From dcf56df8ed3f22555070cae513ce91ec6b9bc5fc Mon Sep 17 00:00:00 2001 From: a-matsuo <47442626+a-matsuo@users.noreply.github.com> Date: Fri, 12 Apr 2024 02:56:21 +0900 Subject: [PATCH] docs(notebooks): add QAOA transpiler guide (#13) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Elena Peña Tapia Co-authored-by: Pedro Rivero Co-authored-by: Daniel J. Egger <38065505+eggerdj@users.noreply.github.com> --- docs/notebooks/qaoa-transpiler.ipynb | 1152 ++++++++++++++++++++++++++ 1 file changed, 1152 insertions(+) create mode 100644 docs/notebooks/qaoa-transpiler.ipynb diff --git a/docs/notebooks/qaoa-transpiler.ipynb b/docs/notebooks/qaoa-transpiler.ipynb new file mode 100644 index 0000000..9f1b282 --- /dev/null +++ b/docs/notebooks/qaoa-transpiler.ipynb @@ -0,0 +1,1152 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Transpile QAOA circuits with a best SWAP strategy" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this comprehensive guide, we will walk you through the **Quantum Approximate Optimization Algorithm (QAOA)** workflow using **[Qiskit Patterns](https://www.ibm.com/quantum/blog/qiskit-patterns).**\n", + "We'll demonstrate the application of these patterns specifically within the domain of **combinatorial optimization** and showcase how the QAOA, a hybrid quantum-classical iterative method, can be employed effectively.\n", + "\n", + "- **Step 1**: Formulating a combinatorial optimization problem in terms of finding the ground state of a Hamiltonian. This reformulated problem can be understood by a quantum computer.\n", + "- **Step 2**: Preparation of the necessary quantum circuits optimized for execution on quantum hardware.\n", + "- **Step 3**: Iteratively utilizing Qiskit's `Sampler` primitive to draw samples from the prepared quantum circuits in Step 2. These samples will inform the loss function of our algorithm routine.\n", + "- **Step 4**: Converting the samples from Step 3 into a solution for our combinatorial optimization problem.\n", + "\n", + "Additionally, We will demonstrate how to build and optimize QAOA circuits using the **SWAP strategy**, a specifically designed transpiler pass for QAOA applied to quadratic problems." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 1: Mapping the classical problem to a problem that can be understood by a quantum computer.\n", + "### Introduction to mapping a classical problem to a Hamiltonian\n", + "We are interested in solving a classical combinatorial optimization problem which has the form\n", + "\n", + "\\begin{align*}\n", + "\\min_{x\\in \\{0, 1\\}^n}f(x)\n", + "\\end{align*}\n", + "\n", + "Here, the vector $x$ are the $n$ decision variables. As you can see, there is nothing relating to quantum computing here yet. We therefore need to reformulate this problem into something that a quantum computer can understand. To be more concrete, we will consider a Quadratic Unconstrained Binary Optimization (QUBO) problem with the form\n", + "\n", + "\\begin{align*}\n", + "\\min_{x\\in \\{0, 1\\}^n}x^T Q x,\n", + "\\end{align*}\n", + "\n", + "where $Q$ is a $n\\times n$ matrix of real numbers. To start, we will convert the binary variables $x_i$ to variables $z_i\\in\\{-1, 1\\}$ by doing\n", + "\n", + "\\begin{align*}\n", + "x_i = \\frac{1-z_i}{2}.\n", + "\\end{align*}\n", + "\n", + "Here, for example, we see that if $x_i$ is $0$ then $z_i$ is $1$. When we substitute the $x_i$'s for the $z_i$'s in the QUBO above, we obtain the equivalent formulations for our optimization task\n", + "\n", + "\\begin{align*}\n", + "\\min_{x\\in\\{0,1\\}^n} x^TQx\\Longleftrightarrow \\min_{z\\in\\{-1,1\\}^n}z^TQz + b^Tz\n", + "\\end{align*}\n", + "\n", + "The details of the computation are shown below. Here, $b$ depends on $Q$. Note that to obtain $z^TQz + b^Tz$ we dropped an irrelevant factor of 1/4 and a constant offset of $n^2$ which do not play a role in the optimization. Now, to obtain a quantum formulation of the problem we promote the $z_i$ variables to a Pauli $Z$ matrix, i.e., a $2\\times 2$ matrix of the form\n", + "\n", + "\\begin{align*}\n", + "Z_i = \\begin{pmatrix}1 & 0 \\\\ 0 & -1\\end{pmatrix}.\n", + "\\end{align*}\n", + "\n", + "When we substitute these matrices in the QUBO above we obtain the following Hamiltonian\n", + "\n", + "\\begin{align*}\n", + "H_C=\\sum_{ij}Q_{ij}Z_iZ_j + \\sum_i b_iZ_i.\n", + "\\end{align*}\n", + "\n", + "We refer to this Hamiltonian as the **cost Hamiltonian**. It has the property that its gound state corresponds to the solution that **minimizes the cost function $f(x)$**.\n", + "Therefore, to solve our optimization problem we now need to prepare the ground state of $H_C$ (or a state with a high overlap with it) on the quantum computer. Then, sampling from this state will, with a high probability, yield the solution to $\\min f(x)$." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Mapping a Max-Cut problem to a cost function Hamiltonian\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The starting point of the workflow is a problem definition, in the form of a **graph** or **cost function hamiltonian**.\n", + "In this example, we will use a random 3 regular graph which we want to find the cut that maximizes the number of crossing edges. Having the problem in graph-form will allow us to directly apply SAT-mapping explained later." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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dQvf/muvXr/PFF18wevRoMmbMyJAhQ+jXrx+ZMmVKnZAiIuK0tEJpAKvVSkhIiFOvTv5bx44d2blzJz4+PlSvXp2JEyfqEvh9JCYmMnfuXPz9/albty5nzpzhhx9+4Pjx47z++uuPvNHJmc6If5Bs2bIxbNgwjh07RpcuXXj33XcpXrw4U6ZMISEhwfFBRUTEaamgNMDRo0c5deqUSxWUAMWKFWPz5s307NmTPn360LFjR65fv252LKdy8+ZNJk6cSMmSJenQoQM+Pj78+uuv7Nmzh65du+Lp+RCd5+8i+Yz44UVsH6fWL2TyPCOKwPAnH26TWL58+Rg/fjy///47tWrVolevXvj5+TFv3jy9KBERSadUUBogJCQEDw8PateubXaUh+bl5cX48eOZO3cuK1asoFKlSuzYscPsWKaLjIzkf//7HwULFuS1116jcuXKbNu2jdWrV9O4cWMsBm7Tt1hsl5sX+kEOD8fv/nbHNs9CPxjygMvc91O0aFF++ukndu7cSeHChQkMDKRatWqsXbvWsKwiIuIaVFAaICQkhOrVq7t0f8fAwEB27txJjhw5qFGjBuPHj0+Xq00nTpygX79+FCxYkJEjR9KxY0eOHDnC7NmzqVKlikPndsYz4lOiYsWKLF++nDVr1gBQr149GjduzK5du4yZQEREnJ4KSjslJCSwZs0aGjRoYHYUuxUtWpRNmzbxyiuv0K9fPwIDA7l27ZrZsVLFjh076NSpE8WKFWPWrFm8/fbbnD59mvHjx/Pkk0+mWg5nPCM+perWrcuWLVuYN28eJ0+epFKlSnTu3Jljx44ZP5mIiDgVFZR22rZtG1FRUS53/+S9ZMyYkTFjxjBv3jxWr15NpUqV2LZtm9mxHMJqtbJixQrq169PlSpV2LZtG+PGjeP06dN8+OGH5M5t0BLeI2iVG/ZUsZ2p3cn3r6LQM4XF5d+/vrMvbKlkG6+lg/9IFouFtm3bsn//fiZPnsxvv/1GqVKl6Nu3LxcuXHDs5CIiYhq1DbLT//73P0aPHk1kZCQeHmnrJMsTJ07QsWNHdu/ezahRo+jfv7+h9w6aJT4+ntmzZzNq1Cj27t1LlSpVeOutt2jbtq3T/j+MjIO112B7NGyLtr2PTvzv1/m4QxUfqOoDlX1s58XnzpDaaf9y8+ZNxo8fz4gRI7h9+zavv/46b775JtmyZTMvlIiIGE4FpZ2effZZcufOzYIFC8yO4hBxcXG8/fbbfP3117Ru3ZqpU6eSI0cOs2M9kujoaKZMmcJXX33FmTNnaNKkCYMHD6Z27douVyibeUb8o7h69Sqff/45Y8aMIXPmzAwdOpQ+ffrg5eVldjQRETGACko7REdHkzNnTsaMGUOfPn3MjuNQixYt4sUXXyRbtmzMnj0bf39/syOl2IULFxg7diwTJ04kJiaGLl268Oabb1K2bFmzo6U7586d4+OPPyYoKIj8+fPz8ccf07VrV9zdne1kcxEReRi6h9IO69evJyEhIc3cP3k/rVq1Yvfu3eTLl4+aNWsyevRop98FfujQIXr16kWhQoUYN24cPXr04Pjx40yfPl3FpEkef/xxJk2aRHh4OP7+/nTv3p3y5cuzePFip/95EhGRe1NBaYeQkBAKFSpEsWLFzI6SKgoVKsSGDRsYMGAAb7zxBq1ateLKlStmx/qPzZs307p1a5566imWLl3Kxx9/zJkzZ/jiiy8oUKCA2fEEKFmyJHPmzGHr1q3ky5ePVq1aUbNmTX777Tezo4mIyCNQQWmH5OMWXe3+O3tkyJCBL774giVLlrBp0yYqVKhAaGio2bFISkpi0aJF1KxZk2eeeYZDhw4xefJkTp48yZAhQ8iePbvZEeUunn76aVatWsXKlSu5desWtWrVonnz5uzbt8/saCIi8hBUUD6is2fPcvDgwXRxuftumjdvzu7duylQoAC1atVi1KhRJCUlpXqO27dvExQUROnSpWndujUWi4VFixYRHh5Ojx49yJgxY6pnkofXsGFDtm3bxuzZszl06BDly5enW7dunDx50uxoIiKSAiooH9GqVauwWCzUr1/f7CimKVCgAOvWreP1119n8ODBtGjRgsjIyFSZ++rVq4wYMYLChQvTq1cvnnrqKTZt2sRvv/1Gy5YtcXPTj7arcXNzo0OHDhw4cIBvvvmGkJAQSpQowYABA7h06ZLZ8URE5D60y/sRPffccxw6dIjt27ebHcUpLFu2jG7dupEpUyZmzZpFzZo1HTLPmTNn+Prrr/nuu++Ij4+nW7duvPHGG5QsWdIh84l5YmNjGTNmDJ999hlJSUm8+eabvP766y59xKmISFqlZZxHkJSUxKpVq9Lt5e67adq0Kbt376Zw4cLUqVOHkSNHGnoJfO/evXTr1o0nn3ySqVOn0r9/f06ePMl3332nYjKN8vb2ZujQoRw/fpxXXnmFESNGULRoUcaNG8ft27fNjiciIn+jgvIR7Nu3j4iICBWU//LEE0+wdu1aBg8ezDvvvEOzZs3sulRptVpZu3YtTZo0oXz58qxbt45Ro0Zx+vRpPv30U/Lly2dgenFWuXLlYtSoURw5coQWLVowcOBASpUqxYwZM0y5b1dERP5LBeUjCAkJwcvLixo1apgdxel4eHgwfPhwli9fzvbt26lQoQIbNmx4qDESEhKYM2cOTz/9NPXq1ePcuXPMmDGDY8eOMXDgQF3yTKcKFChAUFAQ+/bto0KFCnTt2pWKFSuybNky9bAUETGZCspHEBISQq1atXRs3H0EBASwe/duihUrRt26dfn0008fuJp048YNJkyYQIkSJejYsSPZs2dnxYoV7N