYl8EfRf05f5a97PwwYWy8rgQGcjupINpaW3u2kobevbsgWvXUvarUuX21p6aNTMe3yN3dTlfVgFHhauUtSfDdD3bttvXngzT57O4Tq5zR7ZuE7ddtDrQHXM31AKtdVIWh1hOAk4+Ex0NlSrB//0fvPVWprt+tOUjnlr+FMObDOfT+z5FqfTmkxRC5IWkJDh69NbQs3u3+bdJ8lgfX1+oXfvW1p769c2K6k8+CZ99Jnd1OZMdAecuTLfSrFQB520gRofpN1W4egEopsO03ZOS5TR3ZBlwlFI+mHUgftJaj7a3IFciAScf6tULNm6E48ezvL3jxV9e5M31bzKxw0Reuusl59QnhMhQbCzs3397i09UVMo+gYFw/bppHfL1hRUrzAzNMitz3rKni0qFqxBgSaqAcwBor8N0tApX5YA1OkzXyuQaDskdWf5R0FonKKW8ALcdpFC8eHHWZDIeQ3igvn2hbVuz+qCfH1SoAMWLp7vrvd738keZP3h59ctcOnGJbuW6OblYIUR6KlQwjy5dzPvERDPQ+fp1OHPGPCfbts10lwUGmkfBguYh6245nI9Samuq91NtSyNlpowO09EAtpBTOrOdHZU77M26k4HXlFJrgA3AzZUrtdZRGR3kKmJiYmjfvr3VZQhnmTMHRoy4tXM/MBCmToUBA9I9pM1dbbhv7n28e+hd2jdrT7caEnKEcFXp3dXl6wuDBsG+fSboJIefwoWhaVNo1gzuvNM8V6mSMjuzyLYErXUzJ1wn17kjt6uJ2z2joJWkiyqfCQm59V7VZMHBEBmZ4WGXYy/TbkY7Dpw7wJrBa7izwp15VqIQIueyuqsrIcEEna1b4fffzfOOHSn7Fytmgk7q0FOxooQeeziji8p2nVznjkx3UkrdBZxIfpveLvZcRAinisog3Ge03aZwgcIsG7CMVtNa0f3r7mwYtoHqxavnQYFCiNzYuPHWcAPm/YYN5rWPT8pdWEOHpny+e/etoeftt1MGM5cufXvokTuzHOZ7YDDwpu15cUY7OjJ3ZNqCo5RKBCZrrZ+194SuSFpw8pkctuAkO3juIK2mtaKof1E2DNtA6YKZdhcLIdzU9euwc2dK4Nm61bT8JNnu0alQ4dbA07QplMxgXtD8csu6HXdR2bf2ZJiOyeD8DssdWQWcJOB9CTjCrcyZY9ajSj0GB8xCnO+9Z9cpNh3fxN0z76Zu6bqsHryaQn4yA5kQ+cGVK2bOn9Sh5+DBlM9DQm4NPU2aQNGiptssP9yyntcT/Tkyd9gTcL4FPspoH6312twWkdck4ORDc+bAuHGmW6pSJbMgzqVLpiO+YkW7TvHDgR/oNb8Xnat1ZnG/xfh6y2qCQuRHFy/CH3/cGnqOHk35vEoV81dNYqIZ7Dx5shkEXayYuXmzWDETgrxdfmnqrDkp4Dgkd9gTcDIbhSyDjIV7OHjQ/FOreXP4+We7/6aZum0qI5aMYGijoUzrMU0mAhRCAHDunLk1/fff4Ysv7Or9pkiRW0NPRs9ptxUqlP0B0HnVZeakgOOQ3GFPwIkDrme0j9a6mD0XspIEHAHAl1/Co4+apRxeeMHuw8JWhzFh7QRevutlJnSYkIcFCiHcTXq3rBcoAAsWmIbjmBg4fz7lOfXr1M8JCRlfw8fn9uCTVVB66y346ivHd5k5KeA4JHfIGByRf2ht/kkTEQHr15vWHLsO0zz+w+NM+3Man3b/lBHNRuRxoUIId5GdhUgzojVcvZp++MkoECV/duGCOT4jAQFw5IjjWnHcaQyOy3cvCeEwSsGnn8KmTfDww2Y2sMKF7ThM8el9nxJ9JZonlj1BucLl6FGrhxMKFkK4uqxuWbeHUqYbqlAhM2QwOxITzfDC1OFn0iRYtcp8lpgIEyd69sDnjGTVgnMUmKa1ftV5JTmetOCIW/z2G7RvD488AjNn2n3Y1birdJjZgd1ndrNy0Er+VelfeVejEELkQHpdZo5sxXFCC47DcodXZh9qrau4e7gR4jZt28JLL8GsWfD113YfVtCvIEsfXkqFoArcN/c+Dpw9kIdFCiFE9k2cmDKPT7LkVhx34MjcYddSDe5OWnDEbRISoF07M7Xp9u3mPk87/RXzF62mtyLQN5ANj26gXOFyeVenEEJkQ+PG5q+0tBo1Mr3yuZXXLTiOJAFH5F+RkdCwIdStC2vXmlsV7LT15Fbaz2hPjRI1+HXIrwQVCMq7OoUQwkW4U8DJtItKCI8WEmKmHt24Mdvtt83KN+PbB79l1+ld9FnQh7jEuKwPEkII4TQScET+1q8fDB4Mr75qBh9nQ5fqXfiixxf8cuQXhn0/jPzQGiqEEO5CuqiEuHzZdFzHxZmlHIplb+7K19a+xkurX+L51s/z5j1v5lGRQghhPemiEsKdFC5s7qaKjoYRIzKfNSsd/237X0Y1G8Vb69/iw80f5lGRQgghskMCjhBgZjWeOBG++cYs6ZANSik+7PohvWr3YsyPY1i4d2EeFSmEEMJe0kUlRLKkJOjUycx0/McfUKtWtg6/Hn+de2bfw7aT2/h54M+0DW6bR4UKIYQ13KmLSgKOEKmdOAENGpg7rDZuNIvKZMO5a+do82UbTl05xfpH13NHqTvypk4hhLCAOwUc6aISIrUKFczKeX/8YWY7zqYSgSX4ccCPBPgE0OWrLhy/dDwPihRCCJEVCThCpNWrF4wcCe+8A7/8ku3Dg4sGs2zAMi7cuEDXOV25cOOCw0sUQgiROemiEiI9165Bs2Zw4YK5dbxUqWyfYuWRlXSd05XWlVvz44AfKeBTwPF1CiGEE0kXlRDuLjAQ5s6Fc+dg2LBs3zoO0LFqR2b0msGayDUMXjSYE5dO0G5GO05dOZUHBQshhEhNAo4QGWnYEN5+G374AT7+OEeneLj+w7zT6R3m75lPtzndWBe1jgm/TnBwoUIIIdKSLiohMqM1dO8Oq1bB1q1Qr162TxHwWgA3Em7ctt3fx5/r4647okohhHAK6aISwlMoBTNmQNGi0L8/XM9+IDny9BH61+uPt/I2p0RxX437ODrmqGNrFUIIcZMEHCGyUrq0CTm7d8N//pPtw8sVLkeRAkXQaHy9fNFolh9ezvzd80nSSY6vVwghhAQcIezSpQs88wx89BEsWZLtw09fPc3IpiP5/fHfGdxwMCUDSzL2p7HcO/te/r74dx4ULIQQ+ZuMwRHCXrGx0KKFme14504oVy7Hp9Ja88UfX/DMT8/g4+XDR90+YkD9ASilHFiwEEI4lozBEcITFShgbh2/ehUGDzZrV+WQUorHmz7OjpE7qFe6HgO/G8iD3z7IuWvnHFiwEELkXxJwhMiOOnVg8mT4+Wd4991cn65a8Wr8OuRX3uj4Bov3L6beJ/VYfmi5AwoVQoj8TbqohMguraFvXzM/zsaN0LSpQ067/dR2Bn43kN1ndjOi6Qgm3TuJQn6FHHJuIYRwBHfqopKAI0ROxMSYVccDA83CnIUcE0RiE2J5efXLTNowiarFqjK792z+VelfDjm3EELkljsFHOmiEiIniheHr76Cw4dh7FiHnbaATwHe7vQ2a4asISEpgTZftmHcynHEJcY57BpCCJEfSMARIqfat4cXX4Rp0+Cbbxx66ruC72LnqJ0MaTiE19e9TssvWrLnzB6HXkMIITyZdFEJkRvx8dCmDRw8aFYdr1zZ4ZdYvH8xj//wOJdiL/F6x9cZ23IsXkr+bSKEcD536qKSgCNEbv31FzRuDI0awerV4O3t8EucuXqG4T8MZ/GBxbQPac+MnjMILhrs8OsIIURmJOC4GAk4Is999RUMHAgTJsDLL+fJJbTWzNg+gzE/jkEpxQddPmBQw0EyOaAQwmmyCjgqXD0DPAZoYBcwVIfp21cbdgJp5xbCER55BAYMgPBw2LAhTy6hlGJo46HsHLWTRmUbMWTxEPos6MM/V//Jk+sJIUR2qHBVAXgaaKbDdD3AG+hnVT0ScIRwlClTzBicAQPg4sU8u0xI0RBWDVrFO53eYemhpdT7pB5LDmZ/fSwhhMgDPkCAClc+QCBw0qpC8kUXVaVKlfTs2bOtLkPkB1evwv795jbyKlXy/HJHrhzh9f2v89fVv+hetjtPVHuCQJ/APL+uECJ/6tChQxym6ynZVK311OQ3KlyNAV4DrgMrdJge4OQSb8oXAUfG4AinevVVMw5n1iwzLiePxSbEMn7NeN7e8DbBRYKZ1XsWbSq3yfPrCiHyn8zG4KhwVQxYCDwEXAC+Ab7VYfor51WYQrqohHC0F1+Eu+6CJ54wd1jlsQI+BXjjnjdYO2QtSinu+vIunv/5eWITYvP82kIIkco9wFEdpv/RYToeiABaWVWMBBwhHM3b29xV5eMDDz9s5spxgtaVW7N9xHYea/IYb294m+ZfNGfX6V1ZHyiEEI4RBbRU4SpQhSsFdAT2WVWMBBwh8kKlSvD557BlC4wf77TLFi5QmKn3T+WH/j9w+sppmn3ejHfWv0NiUqLTahBC5E86TG8GvgX+wIzT8QKmZnpQHpIxOELkpccfN0s5rFwJHTo49dL/XP2HkUtHErEvgraV2zKz10yqFMv7gc9CCM/lThP9SQuOEHnp/fehRg0IDTWtOl5eEBICc+bk+aVLFSzFtw98y8xeM9lxegcNPm3A9D+no7Um+nI07Wa049SVU3lehxBCWEFacITIa6+9Bi+9dOu2wECYOtXMmeMEURejGLJoCKsjV9OjVg+K+Rdj9s7ZjGg6go+7f+yUGoQQ7s+dWnAk4AiR10JC4Nix27cHB0NkpNPKSNJJFHi1AAlJCbd95u/jz/Vx151WixDCPblTwJEuKiHyWlRU9rbnES/lRdTYKLrV6IbCrF+lULSs0JJ9oy270UEIIfKE5QFHKSKVYpdSbFeKrbZtxZXiZ6U4ZHsulmr/F5XisFIcUIrO1lUuhJ0qV05/e7Fi4OQW1HKFy1E5qDJKKXy9fNFoNp3YRIsvWhC+JpwzV884tR4hhMgrlgccmw5a00hrmtnevwCs1JoawErbe5TiDszCXXWBLsDHSuFtRcFC2O2118yYm9S8vCAmBu67D6KjnVrO6aunGdl0JL8//jujmo2iTaU23Fn+Tsb/Op7K71Vm2OJh7D6z26k1CSGEo1k+BkcpIoFmWnM21bYDQHutiVaKcsAaramlFC8CaM0btv1+AsZrzcbMriFjcITl5syBceNMt1TlymY5h/Pn4T//MeHnk0/gwQctLXH/2f1M3jSZmTtmcj3hOp2qduKZls/QuXpnvJSr/FtICGEldxqD4woB5yhwHtDAZ1ozVSkuaE3RVPuc15piSvERsElrvrJtnwYs15pvbz+vGg4MB/Dz82saGyvT1gsXdOAADBpkJgTs18+sSF68uKUlnbt2js+2fcZHWz4i+ko0dUrWYWzLsQxsMJAA3wBLaxNCWMudAo4r/LOstdY0AboCo5Xirkz2VelsSzehaa2naq2baa