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3b. Meshgrid-OptimizationExample.ipynb

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3c. Meshgrid-SimulationExample.ipynb

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"plt.show()"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"from IPython.display import YouTubeVideo\n",
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"YouTubeVideo('wvJAgrUBF4w', width=500, height=400)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},

4a. Algebra-AngularMomnetum.ipynb

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"num(4)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Random Matrices"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"- Random hermitian matrix"
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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": 59,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/latex": [
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"Quantum object: dims = [[4], [4]], shape = (4, 4), type = oper, isherm = True\\begin{equation*}\\left(\\begin{array}{*{11}c}-0.501 & (-0.172+0.146j) & 0.0 & (-0.060+0.697j)\\\\(-0.172-0.146j) & 0.169 & (-0.305+0.588j) & (0.044+0.641j)\\\\0.0 & (-0.305-0.588j) & 0.0 & (-0.458-0.087j)\\\\(-0.060-0.697j) & (0.044-0.641j) & (-0.458+0.087j) & 0.756\\\\\\end{array}\\right)\\end{equation*}"
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],
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"text/plain": [
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"Quantum object: dims = [[4], [4]], shape = (4, 4), type = oper, isherm = True\n",
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"Qobj data =\n",
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"[[-0.50113582+0.j -0.17222998+0.14571042j 0. +0.j\n",
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" -0.06039662+0.6965142j ]\n",
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" [-0.17222998-0.14571042j 0.1689534 +0.j -0.30474969+0.58835929j\n",
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" 0.04412378+0.64077284j]\n",
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" [ 0. +0.j -0.30474969-0.58835929j 0. +0.j\n",
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" -0.45812567-0.08748371j]\n",
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" [-0.06039662-0.6965142j 0.04412378-0.64077284j -0.45812567+0.08748371j\n",
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" 0.75578241+0.j ]]"
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]
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},
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"execution_count": 59,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"rand_herm(4)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"- Random Unitary Matrix"
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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": 56,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/latex": [
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"Quantum object: dims = [[4], [4]], shape = (4, 4), type = oper, isherm = False\\begin{equation*}\\left(\\begin{array}{*{11}c}(0.332-0.610j) & (-0.248+0.007j) & (-0.332-0.267j) & (0.468-0.235j)\\\\(-0.062-0.085j) & (0.838-0.353j) & (-0.312-0.253j) & (3.589\\times10^{-05}-0.034j)\\\\(-0.032-0.481j) & (0.145-0.293j) & (0.790+0.106j) & (0.020-0.156j)\\\\(-0.427+0.302j) & (0.069+0.006j) & (0.109+0.097j) & (0.834-0.066j)\\\\\\end{array}\\right)\\end{equation*}"
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],
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"text/plain": [
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"Quantum object: dims = [[4], [4]], shape = (4, 4), type = oper, isherm = False\n",
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"Qobj data =\n",
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"[[ 3.32426091e-01-0.61008781j -2.48216764e-01+0.00742287j\n",
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" -3.32218003e-01-0.26721645j 4.67803649e-01-0.23453233j]\n",
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" [-6.18056368e-02-0.08520346j 8.37959790e-01-0.35291461j\n",
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" -3.11514724e-01-0.25291069j 3.58896057e-05-0.03449434j]\n",
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" [-3.17360027e-02-0.48099205j 1.44640852e-01-0.29316018j\n",
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" 7.90378747e-01+0.10591817j 2.00616601e-02-0.15638388j]\n",
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" [-4.27155409e-01+0.30229774j 6.86551818e-02+0.00553252j\n",
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" 1.09189564e-01+0.0968594j 8.34155661e-01-0.06550129j]]"
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]
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},
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"execution_count": 56,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"rand_unitary(4)"
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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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"metadata": {},
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"outputs": [],
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"source": []
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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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"metadata": {},
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"outputs": [],
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"source": []
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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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"metadata": {},
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"outputs": [],
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"source": []
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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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"metadata": {},
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"outputs": [],
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"source": []
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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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