69m+eeew5PT89USi/OrHTp0ixYsIDQ0FBy5MhBs2bNqFOnjlO0rxIRSa9UUD6kW7dusWHDBl3uToH8+fOzevVqhg4dyvvvv0/jxo2JiIj4z9ddunSJjz76iIIFC9K/f3/8/f3ZsWMHq1atolGjRumqz6ekXLVq1Vi7di3Lli3j+vXr1KhRg9atW3PgwAGzo4mIpDsqKB/Spk2buHXrlgrKFPLw8GDYsGGsXLmSPXv2UKFCBdatWwfAsWPH6Nu3L4UKFeLzzz+nS5cuHD16lFmzZlGpUiVzg4tLsFgsNGnShJ07dzJjxgz27t1L2bJleemllzhz5ozZ8URE0g21DXpI77zzDlOnTuX8+fPqdfiQzp8/z3PPPce6desoXbo0Bw8eJGfOnPTv358+ffqQK1cusyOKi4uLi+O7775j2LBhXL9+nddee4133nlHP1siIg6miughhYSE0KBBAxWTD8lqtbJ7926sVitWq5Xw8HCKFy/O1q1bef/99/WEL4bIkCEDr732GkePHmXo0KFMmjSJJ598kuHDhxMbG2t2PBGRNEtV0UO4fPkyO3fu1OXuhxAXF8cPP/xA+fLladq0KbGxscydO5eVK1dy7do1qlevzurVq82OKWmMj48PH3zwAcePH6d79+58/PHHFCtWjIkTJxIfH292PBGRNEcF5UNYvXo1VqtVBWUKREVF8eWXX1K0aFFeeOGFO8c0hoWFERgYSMOGDdm9ezd+fn40bNiQDz/8kMTERLNjSxqTJ08evv76aw4dOkSjRo3o27cvpUuXZvbs2ephKSJiIBWUDyEkJISnnnqK/Pnzmx3FaZ0/f5533nmHggUL8s4771C/fn327dvHL7/8Qu3atf+xYztfvnysWLGCjz/+mE8++YQGDRpw/vx5E9NLWlW4cGGmT5/Onj17KFWqFJ06deLpp58mJCTE7GgiImmCCsoUslqthISEaHXyHn7//Xd69uxJ4cKFmTBhAr169eL48eNMmzYNPz+/e36fu7s777//PqtXr+bQoUNUqFBBT/LiMGXLlmXJkiX89ttveHl50ahRIxo0aMC2bdvMjiYi4tJUUKbQ0aNHOXXqlArKf9m0aROtWrXiqaeeYtmyZQwbNowzZ84watQonnjiiRSPU6dOHXbv3k2FChUICAjgvffeIyEhwYHJJT2rWbMmGzduZPHixVy4cIGqVavSvn17Dh8+bHY0ERGXpIIyhUJCQvDw8KB27dpmRzFdUlISCxcupEaNGtSsWZMjR44wdepUTpw4weDBg8mWLdsjjevr68uvv/7KJ598wogRI6hfvz5//PGHwelFbCwWCy1atGDPnj1MmzaNrVu3Urp0aXr37s25c+fMjici4lJUUKZQSEgI1apVS9fnSN+6dYvJkyfz1FNP0aZNGzw8PFiyZAn79++ne/fuZMyY0e453NzcGDp0KGvXruXo0aNUqFCBFStWGJBe5O7c3d154YUXOHToEKNGjWLevHkUK1aMIUOGcPXqVbPjiYi4BBWUKZCQkMCaNWvS7eXuq1evMnz4cAoXLkzv3r3x8/MjNDSUDRs20Lx5c4f05KxVqxa7d++mSpUqNG7cmHfeeUeXwMWhvLy8GDRoEMePH+fNN99k/PjxFC1alM8//5ybN2+aHU9ExKnppJwUCA0NpUaNGmzevJnq1aubHSfVnD59mq+++orJkyeTkJDAiy++yOuvv06JEiVSLUNSUhKjRo3i3XffpXr16syaNeuh7s0UeVQXL15k2LBhTJo0ibx58/LRRx/x4osv4uHhYXY0ERGnoxXKFFi1ahXZsmXj6aefNjtKqtizZw/PP/88Tz75JNOnT2fQoEGcOnWKb7/9NlWLSbBdAn/77bdZv349J0+epEKFCixbtixVM0j6lDdvXsaPH8/vv/9OrVq16NWrF35+fsybNw+9DhcR+ScVlCkQEhJC3bp10/TKhNVqZfXq1QQEBFChQgV+++03Ro8ezenTpxk2bBh58+Y1Nd8zzzzD7t27qVatGs2aNWPw4ME68URSRdGiRfnpp5/YuXMnhQsXJjAwkGrVqrF27Vqzo4mIOA0VlA8QHR1NaGhomr1/MiEhgZ9//pkqVarQoEEDIiIimDlzJkePHqV///5kyZLF7Ih35MqVi8WLFzNq1Ci++uorateuzenTp82OJelExYoVWb58OWvWrAGgXr16NG7cmF27dpmcTETEfCooH2D9+vUkJCSkuYIyNjaWcePGUbx4cTp37kzOnDlZuXIlO3fupEuXLnh6epod8a7c3Nx488032bBhA3/88QcVKlRgyZIlZseSdKRu3bps2bKFefPmcfLkSSpVqkTnzp05duyY2dFEREyjgvIBQkJCKFSoEMWKFTM7iiEuXbrEhx9+SMGCBRk0aBDVq1dn586dd04B+vvRiM6sevXq7Nq1i5o1a9KyZUveeOMN4uLizI4l6YTFYqFt27bs37+fyZMn89tvv1GqVCn69u3LhQsXzI4nIpLqtMv7AUqXLs0zzzzD5MmTzY5il6NHjzJ69Gi+//573Nzc6NmzJ4MGDaJw4cJmR7OL1Wrl66+/ZvDgwVSuXJmff/7Z5f9M4npu3rzJ+PHjGTFiBLdv3+b111/nzTfffOQm/yIirkYF5X2cPXuWAgUKMHv2bDp06GB2nEeydevWO82ac+fOTf/+/Xn11VfJlSuX2dEMFRYWRseOHbl+/TrTpk2jVatWZkeSdOjq1at8/vnnjBkzhsyZMzN06FD69OmDl5eX2dFERBxKl7zvY9WqVVgsFurXr292lIeSlJTEL7/8Qp06dfD392f37t1MnDiRU6dO8d5776W5YhLA39+fXbt2UadOHVq3bs3AgQN1CVxSXY4cORgxYgRHjx6lXbt2DB48mJIlSzJt2jQSExPNjici4jAqKO8jJCSESpUquUwBFhcXx/Tp0ylXrhzNmzfn1q1bzJs3j99//53evXuTKVMmsyM6VI4cOZg/fz5jxozhm2++oWbNmpw4ccLsWJIOPf7440yaNInw8HD8/f3p3r075cuXZ/HixephKSJpkgrKe0hKSmLVqlUusbs7KiqKL774gieffJIXX3yRIkWKsGHDBkJDQ2nbti3u7u5mR0w1FouF/v37s2nTJiIjI6lYsSLz5883O5akUyVLlmTOnDls3bqVfPny0apVK2rWrMlvv/1mdjQREUOl64LSaoWIODh5Ew7fsL2PiLM9vm/fPiIiImjQoIHZMe/p3LlzvP322xQoUIChQ4fSqFEjwsPDWbJkCc8++6zL7Nh2hKeffpqdO3fSoEED2rVrR79+/bh9+7bZsSSdevrpp1m1ahUrV67k1q1b1KpVi+bNm7Nv3z6zo4mIGCJdbcqJjIM112BHNGyNgh0xEH2X25p83MH36hlOrpjDtKH9aJwnA7kzpHrcezpw4ABffPEFM2bMIFOmTLzyyiv079+f/Pnzmx3N6VitVr755htef/11ypYty+zZsylatKjZsSQdS0pKIjg4mHfffZdjx47x/PPP87///U/dCUTEpaX5gtJqhS1RMOEPmH0JEqzgYbG9f9A3WpISsbp74GGBTr7Q93HwzwpmLPxZrVY2btzI559/ztKlS3n88ccZNGgQvXr1UmuSFNi5cycdOnTg0qVLTJkyhfbt25sdSdK5+Ph4goKC+Pjjj7l8+TKvvvoq7733Hnny5DE7mojIQ0vTBeWiSHjvBOyPTWEReR/J31/WGz4pAi1zG5fzfhITE1m0aBGjRo1iy5YtlClThjfffJMuXbqQIYMTLZu6gKioKHr16sWcOXPo06cPX375pdq5iOliY2MZM2YMn332GUlJSbz55pu8/vrr+Pj4mB1NRCTF0mRBeTke+h2BWRG2m0STDBw7ebzOvjCuOORy0AmFN2/e5IcffuDLL7/kyJEj1K5dm7feeosmTZrg5paub321i9VqZdKkSQwcOJCnnnqKOXPmULx4cbNjiXD58mVGjhzJuHHjyJo1K++//z4vv/wyGTNmNDuaiMgDpbnKZOElKBkGcyJsHxtZTP59vDkRtnkWXjJ2/CtXrvDJJ59QuHBhXn31VcqVK8eWLVtYt24dzZo1UzFpJ4vFwiuvvMKWLVuIjY29c7qOiNly5crFqFGjOHLkCC1atGDgwIGUKlWKGTNmkJRk9L9kIiLGSjPVidUKw09Bm3C4mgCObiGciG2eNuEw4pRtfnucPHmSAQMGULBgQT799FPatm3LoUOHCA4Oxt/f35DM8pcKFSqwY8cOmjdvTufOnXnllVe4efOm2bFEKFCgAEFBQezbt48KFSrQtWtXKlasyLJly9TDUkScVpooKK1WGHoC3v2zh3VqvZZPnid57kf5t3737t0899xzFCtWjBkzZvD6669z6tQpJk6cqEuxDubj48PMmTP57rvvmD59OtWqVePQoUNmxxIBoHTp0ixYsIDQ0FBy5MhBs2bNqFOnDqGhoWZHExH5jzRRUI44DSNPu04Gq9VKSEgIjRo1omLFimzevJmvvvqK06dP87///Q9fX1/HhpU7LBYLvXr1IiwsjFu3blG5cmVmzpxpdiyRO6pVq8batWtZtmwZ169fp0aNGrRu3ZoDBw6YHU1E5A6XLygXXvprZdJsQ0/YdpbfS0JCArNmzaJSpUo0atSIyMhIZs2axZEjR+jXrx/e3t6pF1b+oVy5cuzYsYM2bdrw/PPP06tXL10CF6dhsVho0qQJO3fuZMaMGezdu5eyZcvy0ksvcebMGbPjiYi49i7vy/G2jTFXEsAZ/hBuQA4POOT/z93fMTExTJ06ldGjR3Pq1CkaNWrE4MGDqVevXro+zcYZWa1Wvv/+e1577TWKFi3K3LlzKVWqVCrMC5fi4UYixFkhgwUyu0MeT3P6nopzi4uL47vvvmPYsGFcv36d1157jXfeeYdcuXKZHU1E0imXLii7HLDttnb0BpyH4Q509IWZpSEiIoJx48YxYcIEoqKi6NSpE2+++SYVKlQwO6Y8wP79+2nfvj2nT59m4sSJdOvWzdDxH+bUpspZoGpWqOwD9bLjVKc2ibmio6P56quvGDVqFG5ubgwePJiBAwfqaoeIpDqXLSgXRULr/WanuLeADd+wbvjreHh40KtXLwYOHEihQoXMjiUPITY2lr59+zJ9+nS6d+/O+PHjyZw58yOP98inNvHX1znDqU3ifC5dusSnn37KxIkTyZkzJx988AE9e/bE09NBjXJFRP7FJQtKqxXKbYcDsam3o/uhJCXifuYQH/+xkFdfeYWcOXOanUjsMG3aNPr27UvhwoWZO3cupUuXfugx0sKpTeL8Tp48yYcffsiPP/5I0aJF+eSTT2jfvr3614qIw7nkvzJbomxPzE5ZTAK4uZNYqDT1+w5VMZkGvPjii2zbtg2AKlWqMG3atBR/7+V4260ZrffbXgCBfcXk378/PBZa7beNfznevjElbShcuDDTp09nz549lCpVik6dOvH0008TEhJidjQRSeNcsqCc8IdtlcaZeVhgwjmzU4hRSpcuzbZt2+jcuTPdu3fnhRdeIDY29r7f4+qnNonrKlu2LEuWLOG3337Dy8uLRo0a0aBBgzsvjEREjOZyBWVk3F/3n9nlRDh81B66PAmNM0Or3DCgFmxeYkjOBCv8HGHLK2lD5syZCQoK4ocffiA4OJgqVaqwf/9/b+R19VObJO2oWbMmGzduZPHixVy4cIGqVavSvn17Dh8+bHY0EUljXK6gXHPNgGIS4OIpuBENAS/Aa2Og6/u2x99tCUu+M2ACW8611wwZSpxI165d2bFjBx4eHjz99NMEBQXdORLPlU9tkrTJYrHQokUL9uzZw7Rp09i6dSulS5emd+/enDunyygiYgyX25Tz9jEYfdagovLfEhOhd2WIuwU//G73cB4WeOMJGFnUgGzidG7evMmAAQOYPHkyzz33HN9++y1jL2dxikb7w4vAO2oqIHdx69YtJk6cyKeffsqNGzfo378/b7/9Njly5DA72n+oP6uI63C5grLOLlh/3YETDG0Bv2+D+RcMGa5udlhTwZChxEn99NNP9O7dm6xNunKuzzdmx7ljoZ/tTg6Ru4mKiuKLL75g9OjRZMiQgSFDhtCvXz8yZcpkWib1ZxVxXS5VUFqtkG3j3f+BeWQ3YyHuJsRch82L4du3oG5HeM+Y85x93OF6Tb2aTuvCfj/KM0dzkZg5K7i5mx3nnqc2ifzbxYsXGTZsGJMmTSJv3rx89NFHvPjii3h4eKTK/OrPKpI2uFRBGREHeTcbPOjoV2DJJNt/u7nBs23hje/Ax7jLPxdrgK9ePadptlObrCTiPM9kfz+1SeRBjh07xvvvv8+sWbMoWbIkn376KW3btnXo8bDqzyqSdrjUppwbjtguGzgQvgiBIdOhahNISoR4Y7dm33TahplihEWRMCsCpyomwbb7+6cIWBxpdhJxBUWLFuWnn35i165dFClShMDAQKpVq8batWsNn0v9WUXSHpcqKOMcsZZasBRUbgAB3WDEUrgZA++2MHSb7G0VlGmW1WpbYXHWXyQ3bPlc5zqEmK1ChQr8+uuvdwrJevXq0bhxY3bt2mXI+OrPKpI2Oevz4F1lSI0FoFqBtk05Z4zr05bRpf6W5WE4+6lNScC+WAiLMjuJuJo6deqwZcsW5s2bx8mTJ6lUqRKdO3fm2LFjjzSe+rOKpG0uVepkTo29Drdv2t7HGreVPJNL/S3Lw9CpTZKWWSwW2rZty/79+5kyZQq//fYbpUqVom/fvly4kPJOGOrPKpL2uVSpk8fTtmvaEFcj/vtYQjys/AEyZoLCxuxk8PmzZ5qkPYad2gS2Wy2+/xAGN4aWOaGuBZZPM2Bgndok9vPw8KBHjx4cOXKE4cOHM2vWLIoWLcr777/P9esPfvE94jSMPJ0KQZ08g0ha5lIFpcUClbIYNNjo3vB6fZj+MfwyBX78BHqUgyM74aVPIJMxE1XxUQuLtMqwU5sArkfCD/+D0wehaHmDBv2LTm0SI2TKlIm33nqL48eP079/f7788kuKFi3K6NGjuXXr1l2/Z+ElnKLZP9hWKhdpk5qIQ7hUQQm2HmOGXGKs29HWJmjRRPjqVZg7GvI8AZ8sgg6vGzCBLWdVH0OGEie0I9rAy905H4N55+HnU/DKKIMG/YuHxZZXxAjZs2dnxIgRHD16lHbt2jF48GBKlizJtGnTSEz86+7Iy/HQ8xBO0//ADejxu3Z/iziCyxWUlX0MWhWq18nWLmj+BVgVD4uv2D5+pqUBg9skWG15JW0KizJwhTJDRsiZz6DB/ivBCltVUIrBHn/8cSZNmkR4eDj+/v50796d8uXLs3jxYqxWK/2OwLUEcJZbF5Ow5el/xOwkImmPyxWU9bI7/yaIZB4W29GLkvZYrbAzxuwUD2d7tDYliGOULFmSOXPmsHXrVvLly0erVq0o3WvIn/1ZnYv6s4o4hssVlLkzQMc8zl9UJh8FpvNl06ZL8QYfAZoKohNtuUUc5emnn2bVqlWsWLmSk/V72g6KcELqzypiPJcrKAH65jfwUqODJFht58pK2uSQU5tSgU5tktTgU7Uhtx4r7hTn2t+N+rOKGM/D7ACPolpW23mt4U7aUNoN8PO2bSCStMkhpzalgp/nLeDJDAlkzpz5H2/e3t7/+NjDwyX/aRAnkdyf1Zlf+Cf3Z62WzewkImmDSz5rWCzwSRHbea3OKAkYVkTtgtKyVDm1yQGGvDEQLj64GZ+np+c9i80HPZ7Sz3l6emLRL0maY1h/1pEvworp9/78nLOQJ/8jD5/cn/Wroro1ScQILllQArTMDZ19bee1OtPVR3ego68tn6RdqXJqkwOcPXaULAk3uHHj7m+xsbEp+tyVK1c4e/bsXT93+/btFGVxd3c3vEj995uXl5eK1lRmWH/WFr2hcoN/Pma1wlevQN7CdhWTyZL7s7b3tXsokXTPZQtKgHHFYeUV23mtznDp2w3I7gFji5udRBwt+dQmV9qY4+MOj2f2xGLJRrZsjrvOl5iYyM2bNx+qQL3b56Kiorhw4cJdP3fz5s0UZbFYLIYWqHf7XKZMmXBzc8nb0R0iuT+r3UVlmeq2t7/btxFu3YAGz9k5uE1yf1YVlCL2c+mCMpcnTCkJbcLNTmKTBASVsuWStC351Kb1xh35DgvGQ8w1iPzz4O3NS+DSWdt/t+kHWewrAlPr1CZ3d3eyZMlClixGHWv1X0lJSdy6deuRV1j//hYZGXnPr7emcBuwl5eXQ1ZYkx/PlCmTy9zXamh/1n9b9ZPth7hBF0OGU39WEeNYrCn9F9OJDT/lHEd7DS8C7xQyO4WklrePweizBj55dioMF0/d/XOzTkC+wo88tIcF3ngCRhZ95CHSHavVyu3bt+2+PeB+n4uNjf3HyTL3kyFDBofeHpA5c2YyZLDvZkKrFbJtdNDKfUI8tHsMCpaCcRsNG9bHHa7X1D3vIvZyjZe8D/BOQYhJhBEP3mvg0AxDCpo3v6Q+w05tSvbzSQMH+yed2vTwLBYLXl5eeHl5kTNnTofNEx8f/8BCNCUF6t1WWpM/FxcXl6IsHh4ej7yKmjlzZuKz5CA6b1vH/EVtWwFRlw273J0suT+rrzbmiNglTRSUFgt8WsT2SnPoCdu9jKlxT6UFK1Ys+IXO5JNanbFYdB9VepJ8apMzt0ZJplObnJenpyfZsjn2vtaEhIQ797Xas8J6/fp1zp07d9fP3bx5E/IWgp8dVFCu+gk8PKFOB8OHVn9WEfuliYISbEXlO4WgtDf0+N12Xqsj90u4A9k9LLx8PYyR73Zl6PV9jBw50oEzirNJPrXJkBYpDqRTm8TDwwMfHx98fBy3TJ2UlMTeq7eouM8Bg9+Mgc2L4OkAyJbL8OFvq6AUsVuaW1JrlRsO+UOHP3ftGf0HTB6voy8c9ofhzfwZPXo0n332GZMnTzZ4NnF2OrVJxMbNzY3smTM7ZvCNCw3d3f1vGdPcM6FI6kuTv0a5POGn0rDQD8p42x6z9+zv5O8v4w2L/GBmacj5527uAQMG0LdvX1599VVCQkLsm0hcSvKpTc76i+QGlNOpTZJKHNafddVMyJQFarR0yPCZnPUXWMSFpOlfo1a5YU8VCK1ou+SXXBR6prC4/PvXd/aFLZVs4/27abnFYuHrr78mICCAwMBA9u930iN8xHDJpzY56xUzndokqSm5P6uhrl2CHaugZhvwMn4F1MfdlltE7JMm2galVGSc7VSE7dGwLdr2/m7tLXzcbT37qvrYdsbWzZ6y+8+io6N59tlnuXr1Klu2bOGxxx4z+o8gTqrLAec9tWlmabOTSHpSZ5cD+rOO7QefLYeqAQYObFM3O6ypYPiwIulOuioo/81qtbWLuJlkuyk7o5vt0kcez0df0Tl79iz+/v48/vjjrFu3Dm9vb2NDi1O6HA8lw5zr1KYcHrb7idVoX1KT4f1Z+1aH88dh7jlwN3b5U/1ZRYyTpi95P4jFYus9VsgLSmS2vffNYN/lwSeeeIKlS5dy8OBBnnvuuRQ3LRbXlnxqkzMUk6BTm8Q8hvdnnRAK8y8aXkyC+rOKGCldF5SOUrFiRWbPns2SJUsYPHiw2XEklbTOY+uH6gyGF7HdQyyS2pL7s7oC9WcVMY4KSgdp1qwZY8eOZfTo0XzzzTdmx5FU8k5B25vZGXRqk5gluT+rsxeV6s8qYqw009jcGfXt25ejR4/Sr18/ChcuTNOmTc2OJA5m1qlNyfOMKAJDdJ68mKxvfpgZYXaK+1N/VhFjpetNOakhMTGRtm3bsmbNGjZu3Ej58uXNjiSpZFFkap7aZLtnUpe5xRlYrVB+O4THOs99xX/nBvh5w+4qaqklYhQVlKkgNjaWWrVqcfHiRcLCwsifP7/ZkSSVXI6HfkdgVoTxq5XJ43XxhXHF/2q0L+IMFkdCKyduybvI7789hUXk0ekeylTg7e3NkiVLcHNzo3nz5sTExJgdSVLJ309tKpkxAQC3JPvWK+93apOIs2iZ23YghKMOz3lU7thehKmYFDGWCspU8vjjj7N06VKOHTtGp06d1E4onWmVGzqvHknGQbVplzPBYac2iTiTccVtt2M4yxONG7Y8Y4ubnUQk7dEl71S2YsUKmjVrRp8+fRg7dqzZcSSVxMXFUahQIVq2bMmkSZMcfmqTiLNYeAnahJud4i8L/XSvsYgjqKA0wXfffUfv3r0ZM2YM/fv3NzuOpIKZM2fy/PPPEx4eTunS/z0L0RGnNok4i+Gn4N0TZqew9Wd9R10QRBxCBaVJBg8ezBdffMHChQtp2bKl2XHEgaxWK1WrViVnzpysWLHC7Dgiqc5qtRWUI06bl6Fv9uuMK59NL9BEHMRZbm1Jd0aOHEnbtm3p3LkzO3bsMDuOONDmzZvZvn07AwcONDuKiCmS+7MO//MkqdR64kmeJ0fw56xoX4WLFy+k0swi6Y9WKE1048YN6taty+nTpwkLC6NgQR1vkha1b9+evXv3cvDgQdzc9BpO0jcz+rOWiz5BzZo1yZkzJ+vWrSNXrlwOnFkkfdKzm4kyZ87M4sWLyZgxI82bNycqKsrsSGKwU6dOMX/+fAYMGKBiUgTbhphD/tDB1/ax0b8VyeN19IXD/rb5ihQpwqpVq7hw4QKNGzfWv7UiDqBnOJPlzZuXZcuWcfr0aTp06EBCQoLZkcRAEyZMIGvWrHTr1s3sKCJO4+/9Wct42x6z9+zvB/Vnfeqpp1i5ciVHjhyhefPm3Lhxw74JReQfVFA6gdKlSzNv3jxWr17Na6+9hu5CSBtiYmKYPHkyvXr1IkuWLGbHEXE6rXLb+qmGVoROvji8P2vFihVZtmwZO3fupG3btty+fdv+P4SIALqH0qlMnTqVHj168MUXX/DGG2+YHUfs9M0339CvXz+OHz9OoULqVSLyIKnVn3X16tU0a9aMpk2bMmfOHDw8PIz6I4ikWyooncy7777LiBEjmDt3Lu3atTM7jjyipKQkSpcuTdmyZZk7d67ZcURckiP7sy5ZsuROp41p06bpHmcRO+llmZMZNmwYx44d4/nnn+eJJ57A39/f7EjyCFasWMGhQ4cICgoyO4qIy7JYwNdBJ0O1aNGCH3/8kS5dupAlSxYmTJiARU0qRR6ZViid0K1bt6hfvz5Hjx4lLCyMwoULmx1JHlJAQABXrlxh69atepIScWJBQUH07NmTwYMHM3LkSP2+ijwirVA6IS8vLxYuXEi1atVo1qwZmzZtInv27GbHkhQ6cOAAK1eu5Mcff9STk4iT69GjBzExMQwcOBAfHx/ee+89syOJuCTdNOKk8uTJw7Jlyzh//jyBgYHEx8ebHUlSaOzYseTLl48OHTqYHUVEUmDAgAEMGzaM999/n6+//trsOCIuSQWlEytZsiQLFixgw4YNvPrqq2on5AIuX77MDz/8QN++fcmQwUE3f4mI4d59913eeustBg0apHufRR6BLnk7udq1axMUFES3bt0oVqwYQ4YMMTuS3MfkyZNJSkqid+/eZkcRkYdgsVj47LPPiImJoVevXnh7e9OpUyezY4m4DBWULqBr164cO3aMd955hyJFitCxY0ezI8ldxMfHM378eJ577jny5MljdhwReUgWi4Xx48cTExND165d8fb2pkWLFmbHEnEJ2uXtIqxWK926dWPu3LmsWbOGGjVqmB1J/mX27Nl06tSJPXv2UK5cObPjiMgjSkhIoGPHjvzyyy/88ssv1K9f3+xIIk5PBaULuX37Ng0bNuTgwYNs2bKFokWLmh1J/qZ69epkzpyZ1atXmx1FROx0+/ZtWrduzW+//UZISAjVq1c3O5KIU1NB6WIuX75M9erVcXNzY/PmzeTMmdPsSAJs2bKF6tWrs3jxYl0iE0kjbty4QZMmTdizZw9r166lYsWKZkcScVoqKF3Q0aNHqVatGn5+fqxcuVK7iZ1A586d2bZtG4cPH9YRbiJpSFRUFA0aNODEiRNs2LCBp556yuxIIk5Jz3wuqFixYixatIjQ0FB69eqldkImO3v2LMHBwfTv31/FpEgakzVrVn799Vfy5ctHgwYNOH78uNmRRJySnv1c1DPPPMO0adP44YcfGDZsmNlx0rVvvvmGzJkz0717d7OjiIgD5MqVi5CQEDJnzkyDBg34448/zI4k4nRUULqwzp0788knn/Dhhx8yY8YMs+OkSzdu3GDSpEn06NEDHx8fs+OIiIPky5ePVatWkZCQQIMGDYiIiDA7kohTUUHp4oYOHcqLL75Ijx492LBhg9lx0p0ZM2Zw9epVXnvtNbOjiIiDFSpUiNWrV3P16lUCAgK4du2a2ZFEnIY25aQBcXFxNG7cmD179hAaGkqJEiXMjpQuWK1W/Pz8KFGiBAsWLDA7joikkn379lGnTh1KlChBSEgIWbJkMTuSiOm0QpkGZMiQgXnz5uHr60uzZs2IjIw0O1K6sGrVKg4cOMDAgQPNjiIiqahs2bIsX76c8PBwWrVqxa1bt8yOJGI6rVCmISdOnMDf358SJUqwatUqvLy8zI6UpjVr1oxz586xc+dOLBaL2XFEJJVt2LCBxo0b06BBA+bNm4enp6fZkURMoxXKNKRIkSIsXryYHTt28NJLL6mdkAMdOnSIZcuWMWDAABWTIulUrVq1WLBgAcuXL6dr164kJiaaHUnENCoo05hq1arx448/MmvWLD744AOz46RZ48aNw9fXl06dOpkdRURMFBAQwM8//0xwcDC9e/cmKSnJ7EgiplBBmQYFBgby2Wef8cknnzBt2jSz46Q5V69e5fvvv+fVV1/VbQUiQtu2bfn+++8JCgri9ddf19UhSZc8zA4gjvHWW29x9OhRevXqRcGCBalXr57ZkdKMoKAgEhISeOWVV8yOIiJOomvXrsTExNCnTx98fHx04ISkO9qUk4bFx8fTvHlztm7dyubNm3UGrQESEhIoWrQoderUYfr06WbHEREn8/nnn/P222/z2WefMXjwYLPjiKQarVCmYZ6ensyZM4eaNWvSrFkztmzZgq+vr9mxXNqiRYs4ffo0AwYMMDuKiDihwYMHEx0dzdtvv02WLFno06eP2ZFEUoVWKNOB06dP4+/vT+HChVmzZg2ZMmUyO5LLevbZZ3Fzc2P9+vVmRxERJ2W1Whk0aBBjxoxh+vTpdOvWzexIIg6nFcp0oGDBgixZsoRatWrxwgsv8PPPP+Pmpv1YD2v79u1s3LiR+fPnmx1FRJyYxWLhq6++IiYmhu7du5MlSxbatm1rdiwRh1JVkU5UqVKFn376ieDgYIYOHWp2HJc0ZswYChcuTMuWLc2OIiJOzmKxMGnSJDp06ECnTp1Yvny52ZFEHEoFZTrSunVrvvzySz777DMmT55sdhyXcv78eWbPnk2/fv1wd3c3O46IuAB3d3d++OEHGjduTJs2bdiwYYPZkUQcRgVlOjNw4ED69OnDq6++SkhIiNlxXMbEiRPJmDEjPXr0MDuKiLiQ5M2RzzzzDM2bN2fbtm1mRxJxCG3KSYcSEhJo1aoVGzduZNOmTfj5+ZkdyandunWLAgUK0LlzZ8aOHWt2HBFxQTExMTRq1Ijff/+d9evXU7ZsWbMjiRhKBWU6FR0dzbPPPsvVq1cJCwsjX758ZkdyWlOnTqVnz54cOnSI4sWLmx1HRFzUtWvXqFu3LufPn2fDhg2UKFHC7EgihlFBmY6dPXsWf39/Hn/8cdavX0/mzJnNjuR0rFYrFSpUuLNTXkTEHpcuXaJWrVrExsby22+/UahQIbMjiRhC91CmY0888QRLly7l4MGDPPfccyQmJpodyemsW7eOvXv3MnDgQLOjiEgakCdPHlatWoWHhwcNGjTg/PnzZkcSMYRWKIWlS5fSqlUrBg4cyJdffml2HKfSqlUrjh8/zt69e7FYLGbHEZE04sSJE9SsWZOcOXOybt06cuXKZXYkEbtohVJo3rw5Y8aMYfTo0XzzzTdmx3Eax44dY8mSJQwYMEDFpIgYqkiRIqxatYoLFy7QuHFjoqKizI4kYhcVlALAa6+9xoABA+jXrx/Lli0zO45TGDduHDlz5uS5554zO4qIpEFPPfUUK1eu5MiRIzRv3pwbN26YHUnkkemSt9yRmJhI27ZtWbNmDRs3bqR8+fJmRzJNVFQUTzzxBP379+eTTz4xO46IpGGhoaE0bNiQmjVrsmjRIjJmzGh2JJGHphVKucPd3Z2ffvqJEiVK0KxZM/744w+zI5lm6tSp3Lx5kz59+pgdRUTSuOrVq7N48WLWrVtH586dSUhIMDuSyEPTCqX8x7lz56hWrRq5c+dmw4YNZMmSxexIqSoxMZHixYtTvXp1Zs6caXYcEUknlixZQtu2bencuTPTpk3DzU1rPuI69NMq//H444+zdOlSjh49SufOndNdO6GlS5dy4sQJBgwYYHYUEUlHWrRowY8//siMGTPo27cvWu8RV6IVSrmnFStW0KxZM/r06ZOujhysW7cucXFxbNq0yewoIpIOBQUF0bNnT9566y0+++wzdZkQl+BhdgBxXgEBAUyYMIFXXnmFYsWK0b9/f7MjOdzu3btZt24dc+bMMTuKiKRTPXr0ICYmhoEDB+Lj48P7779vdiSRB1JBKffVu3dvjh49ysCBAylcuDAtW7Y0O5JDjRkzhgIFCtCmTRuzo4hIOjZgwACio6N5//338fHx0Wld4vRUUMoDffbZZ5w4cYLOnTuzYcMGKleubHYkh4iIiOCnn35i2LBheHjoV0NEzPXuu+8SHR3NoEGD8PHxoUePHmZHErknPWvKA7m5ufHDDz9Qt25dWrRoQVhYGAUKFDA7luG+/fZbPDw86Nmzp9lRRESwWCyMHDmSmJgYevXqhbe3N506dTI7lshdaVOOpNjFixfx9/cna9asbNy4kaxZs5odyTC3b9+mUKFCtG3bVsdPiohTSUpKonv37vz000/Mnz+fFi1amB1J5D/UNkhSLG/evCxbtozTp0/ToUOHNNV8d/bs2Vy8eDFdbDwSEdfi5uZGUFAQLVu2pH379qxevdrsSCL/oRVKeWirVq2iSZMm9OjRg4kTJ7p8Swur1UrlypXJmzcvv/76q9lxRETu6vbt27Ru3ZoNGzYQEhJCjRo1zI4kcodWKOWhNWjQgG+//ZZJkyYxevRos+PYbePGjezatUu7KEXEqWXMmJF58+ZRpUoVmjZtys6dO82OJHKHVijlkQ0dOpSRI0cSHBxM27ZtzY7zyNq1a8fBgwcJDw93+dVWEUn7oqKiaNCgASdOnGD9+vWULl3a7EgiKijl0SUlJdGlSxcWL17MunXrqFq1qtmRHtrJkycpWrTonQbuIiKu4PLly9SpU4crV67w22+/8eSTT5odSdI5FZRil1u3blG/fn2OHj1KWFgYhQsXNjvSQ3nzzTeZOnUqZ86cwdvb2+w4IiIpduHCBWrVqkVCQgK//fYb+fPnNzuSpGO6h1Ls4uXlxcKFC8mSJQvNmjXj2rVrZkdKsejoaKZMmcLLL7+sYlJEXE6+fPlYtWoViYmJNGjQgIiICLMjSTqmglLslidPHpYtW8b58+cJDAwkPj7e7EgpMn36dGJiYujbt6/ZUUREHknBggVZtWoVV69eJSAgwKVe1EvaooJSDFGyZEnmz5/Phg0bePXVV3H2OymSkpIYO3Ys7dq1S5On/ohI+lG8eHFWrVrF6dOnadKkCTExMWZHknRIBaUYpk6dOkyZMoWgoCA+++wzs+Pc16+//sqRI0fUKkhE0gQ/Pz+WL19OeHg4rVq14tatW2ZHknRGm3LEcB999BEff/wxs2fPpkOHDmbHuauGDRsSFRXFli1b1CpIRNKMDRs20LhxY+rXr8/8+fPx9PQ0O5KkEyooxXBWq5Vu3boxd+5c1q5dS/Xq1c2O9A/79++nbNmy/PTTT3Tu3NnsOCIihlqxYgUtWrSgbdu2zJw5E3d3d7MjSTqgglIc4vbt2zRs2JCDBw+yZcsWihYtanakO3r16sWyZcs4efKkXr2LSJo0f/58OnTowAsvvMDkyZNxc9MdbuJY+gkTh8iYMSMLFiwgR44cNGvWjCtXrpgdCYDIyEhmzJhB3759VUyKSJrVtm1bvv/+e6ZOncqgQYOcfqOkuD4VlOIwuXLlYtmyZURGRtK2bVvi4uLMjsR3330HwMsvv2xyEhERx+ratSvffPMNY8eO5YMPPjA7jqRxKijFoYoVK8bChQsJDQ2lV69epr5KjouLY8KECXTt2pXcuXOblkNEJLW8+uqrfP7553zyySd8/vnnZseRNMzD7ACS9tWsWZNp06bRpUsXihUrxvvvv29KjuDgYM6dO0f//v1NmV9ExAxvvfUW0dHRvP3222TJkoU+ffqYHUnSIBWUkio6d+7M8ePHee+993jyySd57rnnUnV+q9XK119/TYMGDfDz80vVuUVEzPbxxx8THR1N3759yZIlC926dTM7kqQxKigl1QwdOpSjR4/y0ksvUbBgQZ599tlUm3vLli1s27aNpUuXptqcIiLOwmKxMHr0aGJiYujevTve3t60a9fO7FiShqhtkKSquLg4GjduzJ49ewgNDaVEiRKPNI7VCpfi4UYixFkhgwUyu0MeT7hbn/KOHTuya9cufv/9d7XPEJF0KzExkeeff5558+axaNEimjRpYnYkSSNUUEqqu3r1KjVq1CAhIYHQ0NAUbZCJjIM112BHNGyNgh0xEJ3436/zcYfKWaBqVqjsA/Wyw82LZyhSpAhff/01r732muF/HhERVxIfH0+7du0ICQlh+fLl1K5d2+xIkgaooBRTHD9+nGrVqlGiRAlWrVqFl5fXf77GaoUtUTDhD5h9CRKs4GGxvX+Q5K/zsEDJszs5OWYw51cvxMcniwP+NCIiruXWrVs0b96csLAwVq9eTdWqVc2OJC5OBaWYZsuWLdStW5c2bdowc+bMf5ypvSgS3jsB+2NTXkTeU0I8eHhS1hs+KQIt1TFIRISYmBgCAgI4ePAg69evp2zZsmZHEhemm8nENNWqVePHH39k1qxZfPjhhwBcjocuB6D1fjgQa/s6u4pJAA/biTjhsdBqv238y/F2jiki4uKyZMnCL7/8QuHChWnYsCGHDx82O5K4MK1Qiuk+//xz3n77bfrNXs1Pj9fjWgLc5fZIw7gD2T1gSklonceBE4mIuIBLly5Ru3ZtYmJi+O233yhUqJDZkcQFqaAU0yUlWfEfu5DtFdpgsVqx3m2btsHcgCRgeBEYUvDuO8NFRNKLP/74g2effRZ3d3c2bNjAY489ZnYkcTEqKMVUVisMPQEjT5uX4Z2C8GkRFZUikr6dOHGCmjVrkiNHDtavX0+uXLnMjiQuRPdQiqlGnDa3mHSWDCIiZitSpAirVq3i4sWLNG7cmKioKLMjiQvRCqWYZuElaBNudoq/LPSDVtoBLiLp3K5du6hbty7lypVj+fLlZM6c2exI4gJUUIopLsdDyTC4kgDO8APoBuTwgEP+kMvT7DQiIuYKDQ2lYcOGPPPMMyxevJiMGTOaHUmcnC55iyn6HYFrTlJMgm2DzrUE6H/E7CQiIuarXr06ixcvZv369XTu3JmEhASzI4mTU0EpqW5RJMyKcGxroEeRCPwUAYsjzU4iImK+evXqERwczJIlS3jppZdISkoyO5I4MRWUkqqsVtsJOM76g+eGLZ9uBBERgebNmzNjxgxmzpxJ37590V1yci8eZgeQ9GVLlO04RWeVBOyLhbAoqJbN7DQiIubr2LEjsbGx9OjRAx8fHz777LN/HJUrAiooJZVN+MOAs7kdzMMCE86poBQRSfbSSy8RExPDgAED8PHx4f333zc7kjgZFZSSaiLjYPYlA4rJ3etgUN27f25CKJSuZtfwCVb4OQK+Kgq5M9g1lIhImtG/f3+io6N577338PHxYeDAgWZHEieiglJSzZprBq9Mtu0PpZ7+52P5ixkydIIV1l6D9r6GDCcikiYMHTqUqKgoBg0aRJYsWejZs6fZkcRJqKCUVLMj2uDL3eWehdqBBg32Tx4WW14VlCIif7FYLIwcOZKYmBhefvllvL296dy5s9mxxAmooJRUExblgHsnb0RDxkzgbuyPcoIVtkYbOqSISJpgsVgYN24cMTExdO3aFW9vb1q2bGl2LDGZs3ZvkTTGaoWdMQYP+ll3aJYVGnnZ7qk8tN3Q4bdHq32QiMjduLm5ERQUROvWrWnfvj2rVq0yO5KYTEcvSqqIiIO8mw0abP9mmDsa/JtCttxw6gDM/gJuxcL4zVC8okETwcUa4KuNOSIidxUXF0erVq3YsGEDISEh1KhRw+xIYhIVlJIqTt6EImEOnOCPo9CjHJSrBZ8vN2zYk9WgkJdhw4mIpDk3btygSZMm7NmzhzVr1lCpUiWzI4kJdMlbUkWco1+25C8Gz7SC3Wsh0bhDHW/rpDERkfvKnDkzS5YsoUSJEgQEBHDgwAGzI4kJVFBKqsiQGocq5CkA8XG2S98GyajfEBGRB8qaNSvLly/nscceo2HDhhw/ftzsSJLK9HQpqSKzeypMcv44ZPCCTFkMGzKTfkNERFIkZ86crFy5Em9vb+rXr8/Zs2fNjiSpSE+XkiryeIKPUUXltUv/fezoHti8GKo0Ajdjfqx93G25RUQkZfLly8eqVatISkqiQYMGREREmB1JUok25UiqqbML1l83YKDX60GGTOBXA7L72nZ5L/0O3D1tRy8WesqASaBudlhTwZChRETSlSNHjvDss8+SL18+1q5dS44cOcyOJA6mFUpJNf5ZbSfQ2O2Z1nA90tY66Os+sHY2PNsWJm03rJj0sEBVH0OGEhFJd4oXL86qVas4c+YMTZs2JSbG6EbE4my0QimpZk4EdHShzX9zSuvoRRERe2zfvp169erx9NNP88svv+DlpT5saZVWKCXV1Mtu0AplKvCw2C55i4jIo6tSpQq//PILoaGhtG/fnvj4eLMjiYOooJRUkzsDdMzj/EWlhwU6+dryioiIfZ599lkWLFjAypUr6dq1K4kG9goW56GCUlJV3/yQ4OQ3WSRYoe/jZqcQEUk7AgIC+PnnnwkODubll18mKUmnRqQ1KiglVVXLCmW9nfcHzw0o523bQCQiIsZp06YN06ZNY+rUqQwaNAht4UhbPMwOIOmLxQKfFIFW+81OcndJwLAitpwiImKs559/nujoaPr06YOPjw+ffPKJ2ZHEICooJdW1zA2dfW27vp3qTpqkRFg7m22rD9L4/ffJkEE3UYqIGO3VV18lJiaGwYMH4+Pjw9tvv233mFYrXIqHG4kQZ7Ud95v5z8MptECQOlRQiinGFYeVV+Bqgm1V0GxuQI4MbvTM9AcjPxzJ4sWLmTZtGhUrVjQ7mohImvPWW28RHR3NkCFDyJIlC3379n2o74+MgzXXYEc0bI2CHTEQfZcVCh93qJwFqmaFyj62biPacOkY6kMppll4CdqEm53iLwv9oFVu2L17Ny+++CLh4eG8++67DB06VKuVIiIGs1qtvP7663z99ddMmzaNF1544QFfD1uiYMIfMPuSbQOlhyVlGz2Tvy65i0ffx233ymv10jgqKMVUw0/BuyfMTgHDi8A7hf76OC4ujuHDh/Ppp5/i5+fHtGnTKF++vHkBRUTSIKvVyssvv8zUqVOZM2cO7dq1u+vXLYqE907A/tiUF5H3kvz9Zb1t9/S3zP3oY8lfnHWzraQT7xS0vZmdYci/MmTIkIGPPvqIsLAwEhMTqVKlCv/73//UlFdExEAWi4Vvv/2Wjh070rlzZ3799dd/fP5yPHQ5AK33w4FY22P2tp5L/v7wWNsG0S4HbPOIfbRCKaazWmHkaRh6wvYKJzXuqUyeZ0QRGFLo/l8bFxfHsGHDGDFiBOXKlWP69OmULVs2FVKKiKQP8fHxBAYGsnLlSpYvX07t2rVZeAl6HoJrCY7dwOkOZPeAKSWhdR4HTpTGqaAUp7EoEnr8nnr/eASVst0zmVLbt2/nxRdf5PDhw3z44Ye8/fbbeHhoX5uIiBFu3bpF8+bN2RIWRrflB5gYXyDVFxmGF7FdsdK9lQ9PBaU4lcvx0O8IzIowfrUyebwuvrZd5jk9H36M27dv8/HHH/PZZ59RsWJFpk2bhp+fn4EpRUTSr5iYWEp9OZ8/anc1LcM7BeFT9SN+aLqHUpxKLk/4qbRtx3UZb9tj9p79nfz9ZbxhkR/MLP1oxSRAxowZGT58OKGhody4cYPKlSszYsQIEhIS7AspIiKMvextajEJMOK07TYseThaoRSnZbVCWBRMOAc/R9hupPa0QPxDtIjwTG4RkR+q+hj7ivPWrVt89NFHjBo1isqVKzNt2jRKly5t3AQiIumIs7aSk5RRQSkuITIO1l6D7dGwLdr2/l5NbKv42IrHyj5QN7vjm9hu2bKFF198kZMnT/K///2PN954A3d3d8dOKiKShlyOh5JhcCUBnKEocQNyeMAhf9uVM3kwFZTikpKP2bqZBLeTIKMbZHIz75itmzdv8sEHH/Dll1/i7+/P999/T6lSpVI/iIiIC+pywPmO43UHOvrabpOSB1NBKWKgzZs30717d06dOsWnn37KwIEDtVopInIfiyJtfSad1SI/NT9PCW3KETFQjRo12L17N3379uWtt96iVq1aHD582OxYIiJOyWq1nYDjrMWIG7Z8Wnp7MGf9fyjisjJlysSXX37Jhg0biIiIoHz58nz11VckJjrTxRwREfNtibIdp5gavSYfRRKwL9a2QVTuTwWliIPUrFmTPXv20Lt3b9544w3q1KnD0aNHzY4lIuI0Jvxhf2s4R/Ow2LqNyP2poBRxoMyZM/P111+zbt06zp07R7ly5Rg7dixJSc76elxEJHVExsHsS/afzQ3AoR0wuDE0ywpNfeCtRnB0twED2/L9HGHLK/emglIkFdSqVYu9e/fSs2dPBgwYQN26dTl+/LjZsURETLPmmkHF5OGd0L8mnD8OL3wI3T6As0dgYG04fciACWw5114zZKg0SwWlSCrx9vZm7NixrF27ltOnT1O2bFkmTJig1UoRSZd2RBt0uXvq+5AxE4wPhQ5vQKe3YPxmSEqCKUMNmMCWc0e0IUOlWSooRVJZnTp12LdvHy+++CKvvfYa9evX58SJE2bHEhFJVWFRBq1Q7vsNKjWAbLn+eizXY1C+NmxZCjdj7J4iwQpbVVDelwpKERNkyZKFCRMmsHr1ak6cOEHZsmWZOHGiVitFJF2wWmGn/XWeTfxt2wrlv2XMDPFxcMKYJpfbo9U+6H5UUIqYqF69euzbt4/nn3+ePn360KhRI06dOmV2LBERh7oUf/fjcx9JgZJwcAv8vTVbfBz8HvbnZH8YMk10oi233J0KShGT+fj48O2337Jy5UoOHz6Mn58f3333HTrESkTSqhtGtuVt1QfOHIZRPeDkAduK5IhucPm87fNxNw2b6qYuIt2TCkoRJ9GwYUP2799Pp06d6N27NwEBAZw+fdrsWCIihosz8vVyy1fguaGw+ifoXgZeKgvnjkGnwbbPZ8pi2FS3VVDekwpKESeSNWtWJk+ezPLlyzl48CB+fn4EBQVptVJE0pQMRjcz7/kpzL8IY3+DoL3w7TbbLm+AJ0oYNk1GVU33pL8aEScUEBDA/v37ad++PT179qRp06acPXvW7FgiIobI7O6AQX1yQNma8GRZ28c7V0GeJ6BgKcOmyKSq6Z70VyPipLJly0ZQUBC//PILe/fuxc/Pj++//16rlSLi8vJ4go8jispka2bD79sgcCC4GVPq+LjbcsvdqaAUcXJNmzZl//79tG7dmpdeeonmzZvzxx/G7FoUETGDxQKVjLq1cc8GeKMBzPocfgmCL3rBp89B1cbQboBBk0AVH1tuuTsVlCIuIEeOHEybNo0lS5awa9cu/Pz8+OGHH7RaKSIuyz+rQSfl5M4Pbu4wexSM6Qv7NkKPT+CTReDuYcAEtpxVfQwZKs2yWPWMJOJSrly5woABA5gxYwYtWrRg0qRJPPbYY2bHEhF5KHMioOMBs1Ok3JzS0N7X7BTOSyuUIi4mZ86c/PjjjyxcuJCtW7dSpkwZZs6cqdVKEXEp9bIbtEKZCjwsUDe72SmcmwpKERfVqlUrwsPDadKkCc8//zxt2rThwoULZscSEUmR3BmgYx7nLyo9LNDJ15ZX7k0FpYgLy5UrFzNnzmT+/PmEhoZSpkwZZs2apdVKEXEJffNDgpP/c5Vghb6Pm53C+amgFEkD2rRpQ3h4OA0bNqRLly4EBgYSERFhdiwRkfuqlhXKejtvMeIGlPO2bSCS+3PW/4ci8pBy587Nzz//zNy5c9mwYQNlypRhzpw5ZscSEbkniwU+KQLOeqJhEjCsiNoFpYQKSpE0JjAwkPDwcOrUqUPHjh3p0KEDly5dMjuWiMhdtcwNnX3BkX3OH4U70MXXlk8eTG2DRNKwOXPm0KdPH9zc3Jg4cSLt2rUzO5KIyH9cjoeSYXA1wTlWK92AHB5wyB9y6XScFNEKpUga1qFDB8LDw6lZsyaBgYF06tSJyMhIs2OJiPxDLk+YUtI5ikmw5QgqpWLyYaigFEnj8ubNy7x58/jpp58ICQmhTJkyLFiwwOxYIiL/0DoPfFrE7BQ2w4tAK13qfigqKEXSAYvFQufOnQkPD6d69eq0bduWLl26cPnyZbOjiYjc8U5B25vZGYaYnMEV6R5KkXTGarUyc+ZM+vfvT4YMGZg0aRKtWrUyO5aICABWK4w8DUNP2Fa9UuMyePI8I4rAkEKpMGEapBVKkXTGYrHw/PPPs3//fp5++mlat25N165duXLlitnRRESwWOCdQrDQz7YxxtG7v92xzbPQT8WkPbRCKZKOWa1WfvzxR/r370/mzJn57rvvaN68udmxREQA2+7vfkdgVoTxq5XJ43XxhXHFIac24NhFK5Qi6ZjFYqFbt26Eh4dTsWJFWrRowYsvvsi1a9fMjiYiQi5P+Km0bfWwjLftMUtigl1jJp8dXsYbFvnBzNIqJo2gglJEyJ8/P0uXLmXq1KksWLCAMmXKsGzZMrNjiYgAth3XszIfgD7VqBn/x52i0DOlJ9gkxN/5+s6+sKUS7KmipuVGUkEpIoBttbJ79+7s37+fsmXL0qxZM1566SWuX79udjQREaZODSL3pWOsqvcY56vDnNIw6Amomx187nGjpY+77fOVjq4lz4S+/FHdyg9P2c7m1nGKxtI9lCLyH1arlaCgIF5//XWyZcvGlClTCAgIMDuWiKRTcXFx5M+fn27duvHll1/+5/NWK1yKh5tJcDsJMrpBJjfI42krHJcuXUqLFi04dOgQJUqUMOFPkPZphVJE/sNisdCzZ0/279/PU089RePGjenVqxdRUVFmRxORdGjx4sVERkbSo0ePu37eYgHfDFDIC0pktr33zfDXKmSdOnXw9PRkxYoVqZg6fdEKpYjcl9VqZfLkybzxxhvkyJGDoKAgGjZsaHYsEUlHGjduTFRUFJs3b37kMerVq0fmzJlZunSpgckkmVYoReS+LBYLL7/8Mvv376dEiRI0atSIV155hejoaLOjiUg6cPr0aVauXHnP1cmUCggIYO3atdy+fdugZPJ3KihFJEUKFSpESEgIEydOZMaMGZQtW5bVq1ebHUtE0rjvv/8eb29vOnbsaNc4AQEB3Lhxg02bNhmUTP5OBaWIpJjFYuGVV15h3759PPnkkzRo0IC+ffsSExNjdjQRSYMSExOZOnUqHTt2JEuWLHaNVa5cOfLmzav7KB1EBaWIPLQiRYqwatUqxo8fz7Rp0yhXrhzr1q0zO5aIpDGrV6/m9OnT9OzZ0+6x3NzcaNSoEcuXLzcgmfybCkoReSRubm707duXvXv3UqBAAerWrUu/fv2IjY01O5qIpBFBQUGULl0af39/Q8YLCAhg7969nD9/3pDx5C8qKEXELkWLFmXt2rWMGTOGoKAgypUrx4YNG8yOJSIuLjIykgULFtCzZ08sBnUhb9SoERaLhZUrVxoynvxFBaWI2M3NzY3+/fuzd+9eHn/8cerUqcPAgQO5ceOG2dFExEXNmDEDgK5duxo2Zp48eahUqZLuo3QAFZQiYphixYqxbt06Ro8ezaRJkyhfvjwbN240O5aIuBir1cqUKVNo3bo1uXMbe+B2QEAAISEhJCUlGTpueqeCUkQM5e7uzsCBA9mzZw++vr7UqlWLN954g5s3b5odTURcxNatWwkPD7e79+TdBAQEEBkZyc6dOw0fOz1TQSkiDlGiRAk2bNjAqFGjmDBhAhUqVCA0NNTsWCLiAqZMmULBggVp0KCB4WNXr14dHx8fXfY2mApKEXEYd3d33njjDXbv3k2OHDmoWbMmb731llYrReSeYmJi+Pnnn3nppZdwd3c3fHxPT0/q1aungtJgKihFxOFKlSrFpk2bGDFiBOPGjaNSpUqEhYWZHUtEnNCcOXOIjY2le/fuDpsjICCAzZs3c/36dYfNkd6ooBSRVOHu7s7gwYPZuXMnPj4+1KhRgyFDhnDr1i2zo4mIEwkKCqJRo0YULFjQYXMEBASQmJjImjVrHDZHeqOCUkRSVenSpdm8eTOffvopX331FZUrV2bbtm1mxxIRJ3Dw4EE2b97skM04f/fkk09SvHhxXfY2kApKEUl1Hh4eDBkyhB07dpApUyaqV6/Ou+++y+3bt82OJiImCgoKInfu3LRs2dLhcwUEBLBixQqsVqvD50oPVFCKiGn8/PwIDQ3l448/ZtSoUVSpUoUdO3aYHUtETBAXF8f06dPp2rUrGTNmdPh8AQEBnDx5kiNHjjh8rvRABaWImMrT05N3332X7du34+npib