2b+fj4OKJOIRyvVi1Yvx4mToRvv4V69WD5cktLKhFYgv+2/S+RYyOZ3Xs2/j7+jFgygkrvVeLlVS8Tfdm5XWpCCJETlgccrTlpez4DfAc0B07buqawPSePfDwOVEp1eEUwxwvhtnx8zDw5mzeb1ptu3WDkSLhyxdKy/Lz9eKTBI2wbvo01g9fQpnIbXvvtNYLfD2bwosFsP7Xd0vqEECIzlnZRKUVBwEtrLtte/wxMwCzQdU5r3lSKF4DiWvMfpagLfI0JQeUxA5BraE2mC+3IGBzhNm7cgFdegUmToEoVmDkT2rSxuqqbDsccZvKmyXy5/Uuuxl+lQ0gHnmn5DN1rdpdxOkLkA+7URWV1wKmKabUB8AG+1prXlKIEsACojFmd9AGtibEdMw54FEgAxmpNlu35EnCE2/ntNxg82EwE+NxzMGEC+PtbXdVN56+f5/M/PufDLR9y/NJxapaoyZgWYxjccDAF/dzi7z4hRA5IwHExEnCEW7p82YSbqVOhbl2YPRsaN7a6qlvEJ8azcN9C3t34Lr+f/J1i/sUY0XQETzZ/kgpBFawuTwjhYBJwXIwEHOHWli2Dxx6Df/6BsDB44QUzbseFaK3Z8PcG3tv0Ht/t/w4v5cWDdR/kmZbP0Kx8s6xPIIRwCxJwXIwEHOH2YmJg9GiYNw9atDBjc2rVsrqqdB09f5QPNn/AtD+ncTnuMm0rt+WZls/Qo1YPvL1kXk4h3JkEHBcjAUd4jPnz4Ykn4Pp1eOstE3q8XHNw78UbF5n25zQ+2PwBxy4eo2qxqoxpMYahjYZSuEBhq8sTQuSABBwXIwFHeJSTJ02X1fLl0LEjfPklVKqU9XEWSUhKYNH+Rby78V02Ht9IkQJFeLzJ4zzV4ikqFzHrdEVfjqbfwn7M7zufsoXKWlyxECIjEnBcjAQc4XG0hi++gGefNS04H3xgZkRW6c2F6To2H9/Me5ve49u9ZvLxPnf04dmWzzJzx0w+2/YZI5qO4OPuH1tcpRAiIxJwXIwEHOGxjhyBIUPMbeW9esFnn0Hp0lZXlaWoi1F8uPlDJm2clO7n/j7+XB933clVCSGy4k4BxzU774UQ9qlaFVavhnfeMXdb1asH332X9XEWq1ykMu/c+w4HnzxI03JNUalWYakYVJHJXSZzLf6ahRUKIdydBBwh3J23t5kv548/oGJFCA01kwRevGh1ZVmqUaIGd5a/E6UUft5+AMRci2HEkhGUfqc0AyIG8MOBH4hLjLO4UiGEu5EuKiE8SVwcvPoqvP46lC9vBiB37Gh1VZkKnR9KuULlGN50OFO3TeXk5ZM83eJp5u2ex7f7viXmegxF/YvSp04f+tfrT/uQ9nK7uRAWcacuKgk4QniiLVvMoOMDB+Cpp+DNNyEw0Oqqsi0uMY5fjvzC3N1zWbR/EVfirlCmYBkerPsg/er1418V/4Vy8YHVQngSCTguRgKOyJeuXYP//hcmT4aaNWHWLDNJoJu6Hn+dpYeWMm/3PJYcXEJsYizBRYJ5qO5D9K/fn4ZlGkrYESKPScBxMRJwRL62ahUMHQrHj8OLL0KNGmbJh6goqFwZXnsNBgywuspsuRR7icX7FzNvzzxW/LWChKQEapWoRf96/elXrx+1SrrmLM9CuDsJOC5GAo7I9y5ehLFjYcYMM1dO6v/vAwPNgp5uFnKSnb12loh9EczdPZdfI39Fo2lctjH96vXjoboPEVw02OoShfAYEnBcjAQcIWxKlzaLdqYVHAyRkU4vx9FOXj7Jgj0LmLd7HptPbAagVaVW9K/XnwfueIAyhcpYXKEQ7k0CjouRgCOEjZfXra03yZSCK1fcciByRo6cP8L83fOZu3suu87swkt5cXeVu+lXtx+hdUIpFlDM6hKFcDsScFyMBBwhbEJC4Nix9D8rVAj69DFdVXffbebX8RB7zuxh3u55zNszj8Mxh/H18qVL9S70q9ePHrV6UMiv0M19ZV0sITImAcfFSMARwmbOHBg+3NxhlSww0IzPOX0avvkGLl2CsmWhXz945BFo0sTl17iyl9aabdHbmLd7HvP3zOf4peME+ARwf6376V+vP12rd+WZn56RdbGEyIAEHBcjAUeIVObMgXHj0r+L6sYNWLrU7LN0qZk4sFYt8/mAAWZpCA+RpJNYH7Weebvn8c3eb/jnWjpjk5B1sYRITQKOi5GAI0QOnD8P335rws6vv5pt//qXCToPPgilSllbnwMlJCXwzZ5vGLdqHEcvHL25vXyh8oxuPpqH6j5EteLVLKxQCNcgAcfFSMARIpeiomDuXBN2du0CHx+4917ThdWjBxR0i7/vsjRqySim/jEVHy8f4hLjCCoQxKXYSwBUL16drtW70rV6V9qHtCfAN8DiaoVwPgk4LkYCjhAOtGuXCTpz5pjJAwsWhN69Tdjp2NGEHzeVdl2s6CvRvNPpHZYfXs7yw8tZfXQ11xOu4+/jT/uQ9jcDT40SNawuXQinkIDjYiTgCJEHkpLgt99M0PnmG7hwwcyz06+f6ca6806PGZyc7Hr8ddYeW3sz8Bw8dxCAasWqmbBTw7TuBPp6zu32QqRmT8BR4aoo8AVQD9DAozpMb3RCebfWIQFHCJFrsbGwbJkJO0uWmPc1aqQMTq5e3eoK88SR80dYfsiEnVVHV91s3WkX3O5m4KlRvIaskSU8hp0BZybwmw7TX6hw5QcE6jB9wSkFpq5DAo4QwqEuXICFC03YWbPGTCzYvLkJOg89BGU8czbhGwk3TOuOLfAcOHcAgKrFqt7syupQpYO07gi3llXAUeEqCNgBVNVh1gaMfBFwKlWqpGfPnm11GULkP/HxEBMD587Bddut1kFBUKIEFC1qZlaOiYETJ8wt6X5+UKECFC9uadmOEH09ms0xm9kSs4U/L/zJjaQb+CpfGhZtSIviLWhevDmVAipJ645wKx06dIgDdqXaNFVrPTX5jQpXjYCpwF6gIbANGKPDtNNbGfJFwJEWHCFcwJ49KYOTo6LMBIMNG8Iff5gurWRuvvhnem4k3OC3Y7/dHLuz/+x+AKoUrXKzK6tDSAcK+rnF2E2Rj9nRgtMM2AS01mF6swpXk4FLOky/7LQik2uRgCOEcKqkJFi/3gSdzz8379OqXDnjJSU8QOSFyJtdWSuPruRa/DX8vP1ujt3pUr0LtUvWRiklS0cIl2JHwCkLbNJhOsT2vi3wgg7T3Z1UYkotEnCEEJbJaPFPMPPstG4NrVpBixZQuLBza3OS2IRYfov67Wbg2Xd2HwAhRUPoUq0LkRcjWXF4BSOaydIRwnp2DjL+DXhMh+kDKlyNBwrqMP1vpxSYug4JOEIIy2S0+GehQlClCuzebQKQl5fpzmrdOiX0VK7s9HKd4diFYyw/vJzRy0aTpG9v3fL18uXAkwcIKRoi43eE09kZcBphbhP3A44AQ3WYPu+E8m6tQwKOEMIyGS3+mTwG58IF2LzZdGmtX29eJ/+/XLFiSuBp3RoaNHDrSQbTir4czTM/PcOi/YuITYzFS3nhhRcJOgGAcoXK0bpya1pXMo9GZRvh6+1rcdXC08lEfy5GAo4QLiyzxT/TSkiAHTtgw4aU0HP8uPmsYEHTlZUceFq2hCJFnPdz5IHkpSP8vP2IS4zj8SaPM6rZKNb/vd48otZz7KJpAQv0DaR5heY3A8+/Kv2Lov5Frf0BhMeRgONiJOAI4cGiokzQSQ49O3aYgctKQf36pjsrOfSEhLjV7MrpLR0R8VDELfucuHTiZthZ//d6tp/aTqJORKGoW7ruzcDTunJrqhStIt1aIlck4LgYCThC5COXL6d0a23YABs3mm0A5cqljOFp3RoaNwbfVN062WlNclFX4q6w5cSWm4Fn4/GNNxcMLVuo7C2Bp3HZxtKtJbJFAo6LkYAjRD6WmGgGKyd3aa1fnzKwOSDAzLLcurWZi+fjj1MmJASPmJMnMSmRPf/suRl41v+9nsgLkQAE+ARwZ4U7b4aeVpVaUSygmLUFC5cmAcfFSMARQtzixIlbx/H8+acJQumpUAH+/tuturaycvLyyVsCz5/Rf5Kozc9/R6k7bmnlqVas2s1uLZmTR0jAcTEScIQQmbp61cyzk9Hfh4UKQZ06cMcdtz5CQswt7G7uatxV061lCzwb/97IxdiLAJQpWIZWlVrRulJr1v+9nsUHFjOiqczJk19JwHExEnCEEFnKaE6e4sXhkUdg717zOHky5bOAAKhd+/bgU7WqW9+ynqST2HNmz83AM2fnHDS3/67wVt580v0TapWsRc0SNSlTsIwMYvZwEnBcjAQcIUSWspqTJ9mFC7BvX0rgSX5ERaXs4+cHtWrdHnyqVzefuZnoy9GMXjaapYeWEpcYh7fyppBfIa7HXycuKe7mfkEFgqhVoha1StaiVgkTemqVqEWNEjVkFXUPIQHHxUjAEULYJTd3UV2+DPv33x58jh5N6fry8YEaNaBu3VuDT82aUKCAY+txsLRz8oxoOoIPu37I35f+5sDZAxw4d+Dm88FzB/n70t+3HF+5SGUTfpKDjy0EVSpSCS/l/t18+YUEHBcjAUcIYZlr1+DAgduDz+HDKQuNenmZ1p3UoScy0gQaF7mry545eVK7GneVQzGHUsKPLfgcOHuAy3GXb+4X4BNAjRI1brb2pG4BKuKf+USNMujZ+STguBgJOEIIl3PjBhw6dHvwOXjQzNickeLF4auvoFIl83Cz2Zq11py6cupmi8/BcwdvBqCj54/evJsLzADnm8GnZEr4qVK0Cr7evjyx9Ak+2/aZDHp2Igk4LkYCjhDCbcTHm9adunUzvqsrtcKFTdCpXDkl9KR+VKxoWn7cQFxiHH/F/JUSelK1/py9djbL4/19/Lk+7nqW+4mck4DjYiTgCCHcTkZ3dVWoAAsWmLl50nucPn37MSVKpB9+kh8VKmQ9+Nni8UAx12NudnFti97Gov2LOH7p+C13dxXwLkD9MvVpULoBDcs2pGGZhjQo00AmL3QgCTguRgKOEMLt2HtXV1qxsWYiw6iojEPQ+fO3HqMUlCmTcQDauhVeeCH7teSh1IOeYxNiaR/SnsZlG7Pj9A52nN5xS4tPpaBKNCjTgIZlGtKwrAk9NYrXwNvL25La3ZkEHBcjAUcI4ZbyqtXk6tWMw0/y48qVrM9TuDCMHWvGBRUrlvKc+rW/f+7rTUfopDspt3U/w3+9wtR2hYhuVpuI534HUsb57Di9g52nd9583vfPvptjfPx9/KlXut7NVh5p7bGPBBwXIwFHCCGyQWu4eDEl7HTvnvG+SmU+Vigg4PbQk14QSrutaNGMJ0vMYetWbEIse//Ze0voSa+1p2HZhje7uaS151YScFyMBBwhhMiFjMYDBQfDkSMmDJ0/DzEx5jn167TPqV9n1UoUFJR+EJo/Hy5dun3/ChXMXWgBAXavHZa6tWfHqR3sPLOTHad2sP/s/nRbe5JbetK29uSXW9Yl4LgYCThCCJELOR0PlJW4ODMztL2BKPn51KnMz1uggAlCJUqY59Sv09uW/Dog4OYpstXa848Xv+/+iV/Kx/LwX4F80Oldgh4Zho+X+y7XkREJOC5GAo4QQuSSC82qTHDwrUtjJCteHP7zHxOEzp279Tn5dWxsxuf19880AOlixYgOUuz0jWFHUjQ7b0Qy969F6azSZRTyK0RR/6IUKVDEPPsXufW97Tndz/yLEOATkLO1vebMIfrV5+nX8gTzN1Wk7EtvOuy/lQQcFyMBRwghPEhOW5S0NjNDZxaAMnodF5fuKaMLwTOdYXFtuOELfglQ/wy0j/IisUJ5LvolccEvkYs+SVzwSeCidzwXvOO56BVPgkrK9Mf0xZsiXoEU9Q6kiHdBivoUoqhvYYr4FaaoXxBF/IJSwlFAcYoEFqPopu0UeXsyrzaPZUYjGLENPl7tuDveJOC4GAk4QgjhYZzZoqS1CVPpBaCRIxnVHaY2Bb9EiPO2hYqlQNu2ZuLGuDjzSH4dH4+Oi+VaUhwXveJM4PFO4II/XPTHPBcwz+ltS35/NRvrtvonKK5PzDxQ2UMCjouRgCOEECJPhIQQ2uIY5a7A8G0m6EQXgojNwWY9MXtpbZboSB2EMnpte06Ivc7FGxe4eOMiF25c4GLcZY589hZfNIVt5SHeGwLjoPd+mLQCyl7O/e97dwo4njcCSgghhHCW114jIlV32ZRl2LrLXsveeZQCX1/zsJMPUML2SNbhzXlsPXWMLRXAPx5u+EBQLJQtEZy9ejyArFEvhBBC5NSAAWZ8S3CwCSnBwZbO8Mxrr3E6yIuRW2HTFzByK5wK8jJdePmMdFEJIYQQniQPxye5UxeVBBwhhBBC2MWdAo50UQkhhBDC40jAEUIIIYTHkYAjhBBCCI8jAUcIIYQQHsctA45SdFGKA0pxWClesLoeIYQQQrgWtws4SuENTAG6AncA/ZXiDmurEkIIIYQrcbuAAzQHDmvNEa2JA+YBPS2uSQghhBAuxB0DTgXg71Tvj9u23UIpNVwptVUptTUhIcFpxQkhhBDCeu64FpVKZ9ttsxVqracCU8FM9JfXRQkhhBACVLjyBrYCJ3SYvs+qOtyxBec4UCnV+4rASYtqEUIIIcStxgD7rC7CHQPO70ANpaiiFH5AP+B7i2sSQggh8j0VrioC3YEvrK7F7bqotCZBKZ4EfgK8gelasyezY4oXL86aNWucUZ4QQgjhyXyUUltTvZ9qGxKS7H3gP0Bhp1aVjnyx2KZSKgm47uDT+gAyejlvyXect+T7zXvyHec9+Y7zVtrvN0BrnW7vjwpX9wHddJh+QoWr9sBzVo7ByRcBJy8opbZqrZtZXYcnk+84b8n3m/fkO8578h3nrex8vypcvQEMxAQifyAIiNBh+pE8LDFDbtdFJYQQQgjXo8P0i8CLAKlacCwJN+Ceg4yFEEIIITIlLTg5NzXrXUQuyXect+T7zXvyHec9+Y7zVo6+Xx2m1wBrHFpJNskYHCGEEEJ4HOmiEkIIIYTHkYAjhBBCCI8jAScLSqkuSqkDSqnDSqkX0vlcKaU+sH2+UynVxIo63ZUd3+8A2/e6Uym1QSnV0Io63VlW33Gq/e5USiUqpfo6sz5PYM93rJRqr5TarpTao5T61dk1ujM7/p4oopT6QSm1w/b9DrWiTnellJqulDqjlNqdwefu+XtOay2PDB6YmZL/AqoCfsAO4I40+3QDlmMWAW0JbLa6bnd52Pn9tgKK2V53le/X8d9xqv1WAcuAvlbX7U4PO/8cFwX2ApVt70tbXbe7POz8fv8LvGV7XQqIAfysrt1dHsBdQBNgdwafu+XvOWnByVxz4LDW+ojWOg6YB/RMs09PYJY2NgFFlVLlnF2om8ry+9Vab9Ban7e93YRZXFXYz54/wwBPAQuBM84szkPY8x0/DERoraMAtNbyPdvPnu9XA4WVUgoohAk4MruxnbTWazHfWUbc8vecBJzMVQD+TvX+uG1bdvcR6cvudzcM868IYb8sv2OlVAWgN/CpE+vyJPb8Oa4JFFNKrVFKbVNKDXJade7Pnu/3I6AOcBLYBYzRWic5p7x8wS1/z8k8OJlT6WxLe1+9PfuI9Nn93SmlOmACTps8rcjz2PMdvw88r7VONP8AFtlkz3fsAzQFOgIBwEal1Cat9cG8Ls4D2PP9dga2A3cD1YCflVK/aa0v5XFt+YVb/p6TgJO540ClVO8rYv6FkN19RPrs+u6UUg2AL4CuWutzTqrNU9jzHTcD5tnCTUmgm1IqQWu9yCkVuj97/544q7W+ClxVSq0FGgIScLJmz/c7FHhTmwEjh5VSR4HawBbnlOjx3PL3nHRRZe53oIZSqopSyg/oB3yfZp/vgUG2UeYtgYta62hnF+qmsvx+lVKVgQhgoPxrN0ey/I611lW01iFa6xDgW+AJCTfZYs/fE4uBtkopH6VUINAC2OfkOt2VPd9vFKZ1DKVUGaAWcMSpVXo2t/w9Jy04mdBaJyilngR+wozkn6613qOUGmn7/FPMXSfdgMPANcy/JIQd7Px+XwFKAB/bWhgStKwcbDc7v2ORC/Z8x1rrfUqpH4GdQBLwhdY63Vtyxa3s/DM8EZihlNqF6U55Xmt91rKi3YxSai7QHiiplDoOhAG+4N6/52SpBiGEEEJ4HOmiEkIIIYTHkYAjhBBCCI8jAUcIIYQQHkcCjhBCCCE8jgQcIYQQQngcCThC5GNKqSFKKa2U2p6NY2bYjhmfy2uvsZ1nSG7Ok81rtrdd84ITruWQ70kIkTMScIRwYUqpSNsvSa2Uap1qe9tU2yMtLDFLqUJFZJqPvgUmY1bZdltKqZDk/xZW1yKESCET/QnhPkYB622vR1pZiCNorT+yugYhhOeSFhwh3MN5oK9SqqRSqhTQx7btFrbWhG+UUtFKqfNKqdVKqRapPi+vlFqhlLqqlPoNqJLm+NtaW7LqSlJKdVJK/amUuqiUildKHVNKhSefD1ht2zU4dUtH2vMqpXyVUi8qpfbb6tunlHpGKeVl+zy5O22dUuo9pdQFpdQJpdSAjL40pVQRpdR8pdQlpdQOoEk6+1RWSs2zneuC7fupl+rz5Fa055VSu5RSl5VS3ymlSiilQoCjqfZNblULSXWJEkqpCKXUNaXUTqVUo4zqFUI4jgQcIdzDTKAA8KjtUQCYkXoHpVRBYBXQF7OI4yrM9OurlFLVbLt9DXTCrN1zFHjeAbVVAM4C84DZQGHgFaVUP8wifQtt+13GdElNzuA8rwGv246fh1n48910amxte2wBygOfKaWCMjjnB8CDwEVgG2YK+puUWRdqlW2fncDPmO9stVKqZJpzvYRZF+ks0AuYClwCvky1T/LPl3oV69GY5QOOAvWBDzOoVQjhQBJwhHAPv2LGqgy3PfYCa9Ps0x3TInMEaK+17gMsAgKBYUqpikA72773aq0HAVMcUNss4D3gb0yQ+Mu2/W6t9WEguSsqRms9Vms9Nu0JlFlo7Anb24e11sOAx2zvn0qzewxwF+bnTQQKAjXTOac3ZmHG5HM+igkpqXUHqmFWRj4AnMCEv5KYoJjaS7Zz9LK9DwXigAnJOyT/fFrrmFTHLdda9waetL1vnLZWIYTjyRgcIdzHp5gWCbj9lz5AiO35gE5ZZG6/7TkY09ICcF1r/bfttT0rtHtn8fknmNCVVik7zp1634K218mrbCfXXk6ZVaST7dNa3wBQSl0FgoBC6ZyzJJB83AHbc9qfN8T2XAEYk+az6mnep60r+bjYdK6d2p+25wu254IZ7CeEcCBpwRHCfczCrOR7FdMVlFak7bmmrUUEoJbt+RimdQIgQClVKXnfNOe4ansuDGZcTDr7pPWQ7XkIJgx9YnufXEOi7Tmzv2/+SXXt2mlqj9Zax6XaNyHV68zuXDqLaWFJfa60P0uk7Xkb4KW1VlprBRTDdJmlVidNfWC+0+Sfj+TxQmkk1yt3WQnhRNKCI4Sb0FpfVErdlep12l2WYn5hV8OMITkL9AauA9O11seVUmsx3TsrlFK/kxJOkh3EhKjiSqlZQFmgdBalnQaKAE8D99qumVpya1FFpdQXwCGt9VtpfjatlPoEeA74Win1I9DD9nGO7rbSWicqpeYDA23n/Jnbu52WYbr0mgLrlVI7gcqYcTjdgDWp9p2olGoIdLC9/05rfUUpFYcJUn626xzTWjtibJMQIhekBUcIN6K13qa13pbBZ1eBjphBvbWBezBjdzraxsIADAB+wXRZ1cQM4k19jouYW9BPAl0w42k2ZVHWY5humzswLT+fpTlnJDAJMz5nGCZwpGcc8DImYD2MGWvzb+CtDPa3x9OY+XaKAs2BN9LUlvydzcUEm8GY1p6vSOnWSjYecxdWKeB7bN1yttal5zGtUA9hBhULISymUrrqhRBCpGW7ZT4Y6KC1XmNtNUIIe0kLjhBCCCE8jgQcIYQQQngc6aISQgghhMeRFhwhhBBCeBwJOEIIIYTwOBJwhBBCCOFxJOAIIYQQwuNIwBFCCCGEx/l/h+Dj19Ud5QwAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "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", "modulation_depth = np.arange(0, 1.0, 0.08)\n", "\n", "w_xs = w_x * convert_modulation_depth_to_alpha(modulation_depth)[0]\n", + "new_aspect_ratio = w_xs / w_z\n", "\n", "v_x = np.zeros(len(modulation_depth))\n", "v_y = np.zeros(len(modulation_depth))\n", "v_z = np.zeros(len(modulation_depth))\n", "\n", "for i in range(len(modulation_depth)):\n", - " v_x[i] = calculateTrapFrequency(w_xs[i], w_z, Power, Polarizability, dir = 'x').value\n", - " v_y[i] = calculateTrapFrequency(w_xs[i], w_z, Power, Polarizability, dir = 'y').value\n", - " v_z[i] = calculateTrapFrequency(w_xs[i], w_z, Power, Polarizability, dir = 'z').value\n", + " v_x[i] = calculateTrapFrequency(w_xs[i], w_z, Power, dir = 'x').value\n", + " v_y[i] = calculateTrapFrequency(w_xs[i], w_z, Power, dir = 'y').value\n", + " v_z[i] = calculateTrapFrequency(w_xs[i], w_z, Power, dir = 'z').value\n", "\n", "plotTrapFrequencies(v_x, v_y, v_z, modulation_depth, new_aspect_ratio, plot_against_mod_depth = True)" ] @@ -393,23 +300,10 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "7a85ec41", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "modulation_depth = [0.5, 0.3, 0.7, 0.9, 0.8, 1.0, 0.6, 0.4, 0.2, 0.1]\n", "w_xs = w_x * convert_modulation_depth_to_alpha(modulation_depth)[0]\n", @@ -460,9 +341,9 @@ "v_z = np.zeros(len(modulation_depth))\n", "\n", "for i in range(len(modulation_depth)):\n", - " v_x[i] = calculateTrapFrequency(w_xs[i], w_z, Power, Polarizability, dir = 'x').value / 1e3\n", - " v_y[i] = calculateTrapFrequency(w_xs[i], w_z, Power, Polarizability, dir = 'y').value\n", - " v_z[i] = calculateTrapFrequency(w_xs[i], w_z, Power, Polarizability, dir = 'z').value / 1e3\n", + " v_x[i] = calculateTrapFrequency(w_xs[i], w_z, Power, dir = 'x').value / 1e3\n", + " v_y[i] = calculateTrapFrequency(w_xs[i], w_z, Power, dir = 'y').value\n", + " v_z[i] = calculateTrapFrequency(w_xs[i], w_z, Power, dir = 'z').value / 1e3\n", "\n", "fx = [0.28, 0.690, 0.152, 0.102, 0.127, 0.099, 0.205, 0.404, 1.441, 2.813]\n", "dfx = [0.006, 0.005, 0.006, 0.003, 0.002, 0.002,0.002, 0.003, 0.006, 0.024]\n", @@ -484,23 +365,10 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "d15205ff", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "AtomNumber = 1.00 * 1e7\n", "BField = 1.4 * u.G\n", + "Power = 40*u.W\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", "modulation_depth = np.arange(0, 1.0, 0.08)\n", "\n", "w_xs = w_x * convert_modulation_depth_to_alpha(modulation_depth)[0]\n", @@ -548,9 +406,9 @@ "PSD = np.zeros(len(modulation_depth))\n", "\n", "for i in range(len(modulation_depth)):\n", - " # n[i] = particleDensity(w_xs[i], w_z, Power, Polarizability, N = AtomNumber, T = Temperatures[i], m = 164*u.u).decompose().to(u.cm**(-3))\n", - " Gamma_elastic[i] = calculateElasticCollisionRate(w_xs[i], w_z, Power, Polarizability, N = AtomNumber, T = Temperatures[i], B = BField).value\n", - " PSD[i] = calculatePSD(w_xs[i], w_z, Power, Polarizability, N = AtomNumber, T = Temperatures[i]).decompose().value\n", + " # 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)" @@ -566,24 +424,16 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "id": "6c81d9da", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "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", @@ -648,40 +498,14 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": null, "id": "7b8191f2", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "Power = 40*u.W\n", - "Polarizability = 184.4 # in a.u, most precise measured value of Dy polarizability\n", "Wavelength = 1.064*u.um\n", - "w_x, w_z = 27.5*u.um, 33.8*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", @@ -690,7 +514,7 @@ " 'delta': 70, # angle between arms in degrees\n", " 'modulation': False,\n", " 'aspect_ratio': 5, # required aspect ratio of modulated arm\n", - " 'gravity': False,\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", @@ -717,23 +541,23 @@ "for i in range(len(w_x)):\n", " \n", " options['axis'] = 0\n", - " ExtractedTrapFrequencies = computeTrapPotential(w_x[i], w_z, Power, Polarizability, options)[5]\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, Polarizability, options)[5]\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, Polarizability, options)[5]\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, Polarizability, dir = 'x').value\n", - " #v_y[i] = calculateTrapFrequency(w_x[i], w_z, Power, Polarizability, dir = 'y').value\n", - " #v_z[i] = calculateTrapFrequency(w_x[i], w_z, Power, Polarizability, dir = 'z').value\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", @@ -772,23 +596,12 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "id": "3950f1b5", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Particle Density = 1.87E+12 1 / cm3\n", - "Elastic Collision Rate = 37.24 1 / s\n", - "PSD = 2.50E-05 \n" - ] - } - ], + "outputs": [], "source": [ "Power = 9.5*u.W\n", - "Polarizability = 184.4 # in a.u, most precise measured value of Dy polarizability\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", @@ -802,9 +615,9 @@ "new_aspect_ratio = w_x / w_z\n", "Temperature = 33 * u.uK\n", "\n", - "n = particleDensity(w_x, w_z, Power, Polarizability, N = AtomNumber, T = Temperature, m = 164*u.u).decompose().to(u.cm**(-3))\n", - "Gamma_elastic = calculateElasticCollisionRate(w_x, w_z, Power, Polarizability, N = AtomNumber, T = Temperature, B = BField)\n", - "PSD = calculatePSD(w_x, w_z, Power, Polarizability, N = AtomNumber, T = Temperature).decompose()\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", @@ -821,23 +634,10 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "id": "b11b6aae", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "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", @@ -869,32 +669,18 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "id": "f17a4d01", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "Powers = [35, 11] * u.W\n", - "Polarizability = 184.4 # in a.u, most precise measured value of Dy polarizability\n", + "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 = [32, 67]*u.um # Beam Waists in the y direction\n", + "w_x = [30, 67]*u.um # Beam Waists in the x direction\n", + "w_z = [30, 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", + " 'axis': 0, # 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,\n", " 