+/P++//z5xcXFmRxORVLRkyRIiIyMdfrk7WZ06dfD09NRlb4NYrFrrFREnER8fz4gRIxg2bBilS5dm2rRpVKxY0exYIpIKmjRpwrVr11K1X229evXInDkzS5cuTbU50yqtUIqI0/D09OSDDz5g27ZtWCwWqlatykcffaTVSpE07syZM6xYsYKePXum6rwBAQGsXbtW928bQAWliDidChUqsHXrVt59910+/fRT/P392bNnj9mxRMRBvv/+ezJnzkyHDh1Sdd6AgABu3LjBxo0bU3XetEgFpYg4pQwZMvDRRx8RFhZGYmIiVapUYdiwYcTHx5sdTUQMlJSUxNSpU+nUqRM+Pj6pOnf58uXJly+f7qM0gApKEXFqlSpVYvv27QwZMoSPP/6YatWqsW/fPrNjiYhBVq9ezalTp1JtM87fWSwWGjVqpILSACooRcTpZciQgWHDhrFlyxZu375N5cqV+fTTT0lISDA7mojYKSgoiNKlS1OtWjVT5g8ICGDv3r2cP3/elPnTChWUIuIykvtUvvnmm3zwwQdUr16d8PBws2OJyCO6fPkyCxYsoEePHlgsFlMyNGzYEIvFwsqVK02ZP61QQSkiLiVjxowMHz6c0NBQYmNjqVSpEiNGjNBqpYgLmjFjBlarla5du5qWIU+ePFSqVEmXve2kglJEXFLVqlXZuXMngwYN4r333qNGjRocOHDA7FgikkJWq5UpU6bQqlUr8uTJY2qWgIAAVq5cSWJioqk5XJkKShFxWV5eXowcOZJNmzYRFRVFpUqV+Pzzz/WkIOICtm3bxv79+1O99+TdBAQEcPnyZXbu3Gl2FJelglJEXF61atXYtWsX/fr1Y8iQIdSsWZPff//d7Fgich9TpkyhQIECNGjQwOwoVK9eHR8fH132toMKShFJEzJlysSoUaPYuHEjly9fpkKFCnz55ZdarRRxQjExMcyaNYuXXnoJd3d3s+Pg6elJ/fr1VVDaQQWliKQpNWrUYPfu3fTp04e33nqLWrVqcfjwYbNjicjfzJ07l9jYWLp37252lDsCAgIIDQ3l+vXrZkdxSSooRSTNyZw5M6NHj2bDhg1ERERQvnx5vvrqK61WijiJoKAgGjZsSKFChcyOckdAQACJiYmsWbPG7CguSQWliKRZNWvWZM+ePfTu3Zs33niDOnXqcPToUbNjiaRrBw8eZNOmTaacjHM/RYoUoXjx4rrs/YhUUIpImpY5c2a+/vpr1q1bx7lz5yhXrhxjx44lKSnJ7Ggi6dLUqVPJlSsXrVq1MjvKfwQEBLBixQqsVqvZUVyOCkoRSRdq1arF3r176dmzJwMGDKBu3bocP37c7Fgi6UpcXBzTp0+na9euZMyY0ew4/xEQEMDJkyc5cuSI2VFcjgpKEUk3vL29GTt2LGvXruX06dOULVuWCRMmaLVSJJUsXbqUS5cuOd3l7mR16tTB09OT5cuXmx3F5VisWtcVkXQoJiaGt99+m2+++YY6deowdepUihQpYnYskTStadOmXLlyhS1btpgd5Z7q1atHpkyZ+OWXX8yO4lK0Qiki6VKWLFmYMGECq1ev5sSJE5QtW5aJEydqtVLEQc6cOcOKFSuc4mSc+2ncuDHr1q3j9u3bZkdxKSooRSRdq1evHvv27eP555+nT58+NGrUiFOnTpkdSyTNmTZtGpkyZaJjx45mR7mvgIAAbty4wcaNG82O4lJUUIpIuufj48O3337LypUrOXz4MH5+fnz33Xfa6SlikKSkJKZOnUrHjh3x8fExO859lStXjnz58ql90ENSQSki8qeGDRuyf/9+OnXqRO/evQkICOD06dNmxxJxeWvWrOHkyZNOuxnn7ywWC40aNVJB+ZBUUIqI/E3WrFmZPHkyy5cv5+DBg/j5+REUFKTVShE7BAUF8dRTT1G9enWzo6RIQEAAe/fu5dy5c2ZHcRkqKEVE7iIgIID9+/fTvn17evbsSdOmTTl79myq57BaISIOTt6Ewzds7yPibI+LuILLly8zf/58evTogcViMTtOijRs2BCLxcLKlSvNjuIy1DZIROQBli1bRq9evYiNjeWrr77ixRdfdNgTY2QcrLkGO6JhaxTsiIHouxxB7uMOlbNA1axQ2QfqZYfcGRwSScQuY8eO5c033+Ts2bP4+vqaHSfFqlSpQvHixZk1a5bZUVyCCkoRkRS4evUqgwYNYvr06TRt2pTvvvuO/PnzGzK21QpbomDCHzD7EiRYwcNie/8gyV/nYYFOvtD3cfDPCi6yECRpnNVqpXz58pQoUYLg4GCz4zyU9957j2+//ZaLFy/i7u5udhynp0veIiIpkCNHDqZNm8aSJUvYtWsXfn5+/PDDD3bfW7koEspthxq7/iomIWXF5N+/LsEKP0dA9V1QfjssjrQrloghtm/fzr59+5y+9+TdBAQEcPnyZXbu3Gl2FJegglJE5CE0b96c/fv307x5c1544QVatWrF+fPnH3qcy/HQ5QC03g8HYm2PpbSIvJfk7w+PhVb7beNfjrdvTBF7TJkyhQIFCtCwYUOzozy0atWq4ePjo93eKaSCUkTkIeXMmZMff/yRhQsXsnXrVsqUKcPMmTNTvFq58BKUDIM5EbaPjT6bJ3m8ORG2eRZeMngCkRSIjY1l1qxZdO/e3SUvGXt6elK/fn0VlCmkglJE5BG1atWK8PBwmjRpwvPPP0+bNm24cOHCPb/eaoXhp6BNOFxNgLvstTFUIrZ52oTDiFPaGS6pa+7cucTExNC9e3ezozyygIAAQkNDuX79utlRnJ4KShERO+TKlYuZM2cyf/58QkNDKVOmDLNmzfrPaqXVCkNPwLsnbB+n1onhyfMkz62iUlLLlClTaNCgAYULFzY7yiMLCAggMTGRNWvWmB3F6amgFBExQJs2bQgPD6dhw4Z06dKFwMBAIiIi7nx+xGkYafKhO86QQdKH33//nU2bNrnEyTj3U6RIEYoXL87y5cvNjuL0VFCKiBgkd+7c/Pzzz8ydO5cNGzZQpkwZ5syZw8JLf61Mmm3oCdvOchFHCgoKImfOnLRu3drsKHYLCAhgxYoVOi3rAVRQiogYLDAwkPDwcOrUqUPHXq/ScXsUFpzjycgN6PG7dn+L48TFxfHDDz/QtWtXMmbMaHYcuzVu3JhTp05x+PBhs6M4NRWUIiIO4Ovry9y5c3lm9k7iMmTGinN0Gk8CriVA/yNmJ5G0aunSpURERLj85e5kderUIUOGDNrt/QA6KUdExEEWRdr6TDqrRX7QMrfZKSStadasGZGRkYSFhZkdxTD169fHy8uLX375xewoTksrlCIiDmC1wnsnnPcfWTds+bSkIEY6e/Ysy5cvd8mTce4nICCAdevWcfv2bcD2exMRBydvwuEbtvcRcen798nD7AAiImnRlijYH2t2intLAvbFQlgUVMtmdhpJK6ZNm4aXlxcdO3Y0O4qhqjZsyo1ft/PCpvNczFGYHTEQfZdGsj7uUDkLVM0KlX2gXnbInSHV45pCl7xFRBzg+QP/PJvbGXlYoJMv/PiU2UkkLUhKSqJo0aLUrVuXqVOnmh3Hblar7YXhhD9g9iUrCVYLbkmJJLk9+NQfD4vtdz/5d6zv4+CfFSzOcSu1Qzjr1RgREZcVGefAYnLGp1DXAt397B4qwQo/R9jyithr7dq1nDx5Mk1sxlkUCeW2Q41dyb/LtkowJcUk/PW7n/w7Vn0XlN8Oi9Nwyy4VlCIiBltzzUHF5KWzMHM4eHkbNmSCFdZeM2w4ScemTJlCqVKlqFGjhtlRHtnleOhywLaZ7sCft6zY+7uc/P3hsdBqv238tNi2SwWliIjBdkTbLnUZbuKb8FQ1KFnFsCE9LLa8Iva4fPky8+fPp0ePHlhc9LruwktQMgzm/HnAldHHoyaPNyfCNs/CSwZPYDIVlCIiBguLcsAK5Z4NsD4YXvva0GETrLBVBaXYaebMmSQlJdGtWzezozw0qxWGn4I24XA1Ae6y18ZQidjmaRMOI06lnZ3hKihFRAxktcLOGIMHTUyEsf2gWU94sqzBg8P26LTzpCapz2q1MmXKFFq1aoWvr6/ZcR6K1Wo7jjT5aFSjVyXvJXme5LnTwu+fCkoREQNdir97OxG7LP4WLp6Cl4YZPLBNdKItt8ij2L59O/v27XPJzTgjTsPI08pgBBWUIiIGumF0MXn9Mkz7ALq9D9nzGDz4X26m1tKMpDlBQUE88cQTNGrUyOwoD2Xhpb9WJs029IRtZ7krU2NzEREDxRl96Wrqe+CTE9r0M3jgf/p6wkSezJBA1qxZyZYtG1mzZv3Pf3t5ebnshgtxjNjYWH766ScGDhyIu3vKWuo4g8vx0PMQWABnuNrsBvT4HWr6Qy5Ps9M8GhWUIiIGymBkvXX2CCz9Dvp+DZfP/fV43C1IjIcLJyFzVsia0+6pfpw6hZhj4XeOlrsbT0/P+xacKf3vDBnSydEh6UBwcDAxMTG89NJLZkd5KP2OwLUE5ygmwXZP5bUE6H8EZpY2O82j0Uk5IiIGioiDvJsNGmz3OhhU9/5f026AITu/L9YA3wxw+/ZtoqOjuX79OlFRUURFRT3Sf8fH3/umzIwZM9pdmGbNmhVPTxddyklDnn32Wby8vAgJCTE7SootirT1mXRWi/ygZW6zUzw8FZQiIgayWiHbRoM25lyPhH0b//t40HtwMxpeGwOPF7V757ePO1yvadyxcFarldu3bz9yMfr3/05MvPdfZKZMmVJUgN7v8z4+Pi51qdaZHDp0iFKlSvHzzz+7zNndVqvtBJwDsam3o/thuAFlvGFPFdc7plGXvEVEDGSxQKUssP66AYNlyw01W//38eCvbe/v9rlHUMXH2Ccvi8WCl5cXXl5edrWRsVqt3Lx58x+FZkoK0YsXL/7n8futnXh7e9t9GT9Lliy4uaWvfa5BQUHkzJmT1q1bmx0lxbZEwf5Ys1PcWxKwL9bWy7ZaNrPTPBwVlCIiBvPPCpsc0dzcATwsUNXH7BR3Z7FYyJw5M5kzZyZfvnyPPI7VaiU2NvahV0j/+OOPfzweHX3/DvA+Pj6PXJgmv/f29naJjU/x8fFMnz6drl27kjFjRrPjpNiEP2w/8878u+lhgQnnXK+g1CVvERGDzYmAjgfMTpFynQ7N5+O6fpQoUcLsKE4tKSmJmJiYuxagD1Osxsbee4nMzc3tH/eJPmqBmilTJocWpgsWLKBt27bs3buXsmWNb7bvCJFx8FiogcXk4Z0w/SPbbSlxt+CxJ6H5y9Cuv91De1jgfHXI7UL711RQiogYzPAnLgeyJCbg9fyT3LxwhrJly9KuXTsCAwMpXbq0S6yUuaKEhASio6Pturc0KiqKmzdv3nMODw8PQwrTjBkz3vXnoHnz5ly6dImwsDBH/lUZytAXettWwrstoFhFqNsRMmWBc8cgKQle+dyQKeaUhvYudPCQCkoREQd4/gDMvuTcRaWHBTr5wqRCN1ixYgXz5s1j8eLFREdHU6pUKQIDA2nXrh3ly5dXcemE4uPj7xSZ9hSmD2oV9e9C09PTk9WrV1OrVi2qV6+eogLVGVpFvX0MRp814HcyNgq6lgC/GvBRMDjg3lkPC7zxBIwsavjQDqOCUkTEAUKvQ41dZqd4sNCK/7xX6/bt24SEhBAcHMyiRYu4du0aRYsWvVNcVqlSRcVlGpO8Iz+lhej27ds5cuQIZcqUISYm5s7nExIS7jmHl5eX3aulWbNmxcPj0bd+1Nll0Ga5xd/CV6/CtANQ6Cm4GQsZMxleWNbNDmsqGDqkQ6mgFBFxAKsVym+HcCduT+LnDbvv054kLi6OtWvXEhwczMKFC4mMjKRQoUK0a9eOdu3aUa1atXS3szm9S0pKolixYtSuXZvvv//+zuNWq5Vbt27ZvVp6/fp1kpLu/RuTOXPmh97oZHvLRvUrpYm1GvDz+mEg7AiBj+fBmL5w5jB4eUOjrtD3K8jgZf8cGN/Oy9FUUIqIOMjiSGiVRhooJyQksGHDBoKDg5k/fz4XL17k8ccfv3PP5TPPPKN+junAmjVrqF+/Phs3buSZZ54xfHyr1cqNGzceqgC92+f/0yoqex5YEGFMyB7l4dxR23836QEV6tgOIVgwDup1gvdnGTMPfx044ApUUIqIOFCXA7bNAEb0OTeKO9DR99GPeEtMTGTz5s0EBwczb948/vjjD3x9fWnbti2BgYHUrl3brkuT4ry6dOnCzp07OXjwoFPf+pCUlERsbOydQvPQtdu0jatozODPFYVzx6HlKzBo4l+Pj34FlkyCHw/DE8UNmepkNShkzIKnw+lahYiIA40rDtk9nOcfWzdsecba8Xzn7u7Os88+y5gxYzh9+jShoaF07dqVX3/9lQYNGpAvXz569uzJ8uXLiYuLMyy7mOvKlSvMnz+fnj17OnUxCbb2Sz4+PuTPn5/SpUtTpoJBxSRAhky29/U6//Px+l1s78NDDZvqtjPeL3MPzvJvnIhImpTLE6aUdJ77KJOAoFK2XEZwc3OjWrVqfPHFF5w4cYLt27fTq1cv1q9fT5MmTcibNy8vvPACS5Ys4datW8ZMKqaYOXMmiYmJdOvWzewoDy2DkfVv7sdt73Pk/efjOf7s8RN91bCpMrpQleZCUUVEXFPrPPBpEbNT2AwvAq1SeN/kw7JYLFSuXJkRI0Zw+PBh9uzZQ79+/di2bRstW7bE19eXLl26MH/+fG7cuOGYEOIQVquVKVOm3Pn/6GoyG3l7b4nKtveRf/zz8chztvfZ8xg2VSYXqtJcKKqIiOt6p6DtzewMQ1Ipg8VioVy5cvzvf//jwIEDhIeH89ZbbxEeHk67du3IkycP7du3Z/bs2cTExKROKHlkO3bsYO/evfTo0cPsKI8kj6dt17Qh6nSwvV8W9M/Hf5kC7h62TToG8HG35XYV2pQjIpJKrFYYeRqGnrC9mk+Ny+DJ84woAkMKpcKEKXDkyBHmzZtHcHAwO3bswMvLi8aNG9OuXTtatGhBtmwudohxOvDqq6+yZMkSTp065bK7+Q3rQwnweQ/4daqtuCxf27bLe/1c6PIO9BpuyBTqQykiIve1KBJ6/A7XEhy7+9sd2wacoFKOu8xtrxMnTjB//nyCg4PZsmULGTJkoGHDhgQGBtKyZUty5sxpdsR078aNGzz22GP079+fYcOGmR3nkRl2Ug5AQjzMHA6/fg+Xz0HeQtC6LwQONGBwnZQjIiIpdDke+h2BWRHGr1Ymj9fF17bLPKeLXDY7c+YMCxYsIDg4mI0bN+Lu7k69evUIDAykdevW5Mlj3L1pknI//PADL7zwAsePH6dIESe5GfgRGHqWdyrQWd4iIpJiiyLh/ROwL9a2KmHP6kny95f1hk+KpLxpuTM6f/48CxYsYN68eaxbtw6A2rVrExgYSJs2bXjsscfMDZiO1KpViwwZMrBq1Sqzo9glMg4eC7WSYHXulkdg+10+Xx1yu0hTc1BBKSJiOqsVwqJgwjn4OcJWFHpaID4F/zonF5GeFujkC33zQ1Uf1zmuLSUuXbrEwoULCQ4OZs2aNSQmJvLMM88QGBhI27ZtKVCggNkR06zDhw9TsmRJZs2aRadOncyO88iuXLnC5MmT+V9CcW74twAP51229/jzd/nHp8xO8nBUUIqIOJHIOFh7DbZHw7Zo2/vou9xo6eMOVXxsxWNlH9sN/K60mvGorly5wuLFiwkODiYkJIS4uDj8/f0JDAykXbt2Ln1J1hm9/fbbTJ48mXPnzuHl5SJHtvzN/v37GTt2LDNmzCApKYkG/d/nl6bvmh3rgUIrQjUX25umglJExIlZrXApHm4m2U7NyOhm602XxzNtrUI+iuvXr7N06VKCg4NZvnw5t27dolKlSneKyxIlSpgd0aXFx8dToEABOnbsyJgxY8yOk2KJiYn88ssvjBkzhjVr1vD444/Tp08fXn75ZXLnzkP57RAe6zyHDfydG+DnDburuN7vtwpKERFxeTExMSxbtozg4GB++eUXbty4QdmyZQkMDCQwMJDSpR/x4PJ0bOHChbRp04Y9e/ZQrlw5s+M80PXr15k6dSrjx4/n+PHjVKtWjQEDBtCuXTs8Pf+6xL04ElrtNzHoAyzyc837n1VQiohImnLjxg1WrFhBcHAwS5YsITo6mqeeeop27doRGBhIuXLlnP4sakdJXvG+kQhxVtuRhJnd777i3aJFCy5evMjWrVvNCZtChw4dYty4cUybNo24uDg6dOhA//79qVq16j2/p8sB265vR7bteljuQEdfmOmir