'delta': 70, # angle between arms in degrees\n", @@ -909,7 +695,7 @@ " 'extract_trap_frequencies': False\n", "}\n", "\n", - "Positions, TrapPotential = computeTrapPotential(w_x, w_z, Powers, Polarizability, options)\n", + "Positions, TrapPotential = computeTrapPotential(w_x, w_z, Powers, options)\n", "\n", "plt.figure()\n", "plt.plot(Positions[options['axis']], TrapPotential[options['axis']], label = 'Crossed beam potential')\n", @@ -929,20 +715,10 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "id": "09149423", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "v_x = 442.04 Hz\n", - "v_y = 459.15 Hz\n", - "v_z = 637.34 Hz\n" - ] - } - ], + "outputs": [], "source": [ "Powers = [1, 11] * u.W\n", "w_x = [30, 50]*u.um # Beam Waists in the x direction\n", @@ -951,17 +727,17 @@ "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,\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,\n", + " 'modulation': False, # Flag for spatial modulation of a single beam\n", " 'aspect_ratio': 5, # required aspect ratio of modulated arm\n", - " 'gravity': False,\n", - " 'tilt_gravity': False,\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,\n", + " 'astigmatism': False, # Flag for astigmatism of beam\n", " '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", - " 'extract_trap_frequencies': False\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", @@ -979,7 +755,28 @@ "id": "712ec2c7", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "Powers = [1, 11] * u.W\n", + "w_x = [30, 50]*u.um # Beam Waists in the x direction\n", + "w_z = [30, 50]*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", + " '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", + " 'disp_foci_crossed': [2.5*u.mm, 1.5*u.mm], # astigmatism of each of the two beams in the cODT\n", + " 'extract_trap_frequencies': False # Flag to extract trap frequencies by fitting the computed potential\n", + "}" + ] } ], "metadata": { diff --git a/calculateDipoleTrapPotential.py b/calculateDipoleTrapPotential.py index 94f5e7c..b6a3f6e 100644 --- a/calculateDipoleTrapPotential.py +++ b/calculateDipoleTrapPotential.py @@ -87,10 +87,10 @@ def calculateAtomNumber(NCount, pixel_size = 5.86 * u.um, magnification = 0.5, e def meanThermalVelocity(T, m = 164*u.u): return 4 * np.sqrt((ac.k_B * T) /(np.pi * m)) -def particleDensity(w_x, w_z, Power, Polarizability, N, T, m = 164*u.u): # For a thermal cloud - v_x = calculateTrapFrequency(w_x, w_z, Power, Polarizability, dir = 'x') - v_y = calculateTrapFrequency(w_x, w_z, Power, Polarizability, dir = 'y') - v_z = calculateTrapFrequency(w_x, w_z, Power, Polarizability, dir = 'z') +def particleDensity(w_x, w_z, Power, N, T, m = 164*u.u): # For a thermal cloud + v_x = calculateTrapFrequency(w_x, w_z, Power, dir = 'x') + v_y = calculateTrapFrequency(w_x, w_z, Power, dir = 'y') + v_z = calculateTrapFrequency(w_x, w_z, Power, dir = 'z') return N * (2 * np.pi)**3 * (v_x * v_y * v_z) * (m / (2 * np.pi * ac.k_B * T))**(3/2) def calculateParticleDensityFromMeasurements(v_x, dv_x, v_y, dv_y, v_z, dv_z, w_x, w_z, T_x, T_y, dT_x, dT_y, modulation_depth, N, m = 164*u.u): @@ -167,11 +167,11 @@ def dipolarLength(mu = 9.93 * ac.muB, m = 164*u.u): def scatteringCrossSection(B): return 8 * np.pi * scatteringLength(B)[0]**2 + ((32*np.pi)/45) * dipolarLength()**2 -def calculateElasticCollisionRate(w_x, w_z, Power, Polarizability, N, T, B): #For a 3D Harmonic Trap - return (particleDensity(w_x, w_z, Power, Polarizability, N, T) * scatteringCrossSection(B) * meanThermalVelocity(T) / (2 * np.sqrt(2))).decompose() +def calculateElasticCollisionRate(w_x, w_z, Power, N, T, B): #For a 3D Harmonic Trap + return (particleDensity(w_x, w_z, Power, N, T) * scatteringCrossSection(B) * meanThermalVelocity(T) / (2 * np.sqrt(2))).decompose() -def calculatePSD(w_x, w_z, Power, Polarizability, N, T): - return (particleDensity(w_x, w_z, Power, Polarizability, N, T, m = 164*u.u) * thermaldeBroglieWavelength(T)**3).decompose() +def calculatePSD(w_x, w_z, Power, N, T): + return (particleDensity(w_x, w_z, Power, N, T) * thermaldeBroglieWavelength(T)**3).decompose() def convert_modulation_depth_to_alpha(modulation_depth): fin_mod_dep = [0, 0.5, 0.3, 0.7, 0.9, 0.8, 1.0, 0.6, 0.4, 0.2, 0.1] @@ -213,19 +213,19 @@ def convert_modulation_depth_to_temperature(modulation_depth): def gravitational_potential(positions, m): return m * ac.g0 * positions -def single_gaussian_beam_potential(positions, waists, alpha, P=1, wavelength=1.064*u.um): +def single_gaussian_beam_potential(positions, waists, alpha = 184.4, P=1, wavelength=1.064*u.um): A = 2*P/(np.pi*w(positions[1,:], waists[0], wavelength)*w(positions[1,:], waists[1], wavelength)) U_tilde = (1 / (2 * ac.eps0 * ac.c)) * alpha * (4 * np.pi * ac.eps0 * ac.a0**3) U = - U_tilde * A * np.exp(-2 * ((positions[0,:]/w(positions[1,:], waists[0], wavelength))**2 + (positions[2,:]/w(positions[1,:], waists[1], wavelength))**2)) return U -def astigmatic_single_gaussian_beam_potential(positions, waists, del_y, alpha, P=1, wavelength=1.064*u.um): +def astigmatic_single_gaussian_beam_potential(positions, waists, del_y, alpha = 184.4, P=1, wavelength=1.064*u.um): A = 2*P/(np.pi*w(positions[1,:] - (del_y/2), waists[0], wavelength)*w(positions[1,:] + (del_y/2), waists[1], wavelength)) U_tilde = (1 / (2 * ac.eps0 * ac.c)) * alpha * (4 * np.pi * ac.eps0 * ac.a0**3) U = - U_tilde * A * np.exp(-2 * ((positions[0,:]/w(positions[1,:] - (del_y/2), waists[0], wavelength))**2 + (positions[2,:]/w(positions[1,:] + (del_y/2), waists[1], wavelength))**2)) return U -def modulated_single_gaussian_beam_potential(positions, waists, alpha, P=1, wavelength=1.064*u.um, mod_amp=1): +def modulated_single_gaussian_beam_potential(positions, waists, alpha = 184.4, P=1, wavelength=1.064*u.um, mod_amp=1): mod_amp = mod_amp * waists[0] n_points = len(positions[0,:]) dx, x_mod = modulation_function(mod_amp, n_points, func = 'arccos') @@ -245,7 +245,7 @@ def gaussian_potential(pos, amp, waist, xoffset, yoffset): U_Gaussian = amp * np.exp(-2 * ((pos + xoffset) / waist)**2) + yoffset return U_Gaussian -def crossed_beam_potential(positions, theta, waists, P, alpha, wavelength=1.064*u.um): +def crossed_beam_potential(positions, theta, waists, P, alpha = 184.4, wavelength=1.064*u.um): beam_1_positions = positions A_1 = 2*P[0]/(np.pi*w(beam_1_positions[1,:], waists[0][0], wavelength)*w(beam_1_positions[1,:], waists[0][1], wavelength)) @@ -262,15 +262,35 @@ def crossed_beam_potential(positions, theta, waists, P, alpha, wavelength=1.064* return U +def astigmatic_crossed_beam_potential(positions, theta, waists, P, del_y, alpha = 184.4, wavelength=1.064*u.um): + + del_y_1 = del_y[0] + del_y_2 = del_y[1] + + beam_1_positions = positions + A_1 = 2*P[0]/(np.pi*w(beam_1_positions[1,:] - (del_y_1/2), waists[0][0], wavelength)*w(beam_1_positions[1,:] + (del_y_1/2), waists[0][1], wavelength)) + U_1_tilde = (1 / (2 * ac.eps0 * ac.c)) * alpha * (4 * np.pi * ac.eps0 * ac.a0**3) + U_1 = - U_1_tilde * A_1 * np.exp(-2 * ((beam_1_positions[0,:]/w(beam_1_positions[1,:] - (del_y_1/2), waists[0][0], wavelength))**2 + (beam_1_positions[2,:]/w(beam_1_positions[1,:] + (del_y_1/2), waists[0][1], wavelength))**2)) + + R = rotation_matrix([0, 0, 1], np.radians(theta)) + beam_2_positions = np.dot(R, beam_1_positions) + A_2 = 2*P[1]/(np.pi*w(beam_2_positions[1,:] - (del_y_2/2), waists[1][0], wavelength)*w(beam_2_positions[1,:] + (del_y_2/2), waists[1][1], wavelength)) + U_2_tilde = (1 / (2 * ac.eps0 * ac.c)) * alpha * (4 * np.pi * ac.eps0 * ac.a0**3) + U_2 = - U_2_tilde * A_2 * np.exp(-2 * ((beam_2_positions[0,:]/w(beam_2_positions[1,:] - (del_y_2/2), waists[1][0], wavelength))**2 + (beam_2_positions[2,:]/w(beam_2_positions[1,:] + (del_y_2/2), waists[1][1], wavelength))**2)) + + U = U_1 + U_2 + + return U + ##################################################################### # COMPUTE/EXTRACT TRAP POTENTIAL AND PARAMETERS # ##################################################################### -def trap_depth(w_1, w_2, P, alpha): +def trap_depth(w_1, w_2, P, alpha = 184.4): return 2*P/(np.pi*w_1*w_2) * (1 / (2 * ac.eps0 * ac.c)) * alpha * (4 * np.pi * ac.eps0 * ac.a0**3) -def calculateTrapFrequency(w_x, w_z, Power, Polarizability, dir = 'x', m = 164*u.u): - TrapDepth = trap_depth(w_x, w_z, Power, alpha=Polarizability) +def calculateTrapFrequency(w_x, w_z, Power, dir = 'x', m = 164*u.u): + TrapDepth = trap_depth(w_x, w_z, Power) TrapFrequency = np.nan if dir == 'x': TrapFrequency = ((1/(2 * np.pi)) * np.sqrt(4 * TrapDepth / (m*w_x**2))).decompose() @@ -281,10 +301,10 @@ def calculateTrapFrequency(w_x, w_z, Power, Polarizability, dir = 'x', m = 164*u TrapFrequency = ((1/(2 * np.pi)) * np.sqrt(4 * TrapDepth/ (m*w_z**2))).decompose() return round(TrapFrequency.value, 2)*u.Hz -def calculateCrossedBeamTrapFrequency(delta, Waists, Powers, dir = 'x', m = 164*u.u, Polarizability = 184.4, wavelength=1.064*u.um): +def calculateCrossedBeamTrapFrequency(delta, Waists, Powers, dir = 'x', m = 164*u.u, wavelength=1.064*u.um): - TrapDepth_1 = trap_depth(Waists[0][0], Waists[1][0], Powers[0], alpha=Polarizability) - TrapDepth_2 = trap_depth(Waists[0][1], Waists[1][1], Powers[1], alpha=Polarizability) + TrapDepth_1 = trap_depth(Waists[0][0], Waists[1][0], Powers[0]) + TrapDepth_2 = trap_depth(Waists[0][1], Waists[1][1], Powers[1]) w_x1 = Waists[0][0] w_z1 = Waists[1][0] @@ -292,8 +312,8 @@ def calculateCrossedBeamTrapFrequency(delta, Waists, Powers, dir = 'x', m = 164* w_y2 = Waists[0][1] w_z2 = Waists[1][1] - zReff_1 = np.sqrt(2) * z_R(w_x1, 1.064*u.um) * z_R(w_z1, 1.064*u.um) / np.sqrt(z_R(w_x1, 1.064*u.um)**2 + z_R(w_z1, 1.064*u.um)**2) - zReff_2 = np.sqrt(2) * z_R(w_y2, 1.064*u.um) * z_R(w_z2, 1.064*u.um) / np.sqrt(z_R(w_y2, 1.064*u.um)**2 + z_R(w_z2, 1.064*u.um)**2) + zReff_1 = np.sqrt(2) * z_R(w_x1, wavelength) * z_R(w_z1, wavelength) / np.sqrt(z_R(w_x1, wavelength)**2 + z_R(w_z1, wavelength)**2) + zReff_2 = np.sqrt(2) * z_R(w_y2, wavelength) * z_R(w_z2, wavelength) / np.sqrt(z_R(w_y2, wavelength)**2 + z_R(w_z2, wavelength)**2) wy2alpha = np.sqrt(((np.cos(np.radians(90 - delta)) / w_y2)**2 + (np.sin(np.radians(90 - delta)) / (2 * zReff_2))**2)**(-1)) zR2alpha = np.sqrt(((np.sin(np.radians(90 - delta)) / w_y2)**2 + (np.cos(np.radians(90 - delta)) / (2 * zReff_2))**2)**(-1)) @@ -328,7 +348,7 @@ def extractTrapFrequency(Positions, TrappingPotential, axis): dv = pcov[0][0]**0.5 return v, dv, popt, pcov -def computeTrapPotential(w_x, w_z, Power, Polarizability, options): +def computeTrapPotential(w_x, w_z, Power, options): axis = options['axis'] extent = options['extent'] @@ -343,7 +363,7 @@ def computeTrapPotential(w_x, w_z, Power, Polarizability, options): w_x = w_x * (aspect_ratio / current_ar) TrappingPotential = [] - TrapDepth = trap_depth(w_x, w_z, Power, alpha=Polarizability) + TrapDepth = trap_depth(w_x, w_z, Power) IdealTrapDepthInKelvin = (TrapDepth/ac.k_B).to(u.uK) projection_axis = np.array([0, 1, 0]) # default @@ -366,74 +386,68 @@ def computeTrapPotential(w_x, w_z, Power, Polarizability, options): Positions = np.vstack((x_Positions, y_Positions, z_Positions)) * projection_axis[:, np.newaxis] if not crossed: - IdealTrappingPotential = single_gaussian_beam_potential(Positions, np.asarray([w_x.value, w_z.value])*u.um, P = Power, alpha = Polarizability) + IdealTrappingPotential = single_gaussian_beam_potential(Positions, np.asarray([w_x.value, w_z.value])*u.um, P = Power) IdealTrappingPotential = IdealTrappingPotential * (np.ones((3, len(IdealTrappingPotential))) * projection_axis[:, np.newaxis]) IdealTrappingPotential = (IdealTrappingPotential/ac.k_B).to(u.uK) - - else: - delta = options['delta'] - waists = np.vstack((np.asarray([w_x[0].value, w_z[0].value])*u.um, np.asarray([w_x[1].value, w_z[1].value])*u.um)) - IdealTrappingPotential = crossed_beam_potential(Positions, delta, waists, P = Power, alpha = Polarizability) - IdealTrappingPotential = IdealTrappingPotential * (np.ones((3, len(IdealTrappingPotential))) * projection_axis[:, np.newaxis]) - IdealTrappingPotential = (IdealTrappingPotential/ac.k_B).to(u.uK) - - if gravity and not astigmatism: - # Influence of Gravity - m = 164*u.u - gravity_axis = np.array([0, 0, 1]) - tilt_gravity = options['tilt_gravity'] - theta = options['theta'] - tilt_axis = options['tilt_axis'] - if tilt_gravity: - R = rotation_matrix(tilt_axis, np.radians(theta)) - gravity_axis = np.dot(R, gravity_axis) - gravity_axis_positions = np.vstack((x_Positions, y_Positions, z_Positions)) * gravity_axis[:, np.newaxis] - TrappingPotential = single_gaussian_beam_potential(Positions, np.asarray([w_x.value, w_z.value])*u.um, P = Power, alpha = Polarizability) - TrappingPotential = TrappingPotential * (np.ones((3, len(TrappingPotential))) * projection_axis[:, np.newaxis]) + gravitational_potential(gravity_axis_positions, m) - TrappingPotential = (TrappingPotential/ac.k_B).to(u.uK) + + if gravity and not astigmatism: + # Influence of Gravity + m = 164*u.u + gravity_axis = np.array([0, 0, 1]) + tilt_gravity = options['tilt_gravity'] + theta = options['theta'] + tilt_axis = options['tilt_axis'] + if tilt_gravity: + R = rotation_matrix(tilt_axis, np.radians(theta)) + gravity_axis = np.dot(R, gravity_axis) + gravity_axis_positions = np.vstack((x_Positions, y_Positions, z_Positions)) * gravity_axis[:, np.newaxis] + TrappingPotential = single_gaussian_beam_potential(Positions, np.asarray([w_x.value, w_z.value])*u.um, P = Power) + TrappingPotential = TrappingPotential * (np.ones((3, len(TrappingPotential))) * projection_axis[:, np.newaxis]) + gravitational_potential(gravity_axis_positions, m) + TrappingPotential = (TrappingPotential/ac.k_B).to(u.uK) + + elif not gravity and astigmatism: + # Influence of Astigmatism + disp_foci = options['disp_foci'] + TrappingPotential = astigmatic_single_gaussian_beam_potential(Positions, np.asarray([w_x.value, w_z.value])*u.um, P = Power, del_y = disp_foci) + TrappingPotential = TrappingPotential * (np.ones((3, len(TrappingPotential))) * projection_axis[:, np.newaxis]) + TrappingPotential = (TrappingPotential/ac.k_B).to(u.uK) - elif not gravity and astigmatism: - # Influence of Astigmatism - disp_foci = options['disp_foci'] - TrappingPotential = astigmatic_single_gaussian_beam_potential(Positions, np.asarray([w_x.value, w_z.value])*u.um, P = Power, del_y = disp_foci, alpha = Polarizability) - TrappingPotential = TrappingPotential * (np.ones((3, len(TrappingPotential))) * projection_axis[:, np.newaxis]) - TrappingPotential = (TrappingPotential/ac.k_B).to(u.uK) - - elif gravity and astigmatism: - # Influence of Gravity and Astigmatism - m = 164*u.u - gravity_axis = np.array([0, 0, 1]) - tilt_gravity = options['tilt_gravity'] - theta = options['theta'] - tilt_axis = options['tilt_axis'] - disp_foci = options['disp_foci'] - if tilt_gravity: - R = rotation_matrix(tilt_axis, np.radians(theta)) - gravity_axis = np.dot(R, gravity_axis) - gravity_axis_positions = np.vstack((x_Positions, y_Positions, z_Positions)) * gravity_axis[:, np.newaxis] - TrappingPotential = astigmatic_single_gaussian_beam_potential(Positions, np.asarray([w_x.value, w_z.value])*u.um, P = Power, del_y = disp_foci, alpha = Polarizability) - TrappingPotential = TrappingPotential * (np.ones((3, len(TrappingPotential))) * projection_axis[:, np.newaxis]) + gravitational_potential(gravity_axis_positions, m) - TrappingPotential = (TrappingPotential/ac.k_B).to(u.uK) - - else: - TrappingPotential = IdealTrappingPotential - - if not crossed: + elif gravity and astigmatism: + # Influence of Gravity and Astigmatism + m = 164*u.u + gravity_axis = np.array([0, 0, 1]) + tilt_gravity = options['tilt_gravity'] + theta = options['theta'] + tilt_axis = options['tilt_axis'] + disp_foci = options['disp_foci'] + if tilt_gravity: + R = rotation_matrix(tilt_axis, np.radians(theta)) + gravity_axis = np.dot(R, gravity_axis) + gravity_axis_positions = np.vstack((x_Positions, y_Positions, z_Positions)) * gravity_axis[:, np.newaxis] + TrappingPotential = astigmatic_single_gaussian_beam_potential(Positions, np.asarray([w_x.value, w_z.value])*u.um, P = Power, del_y = disp_foci) + TrappingPotential = TrappingPotential * (np.ones((3, len(TrappingPotential))) * projection_axis[:, np.newaxis]) + gravitational_potential(gravity_axis_positions, m) + TrappingPotential = (TrappingPotential/ac.k_B).to(u.uK) + else: + TrappingPotential = IdealTrappingPotential + infls = np.where(np.diff(np.sign(np.gradient(np.gradient(TrappingPotential[axis].value)))))[0] - if TrappingPotential[axis][0] > TrappingPotential[axis][-1]: - EffectiveTrapDepthInKelvin = max(TrappingPotential[axis][infls[1]:-1]) - min(TrappingPotential[axis][infls[0]:infls[1]]) - elif TrappingPotential[axis][0] < TrappingPotential[axis][-1]: - EffectiveTrapDepthInKelvin = max(TrappingPotential[axis][0:infls[0]]) - min(TrappingPotential[axis][infls[0]:infls[1]]) - else: - EffectiveTrapDepthInKelvin = IdealTrapDepthInKelvin + try: + if TrappingPotential[axis][0] > TrappingPotential[axis][-1]: + EffectiveTrapDepthInKelvin = max(TrappingPotential[axis][infls[1]:-1]) - min(TrappingPotential[axis][infls[0]:infls[1]]) + elif TrappingPotential[axis][0] < TrappingPotential[axis][-1]: + EffectiveTrapDepthInKelvin = max(TrappingPotential[axis][0:infls[0]]) - min(TrappingPotential[axis][infls[0]:infls[1]]) + else: + EffectiveTrapDepthInKelvin = IdealTrapDepthInKelvin + except: + EffectiveTrapDepthInKelvin = np.nan TrapDepthsInKelvin = [IdealTrapDepthInKelvin, EffectiveTrapDepthInKelvin] - v_x = calculateTrapFrequency(w_x, w_z, Power, Polarizability, dir = 'x') - v_y = calculateTrapFrequency(w_x, w_z, Power, Polarizability, dir = 'y') - v_z = calculateTrapFrequency(w_x, w_z, Power, Polarizability, dir = 'z') + v_x = calculateTrapFrequency(w_x, w_z, Power, dir = 'x') + v_y = calculateTrapFrequency(w_x, w_z, Power, dir = 'y') + v_z = calculateTrapFrequency(w_x, w_z, Power, dir = 'z') CalculatedTrapFrequencies = [v_x, v_y, v_z] v, dv, popt, pcov = extractTrapFrequency(Positions, IdealTrappingPotential, axis) @@ -458,6 +472,53 @@ def computeTrapPotential(w_x, w_z, Power, Polarizability, options): return Positions, IdealTrappingPotential, TrappingPotential, TrapDepthsInKelvin, CalculatedTrapFrequencies, ExtractedTrapFrequencies else: + delta = options['delta'] + waists = np.vstack((np.asarray([w_x[0].value, w_z[0].value])*u.um, np.asarray([w_x[1].value, w_z[1].value])*u.um)) + IdealTrappingPotential = crossed_beam_potential(Positions, delta, waists, P = Power) + IdealTrappingPotential = IdealTrappingPotential * (np.ones((3, len(IdealTrappingPotential))) * projection_axis[:, np.newaxis]) + IdealTrappingPotential = (IdealTrappingPotential/ac.k_B).to(u.uK) + + if gravity and not astigmatism: + # Influence of Gravity + m = 164*u.u + gravity_axis = np.array([0, 0, 1]) + tilt_gravity = options['tilt_gravity'] + theta = options['theta'] + tilt_axis = options['tilt_axis'] + if tilt_gravity: + R = rotation_matrix(tilt_axis, np.radians(theta)) + gravity_axis = np.dot(R, gravity_axis) + gravity_axis_positions = np.vstack((x_Positions, y_Positions, z_Positions)) * gravity_axis[:, np.newaxis] + TrappingPotential = crossed_beam_potential(Positions, delta, waists, P = Power) + TrappingPotential = TrappingPotential * (np.ones((3, len(TrappingPotential))) * projection_axis[:, np.newaxis]) + gravitational_potential(gravity_axis_positions, m) + TrappingPotential = (TrappingPotential/ac.k_B).to(u.uK) + + elif not gravity and astigmatism: + # Influence of Astigmatism + disp_foci = options['disp_foci_crossed'] + TrappingPotential = astigmatic_crossed_beam_potential(Positions, delta, waists, P = Power, del_y = disp_foci) + TrappingPotential = TrappingPotential * (np.ones((3, len(TrappingPotential))) * projection_axis[:, np.newaxis]) + TrappingPotential = (TrappingPotential/ac.k_B).to(u.uK) + + elif gravity and astigmatism: + # Influence of Gravity and Astigmatism + m = 164*u.u + gravity_axis = np.array([0, 0, 1]) + tilt_gravity = options['tilt_gravity'] + theta = options['theta'] + tilt_axis = options['tilt_axis'] + disp_foci = options['disp_foci_crossed'] + if tilt_gravity: + R = rotation_matrix(tilt_axis, np.radians(theta)) + gravity_axis = np.dot(R, gravity_axis) + gravity_axis_positions = np.vstack((x_Positions, y_Positions, z_Positions)) * gravity_axis[:, np.newaxis] + TrappingPotential = astigmatic_crossed_beam_potential(Positions, delta, waists, P = Power, del_y = disp_foci) + TrappingPotential = TrappingPotential * (np.ones((3, len(TrappingPotential))) * projection_axis[:, np.newaxis]) + gravitational_potential(gravity_axis_positions, m) + TrappingPotential = (TrappingPotential/ac.k_B).to(u.uK) + + else: + TrappingPotential = IdealTrappingPotential + return Positions, TrappingPotential def extractWaist(Positions, TrappingPotential): @@ -477,7 +538,7 @@ def extractWaist(Positions, TrappingPotential): popt, pcov = curve_fit(gaussian_potential, xdata, Potential, p0) return popt, pcov -def computeIntensityProfileAndPotentials(Power, waists, alpha, wavelength, options): +def computeIntensityProfileAndPotentials(Power, waists, wavelength, options, alpha = 184.4): w_x = waists[0] w_z = waists[1] extent = options['extent'] @@ -492,7 +553,6 @@ def computeIntensityProfileAndPotentials(Power, waists, alpha, wavelength, optio idx = np.where(y_Positions==0)[0][0] - alpha = Polarizability wavelength = 1.064*u.um xm,ym,zm = np.meshgrid(x_Positions, y_Positions, z_Positions, sparse=True, indexing='ij') @@ -877,4 +937,6 @@ def plotCollisionRatesAndPSD(Gamma_elastic, PSD, modulation_depth, new_aspect_ra plt.grid(visible=1) plt.show() -##################################################################### \ No newline at end of file +##################################################################### + +#Polarizability = 184.4 # in a.u, most precise measured value of Dy polarizability \ No newline at end of file