31UUIqISJp169YtVq1aRXBwMIsWLeLatWsUK1bsTnFZuXLlNF1cRsbBmmuwIxq2RsGOmHvfk1s5C1TNarsn96lb56lQ5Am++eYbevfuneq5HyQpKYmVK1cyZswYli9fjq+vL6+88gqvvPJKijoAXI6HkmFwNcE5Ln27ATk84JA/5HLe/UL3pYJSRETShbi4ONasWcO8efNYsGABly9fplChQneKS39/f9zcXP9EYqsVtkTBhD9g9iVbF4CUtqRK/jq3pEQs62az4tVW1Mvn7TT388XExDB9+nTGjRvHoUOHqFSpEgMGDKBjx45kzJjxocZaeAnahDso6CNY6Oe8BxCkhApKERFJdxISEli/fj3z5s1j/vz5XLx4kfz589OuXTvatWvHM88845JHDC6KhPdOwH4D+ppakhKxurk7RV/T48ePM378eIKCgoiNjaVt27YMGDCAGjVq2LXCPPwUvHvCwKCPmqMIvOMkR6M+KhWUIiKSriUmJrJp0ybmzZvHvHnz+OOPP8ibNy9t27alXbt21K5dGw8PD7Nj3ldqnLzU+c+Tl1LrkqzVamXt2rWMGTOGJUuWkCNHDl5++WX69OljWO9Rq9VWUI44bchwj+SdgvBpEdfb1f1vKihFRET+lJSURFhYGMHBwcybN49Tp06RK1cu2rRpQ2BgIPXq1fvHjmFnsPAS9DyUemfDTykJrR14CuaNGzeYOXMmY8eOZf/+/fj5+TFgwACee+45MmXKZPh8ViuMPA1DTxhfjN9L8jwjisAQF1+ZTKaCUkRE5C6sVis7duwgODiY4OBgjh07Rvbs2WnVqhWBgYE0bNjwoe/bMzafbWXtXRMKoeFFYEhBY1fVTp8+zTfffMPkyZO5evUqrVq1on///tSpUydVNk4tioQev6deYR5UyrXvmfw3FZQiIiIPYLVa2bt3753i8vfff8fHx4cWLVoQGBhI48aNHbJ6du88thW1kS5+qdZqtbJx40bGjh3LggULyJIlCz179qRv376mnHqUGrcOdPnz1oGczrXQbTcVlCIiIg/pwIEDd4rLffv24e3tTdOmTQkMDKRp06ZkyZLFofO7+maSW7du8fPPPzN27Fh27dpFyZIl6d+/P926dXP4311KLIqE90/APgM2NyV/vzNsbnIkFZQiIiJ2OHz4MPPmzSM4OJidO3fi5eVF48aNCQwMpHnz5mTLZuyhzK7c7ubcuXNMnDiRSZMmcenSJZo2bUr//v1p2LCh07VsslohLAomnIOfI2xFoacF4h+i/ZKnBTr5Qt/8UNXH9Tfe3I8KShEREYMcP36c+fPnExwcTFhYGBkyZKBRo0a0a9eOli1bkjNnTrvGT27IfSUBnOHJO6UNucPCwhg7dixz5szBy8uLF198kX79+rnMeeuRcbD2GmyPhm3Rtvf3ahBfxcdWPFb2gbrZIXeG1E5rDhWUIiIiDnDmzJk7xeWmTZtwd3enfv36tGvXjtatW5Mnz8NvlXalIwPj4uIIDg5m7NixhIWF8eSTT9KvXz+6d+9u+Kptaks+wvJmEtxOgoxukMnt7kdYphcqKEVERBzs3LlzLFiwgHnz5rF+/XoA6tSpQ7t27WjTpk2KjgtcFAmt9zs66aNb5Ge7PzAiIoJJkyYxceJEzp8/T4MGDejfvz9NmzZ1yWbxkjIqKEVERFJRREQECxcuZN68eaxevZqkpCRq1qxJu3btaNu27V2bdlutUG47HIh1jrOn/80NeNLtJjWmvsrPs2bh7u5Ot27d6NevH2XKlDE7nqQCFZQiIiImuXz5MosXL2bevHmsXLmS+Ph4qlWrRmBgIO3ataNw4cIAhF6HGrvMzZoSef/XmjeaPEOPHj3svl9UXIsKShERESdw7do1li5dSnBwMMuXL+f27dtUrlyZwMBAQuv2YdmtrHa1r3E0N2sSnX1hRhnn2q0tqUMFpYiIiJOJjo5m2bJlBAcH88vGMG7+eAw8DOiEffYITH0f9m2E6CvgWxDqd4GOb4JXZruH97DA+erpZ2ez/EUFpYiIiBP78cxtuh0z4IjHiDPQoxx4Z4OWr4BPTjgQCsunQY2W8Oki++cA5pSG9r6GDCUuxMPsACIiInJv++My2n1aCwArf4SYazB2IxT5c6NMi5chKQlW/gDRV8Enh11TeFhgR7QKyvRINzqIiIg4sbAoA4pJgBtRtvc58/7z8VyPgZsbeNh/nTrBCluj7R5GXJAKShERESdltcLOGIMGq1DH9v7zHnB0t+0S+JrZsHgitO0PmbwNmWZ7tC23pC+6h1JERMRJRcRB3s0GDvjjJzBzONy++ddjz78LPT4xcBK4WAN8tTEnXdE9lCIiIk7qhtFnLOYrDOVqQa12kDUXbPnFVmDmzAdtXjNsmpvO2H1dHEoFpYiIiJOKM/Ia4pqf4cuX4cfDkOcJ22O12oI1Cb57G+p1hmy5DJnqtgrKdEf3UIqIiDipDBYDB1v0DRSr+FcxmaxGS7h1A44adxRPRlUX6Y7+l4uIiDipzO4GDnb1IiTd5Rp6QrztfWKCYVNlUnWR7uh/uYiIiJPK4wk+RhWVT5SwrUKeOfzPx9fMsrUNerKcIdP4uNtyS/qieyhFRESclMUClbLA+usGDNbxLQj7FQY8C61f+3NTzlLbY816Qu7HDZgEqvjYckv6ohVKERERJ+af1XYCjd3K14Lxm6FEZdv9lBMGwrlj0ONTGDTRgAlsOav6GDKUuBitUIqIiDixyj4GnZQD8FRVGLnMoMH+K8Fqyyvpj1YoRUREnFi97AatUKYCDwvUzW52CjGDCkoREREnljsDdMzj/EWlhwU6+drySvqjglJERMTJ9c1v4GVvB0mwQl9j9vWIC1JBKSIi4uSqZYWy3s77pO0GlPO2bSCS9MlZfzZFRETkTxYLfFIEnPVEwyRgWBG1C0rPVFCKiIi4gJa5obMvGHl4jhHcgS6+tnySflmsVquT35UhIiIiAJfjoWQYXE1wjtVKNyCHBxzyh1w6HSdd0wqliIiIi8jlCVNKOkcxCbYcQaVUTIoKShEREZfSOg98WsTsFDbDi0ArXeoWVFCKiIi4nHcK2t7MzjDE5AziPHQPpYiIiAuyWmHkaRh6wrY6lBqXwZPnGVEEhhRKhQnFZaigFBERcWGLIqHH73AtARIdOI87kN3Dds+kLnPLv6mgFBERcXGX46HfEZgVYfxqZfJ4XXxhXHHIqQ04chcqKEVERNKIRZHw/gnYF2s7W9ue4xqTv7+st62puvpMyv2ooBQREUlDrFYIi4IJ5+DnCFtR6GmB+BQ82ycXkZ4W6ORrO0O8qo9OwJEHU0EpIiKSRkXGwdprsD0atkXb3kff5UZLH3eo4mMrHiv7QN3skDtDaqcVV6aCUkREJJ2wWuFSPNxMgttJkNENMrlBHk+tQop9VFCKiIiIiF3U2FxERERE7KKCUkRERETsooJSREREROyiglJERERE7KKCUkRERETsooJSREREROyiglJERERE7KKCUkRERETsooJSREREROyiglJERERE7KKCUkRERETsooJSREREROyiglJERERE7KKCUkRERETsooJSREREROyiglJERERE7KKCUkRERETsooJSREREROyiglJERERE7KKCUkRERETsooJSREREROyiglJERERE7KKCUkRERETsooJSREREROyiglJERERE7KKCUkRERETsooJSREREROzyf21B/tS0Ytr1AAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import networkx as nx\n", + "\n", + "seed = 100\n", + "graph = nx.random_regular_graph(3, 10, seed=seed)\n", + "nx.draw(\n", + " graph,\n", + " with_labels=True,\n", + " node_size=1000,\n", + " node_color=\"deepskyblue\",\n", + " pos=nx.spring_layout(graph, seed=seed),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This graph has 10 nodes and 15 edges, and it can be encoded in 10 qubits." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "10\n" + ] + } + ], + "source": [ + "num_qubits = len(graph.nodes)\n", + "print(num_qubits)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The following code allows you to easily construct the cost hamiltonian from a graph. You can find this utility function, along with other best practices for combinatorial optimization problems, in the [`qopt-best-practice`](https://github.com/qiskit-community/qopt-best-practices) repository." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[('IIIIIIIIZZ', 1.0), ('IIIIIIZIIZ', 1.0), ('IIIIIIIZIZ', 1.0), ('IIIIZIIIZI', 1.0), ('IIZIIIIIZI', 1.0), ('IIZIIIIZII', 1.0), ('IIIIIIZZII', 1.0), ('ZIZIIIIIII', 1.0), ('IIIIZZIIII', 1.0), ('IIIIZIZIII', 1.0), ('IZIZIIIIII', 1.0), ('IIIZIZIIII', 1.0), ('ZIIZIIIIII', 1.0), ('ZZIIIIIIII', 1.0), ('IZIIIZIIII', 1.0)]\n" + ] + } + ], + "source": [ + "def build_max_cut_paulis(graph: nx.Graph) -> list[tuple[str, float]]:\n", + " \"\"\"Convert the graph to Pauli list.\n", + "\n", + " This function does the inverse of `build_max_cut_graph`\n", + " \"\"\"\n", + " pauli_list = []\n", + " for edge in graph.edges():\n", + " paulis = [\"I\"] * len(graph)\n", + " paulis[edge[0]], paulis[edge[1]] = \"Z\", \"Z\"\n", + "\n", + " weight = graph.get_edge_data(edge[0], edge[1]).get(\"weight\", 1.0)\n", + "\n", + " pauli_list.append((\"\".join(paulis)[::-1], weight))\n", + "\n", + " return pauli_list\n", + "\n", + "\n", + "max_cut_paulis = build_max_cut_paulis(graph)\n", + "print(max_cut_paulis)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 2: Building a quantum circuit from the problem and optimizing the quantum circuit for quantum execution.\n", + "\n", + "### 2.1 Building a quantum circuit from the problem for the QAOA\n", + "The QAOA is a hybrid iterative method for solving combinatorial optimization problems. Please see this [tutorial](https://learning.quantum.ibm.com/tutorial/quantum-approximate-optimization-algorithm) for a more detailed explanation of the QAOA.\n", + "\n", + "The QAOA ansatz is composed of a series of alternating layers of cost hamiltonian unitary and mixer unitary blocks. Typically, a layer of rx gates is employed for the mixer unitary blocks.\n", + "Once the cost hamiltonian is constructed, the ansatz for the QAOA algorithm can be easily built by using the `QAOAAnsatz` circuit from the Qiskit circuit library." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from qiskit.circuit.library import QAOAAnsatz\n", + "from qiskit.quantum_info import SparsePauliOp\n", + "\n", + "cost_operator = SparsePauliOp.from_list(max_cut_paulis)\n", + "ansatz = QAOAAnsatz(\n", + " cost_operator,\n", + " reps=2,\n", + ").decompose()\n", + "ansatz.decompose(reps=2).draw(output=\"mpl\", fold=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 2.2 Optimizing the quantum circuit for quantum execution using the SWAP strategy and the SAT mapping\n", + "SWAP gate insertion is the technique of choice for most quantum circuits to run on quantum hardware with limited qubit connectivity. The first couple of steps of the workflow depend on the choice of qubit configuration we want, which will determine the kind of SWAP strategy that will be used, as well as the evaluation criteria for the backend to obtain the best subset of qubits.\n", + "\n", + "In this example, we choose a SWAP insertion strategy for blocks of commuting two-qubit gates which applies layers of SWAP gates simultaneously executable on the coupling map. This strategy is presented in [Weidenfeller et al.](https://arxiv.org/abs/2202.03459) and exposed as a standardized Qiskit transpiler pass, where we can choose different qubit configurations, in this case, a line." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(range(num_qubits))" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "from qiskit.transpiler.passes.routing.commuting_2q_gate_routing import SwapStrategy\n", + "\n", + "swap_strategy = SwapStrategy.from_line(list(range(num_qubits)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Remap the graph using a SAT mapper\n", + "\n", + "Even when a circuit consists of commuting gates (this is the case for the QAOA circuit, but also for trotterized simulations of Ising Hamiltonians), finding a good initial mapping is a challenging task. The SAT-based approach presented in [Matsuo et al.](https://arxiv.org/abs/2212.05666) enables the discovery of effective initial mappings for circuits with commuting gates, resulting in a significant reduction in the number of required SWAP layers. This approach has been demonstrated to scale to up to *500 qubits*, as illustrated in the paper.\n", + "\n", + "The following code demonstrates how to use the `SATMapper` from Matsuo et al. to remap the graph. This process allows the problem to be mapped to a more optimal initial state for a specified SWAP strategy, resulting in a significant reduction in the number of SWAP layers required to execute the circuit. The `SATMapper` is also available in the [`qopt-best-practice`](https://github.com/qiskit-community/qopt-best-practices) repository." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\"A class to solve the SWAP gate insertion initial mapping problem\n", + "using the SAT approach from https://arxiv.org/abs/2212.05666.\n", + "\"\"\"\n", + "\n", + "from __future__ import annotations\n", + "\n", + "from dataclasses import dataclass\n", + "from itertools import combinations\n", + "from threading import Timer\n", + "\n", + "import numpy as np\n", + "\n", + "from pysat.formula import CNF, IDPool\n", + "from pysat.solvers import Solver\n", + "\n", + "\n", + "@dataclass\n", + "class SATResult:\n", + " \"\"\"A data class to hold the result of a SAT solver.\"\"\"\n", + "\n", + " satisfiable: bool # Satisfiable is True if the SAT model could be solved in a given time.\n", + " solution: dict # The solution to the SAT problem if it is satisfiable.\n", + " mapping: list # The mapping of nodes in the pattern graph to nodes in the target graph.\n", + " elapsed_time: float # The time it took to solve the SAT model.\n", + "\n", + "\n", + "class SATMapper:\n", + " r\"\"\"A class to introduce a SAT-approach to solve\n", + " the initial mapping problem in SWAP gate insertion for commuting gates.\n", + "\n", + " When this pass is run on a DAG it will look for the first instance of\n", + " :class:`.Commuting2qBlock` and use the program graph :math:`P` of this block of gates to\n", + " find a layout for a given swap strategy. This layout is found with a\n", + " binary search over the layers :math:`l` of the swap strategy. At each considered layer\n", + " a subgraph isomorphism problem formulated as a SAT is solved by a SAT solver. Each instance\n", + " is whether it is possible to embed the program graph :math:`P` into the effective\n", + " connectivity graph :math:`C_l` that is achieved by applying :math:`l` layers of the\n", + " swap strategy to the coupling map :math:`C_0` of the backend. Since solving SAT problems\n", + " can be hard, a ``time_out`` fixes the maximum time allotted to the SAT solver for each\n", + " instance. If this time is exceeded the considered problem is deemed unsatisfiable and\n", + " the binary search proceeds to the next number of swap layers :math:``l``.\n", + " \"\"\"\n", + "\n", + " def __init__(self, timeout: int = 60):\n", + " \"\"\"Initialize the SATMapping.\n", + "\n", + " Args:\n", + " timeout: The allowed time in seconds for each iteration of the SAT solver. This\n", + " variable defaults to 60 seconds.\n", + " \"\"\"\n", + " self.timeout = timeout\n", + "\n", + " def find_initial_mappings(\n", + " self,\n", + " program_graph: nx.Graph,\n", + " swap_strategy: SwapStrategy,\n", + " min_layers: int | None = None,\n", + " max_layers: int | None = None,\n", + " ) -> dict[int, SATResult]:\n", + " r\"\"\"Find an initial mapping for a given swap strategy. Perform a binary search\n", + " over the number of swap layers, and for each number of swap layers solve a\n", + " subgraph isomorphism problem formulated as a SAT problem.\n", + "\n", + " Args:\n", + " program_graph (nx.Graph): The program graph with commuting gates, where\n", + " each edge represents a two-qubit gate.\n", + " swap_strategy (SwapStrategy): The swap strategy to use to find the initial mapping.\n", + " min_layers (int): The minimum number of swap layers to consider. Defaults to\n", + " the maximum degree of the program graph - 2.\n", + " max_layers (int): The maximum number of swap layers to consider. Defaults to\n", + " the number of qubits in the swap strategy - 2.\n", + "\n", + " Returns:\n", + " dict[int, SATResult]: A dictionary containing the results of the SAT solver for\n", + " each number of swap layers.\n", + " \"\"\"\n", + " # pylint: disable=too-many-locals\n", + " num_nodes_g1 = len(program_graph.nodes)\n", + " num_nodes_g2 = swap_strategy.distance_matrix.shape[0]\n", + " if num_nodes_g1 > num_nodes_g2:\n", + " return SATResult(False, [], [], 0)\n", + " if min_layers is None:\n", + " # use the maximum degree of the program graph - 2 as the lower bound.\n", + " min_layers = max((d for _, d in program_graph.degree)) - 2\n", + " if max_layers is None:\n", + " max_layers = num_nodes_g2 - 1\n", + "\n", + " variable_pool = IDPool(start_from=1)\n", + " variables = np.array(\n", + " [\n", + " [variable_pool.id(f\"v_{i}_{j}\") for j in range(num_nodes_g2)]\n", + " for i in range(num_nodes_g1)\n", + " ],\n", + " dtype=int,\n", + " )\n", + " vid2mapping = {v: idx for idx, v in np.ndenumerate(variables)}\n", + " binary_search_results = {}\n", + "\n", + " def interrupt(solver):\n", + " # This function is called to interrupt the solver when the timeout is reached.\n", + " solver.interrupt()\n", + "\n", + " # Make a cnf for the one-to-one mapping constraint\n", + " cnf1 = []\n", + " for i in range(num_nodes_g1):\n", + " clause = variables[i, :].tolist()\n", + " cnf1.append(clause)\n", + " for k, m in combinations(clause, 2):\n", + " cnf1.append([-1 * k, -1 * m])\n", + " for j in range(num_nodes_g2):\n", + " clause = variables[:, j].tolist()\n", + " for k, m in combinations(clause, 2):\n", + " cnf1.append([-1 * k, -1 * m])\n", + "\n", + " # Perform a binary search over the number of swap layers to find the minimum\n", + " # number of swap layers that satisfies the subgraph isomorphism problem.\n", + " while min_layers < max_layers:\n", + " num_layers = (min_layers + max_layers) // 2\n", + "\n", + " # Create the connectivity matrix. Note that if the swap strategy cannot reach\n", + " # full connectivity then its distance matrix will have entries with -1. These\n", + " # entries must be treated as False.\n", + " d_matrix = swap_strategy.distance_matrix\n", + " connectivity_matrix = ((-1 < d_matrix) & (d_matrix <= num_layers)).astype(int)\n", + " # Make a cnf for the adjacency constraint\n", + " cnf2 = []\n", + " for e_0, e_1 in program_graph.edges:\n", + " clause_matrix = np.multiply(connectivity_matrix, variables[e_1, :])\n", + " clause = np.concatenate(\n", + " (\n", + " [[-variables[e_0, i]] for i in range(num_nodes_g2)],\n", + " clause_matrix,\n", + " ),\n", + " axis=1,\n", + " )\n", + " # Remove 0s from each clause\n", + " cnf2.extend([c[c != 0].tolist() for c in clause])\n", + "\n", + " cnf = CNF(from_clauses=cnf1 + cnf2)\n", + "\n", + " with Solver(bootstrap_with=cnf, use_timer=True) as solver:\n", + " # Solve the SAT problem with a timeout.\n", + " # Timer is used to interrupt the solver when the timeout is reached.\n", + " timer = Timer(self.timeout, interrupt, [solver])\n", + " timer.start()\n", + " status = solver.solve_limited(expect_interrupt=True)\n", + " timer.cancel()\n", + " # Get the solution and the elapsed time.\n", + " sol = solver.get_model()\n", + " e_time = solver.time()\n", + "\n", + " if status:\n", + " # If the SAT problem is satisfiable, convert the solution to a mapping.\n", + " mapping = [vid2mapping[idx] for idx in sol if idx > 0]\n", + " binary_search_results[num_layers] = SATResult(status, sol, mapping, e_time)\n", + " max_layers = num_layers\n", + " else:\n", + " # If the SAT problem is unsatisfiable, return the last satisfiable solution.\n", + " binary_search_results[num_layers] = SATResult(status, sol, [], e_time)\n", + " min_layers = num_layers + 1\n", + "\n", + " return binary_search_results\n", + "\n", + " def remap_graph_with_sat(\n", + " self, graph: nx.Graph, swap_strategy\n", + " ) -> tuple[int, dict, list] | tuple[None, None, None]:\n", + " \"\"\"Applies the SAT mapping.\n", + "\n", + " Args:\n", + " graph (nx.Graph): The graph to remap.\n", + " swap_strategy (SwapStrategy): The swap strategy to use to find the initial mapping.\n", + "\n", + " Returns:\n", + " tuple: A tuple containing the remapped graph, the edge map, and the number of layers of\n", + " the swap strategy that was used to find the initial mapping. If no solution is found\n", + " then the tuple contains None for each element.\n", + " Note the returned edge map `{k: v}` means that node `k` in the original\n", + " graph gets mapped to node `v` in the Pauli strings.\n", + " \"\"\"\n", + " num_nodes = len(graph.nodes)\n", + " results = self.find_initial_mappings(graph, swap_strategy, 0, num_nodes - 1)\n", + " solutions = [k for k, v in results.items() if v.satisfiable]\n", + " if len(solutions):\n", + " min_k = min(solutions)\n", + " edge_map = dict(results[min_k].mapping)\n", + " remapped_graph = nx.relabel_nodes(graph, edge_map)\n", + " return remapped_graph, edge_map, min_k\n", + " else:\n", + " return None, None, None" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Map from old to new nodes: {0: 9, 1: 4, 2: 6, 3: 8, 4: 2, 5: 7, 6: 3, 7: 5, 8: 1, 9: 0}\n", + "Min SWAP layers: 2\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sm = SATMapper()\n", + "remapped_g, sat_map, min_swap_layers = sm.remap_graph_with_sat(\n", + " graph=graph, swap_strategy=swap_strategy\n", + ")\n", + "\n", + "print(\"Map from old to new nodes: \", sat_map)\n", + "print(\"Min SWAP layers:\", min_swap_layers)\n", + "nx.draw(\n", + " remapped_g,\n", + " with_labels=True,\n", + " node_size=1000,\n", + " node_color=\"lime\",\n", + " pos=nx.spring_layout(remapped_g, seed=seed),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Construct a cost Hamiltonian from the remapped graph\n", + "As explained in Step 1, the repository includes utils to map from a graph to a pauli list for the Max-Cut setting." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "SparsePauliOp(['ZIIIIZIIII', 'ZZIIIIIIII', 'ZIIZIIIIII', 'IIZIIZIIII', 'IIIIZZIIII', 'IIIZZIIIII', 'IZIZIIIIII', 'IIIIZIIIIZ', 'IIZIIIIZII', 'IZZIIIIIII', 'IIIIIIZIZI', 'IIIIIIZZII', 'IIIIIIZIIZ', 'IIIIIIIIZZ', 'IIIIIIIZZI'],\n", + " coeffs=[1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,\n", + " 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j])\n" + ] + } + ], + "source": [ + "remapped_max_cut_paulis = build_max_cut_paulis(remapped_g)\n", + "# define a qiskit SparsePauliOp from the list of paulis\n", + "remapped_cost_operator = SparsePauliOp.from_list(remapped_max_cut_paulis)\n", + "print(remapped_cost_operator)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Build a QAOA circuit with the SWAP strategy and the SAT mapping\n", + "We only want to apply the SWAP strategies to the cost operator layer, so we will start by creating the isolated block that we will later transform and append to the final QAOA circuit.\n", + "\n", + "For this means, we can use the `QAOAAnsatz` class from Qiskit. We will input an empty circuit to the `initial_state` and `mixer_operator` fields to make sure we are buiding an isolated cost operator layer.\n", + "We also define the edge_coloring map so that RZZGates are positioned next to SWAP gates. This strategic placement allows us to exploit CX cancellations, optimizing the circuit for better performance.\n", + "This process is executed within the `create_qaoa_swap_circuit` function. For a detailed explanation of how `create_qaoa_swap_circuit` works, please refer to the corresponding guide in the qopt-best-practice repository: [How to build a QAOA ansatz with SWAP strategies](https://github.com/qiskit-community/qopt-best-practices/blob/main/how_tos/how_to_build_qaoa_swap_circuit.ipynb) works." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "from qiskit.circuit import QuantumCircuit\n", + "from qiskit.transpiler import PassManager\n", + "from qiskit.transpiler.passes.routing.commuting_2q_gate_routing import (\n", + " FindCommutingPauliEvolutions,\n", + " Commuting2qGateRouter,\n", + ")\n", + "from qiskit.circuit.library import QAOAAnsatz\n", + "from qiskit.circuit import ParameterVector\n", + "\n", + "\n", + "def make_meas_map(circuit: QuantumCircuit) -> dict:\n", + " \"\"\"Return a mapping from qubit index (the key) to classical bit (the value).\n", + "\n", + " This allows us to account for the swapping order introduced by the SwapStrategy.\n", + " \"\"\"\n", + " creg = circuit.cregs[0]\n", + " qreg = circuit.qregs[0]\n", + "\n", + " meas_map = {}\n", + " for inst in circuit.data:\n", + " if inst.operation.name == \"measure\":\n", + " meas_map[qreg.index(inst.qubits[0])] = creg.index(inst.clbits[0])\n", + "\n", + " return meas_map\n", + "\n", + "\n", + "def apply_swap_strategy(\n", + " circuit: QuantumCircuit,\n", + " swap_strategy: SwapStrategy,\n", + " edge_coloring: dict[tuple[int, int], int] | None = None,\n", + ") -> QuantumCircuit:\n", + " \"\"\"Transpile with a SWAP strategy.\n", + "\n", + " Returns:\n", + " A quantum circuit transpiled with the given swap strategy.\n", + " \"\"\"\n", + "\n", + " pm_pre = PassManager(\n", + " [\n", + " FindCommutingPauliEvolutions(),\n", + " Commuting2qGateRouter(\n", + " swap_strategy,\n", + " edge_coloring,\n", + " ),\n", + " ]\n", + " )\n", + " return pm_pre.run(circuit)\n", + "\n", + "\n", + "def apply_qaoa_layers( # pylint: disable=too-many-arguments,too-many-locals\n", + " cost_layer: QuantumCircuit,\n", + " meas_map: dict,\n", + " num_layers: int,\n", + " gamma: list[float] | ParameterVector = None,\n", + " beta: list[float] | ParameterVector = None,\n", + " initial_state: QuantumCircuit = None,\n", + " mixer: QuantumCircuit = None,\n", + "):\n", + " \"\"\"Applies QAOA layers to construct circuit.\n", + "\n", + " First, the initial state is applied. If `initial_state` is None we begin in the\n", + " initial superposition state. Next, we alternate between layers of the cot operator\n", + " and the mixer. The cost operator is alternatively applied in order and in reverse\n", + " instruction order. This allows us to apply the swap-strategy on odd `p` layers\n", + " and undo the swap strategy on even `p` layers.\n", + " \"\"\"\n", + "\n", + " num_qubits = cost_layer.num_qubits\n", + " new_circuit = QuantumCircuit(num_qubits, num_qubits)\n", + "\n", + " if initial_state is not None:\n", + " new_circuit.append(initial_state, range(num_qubits))\n", + " else:\n", + " # all h state by default\n", + " new_circuit.h(range(num_qubits))\n", + "\n", + " if gamma is None or beta is None:\n", + " gamma = ParameterVector(\"γ\", num_layers)\n", + " if mixer is None or mixer.num_parameters == 0:\n", + " beta = ParameterVector(\"β\", num_layers)\n", + " else:\n", + " beta = ParameterVector(\"β\", num_layers * mixer.num_parameters)\n", + "\n", + " if mixer is not None:\n", + " mixer_layer = mixer\n", + " else:\n", + " mixer_layer = QuantumCircuit(num_qubits)\n", + " mixer_layer.rx(-2 * beta[0], range(num_qubits))\n", + "\n", + " for layer in range(num_layers):\n", + " bind_dict = {cost_layer.parameters[0]: gamma[layer]}\n", + " cost_layer_ = cost_layer.assign_parameters(bind_dict)\n", + " bind_dict = {\n", + " mixer_layer.parameters[i]: beta[layer + i] for i in range(mixer_layer.num_parameters)\n", + " }\n", + " layer_mixer = mixer_layer.assign_parameters(bind_dict)\n", + "\n", + " if layer % 2 == 0:\n", + " new_circuit.append(cost_layer_, range(num_qubits))\n", + " else:\n", + " new_circuit.append(cost_layer_.reverse_ops(), range(num_qubits))\n", + "\n", + " new_circuit.append(layer_mixer, range(num_qubits))\n", + "\n", + " for qidx, cidx in meas_map.items():\n", + " new_circuit.measure(qidx, cidx)\n", + "\n", + " return new_circuit\n", + "\n", + "\n", + "def create_qaoa_swap_circuit( # pylint: disable=too-many-arguments\n", + " cost_operator: SparsePauliOp,\n", + " swap_strategy: SwapStrategy,\n", + " edge_coloring: dict = None,\n", + " theta: list[float] = None,\n", + " qaoa_layers: int = 1,\n", + " initial_state: QuantumCircuit = None,\n", + " mixer: QuantumCircuit = None,\n", + "):\n", + " \"\"\"Create the circuit for QAOA.\n", + "\n", + " Notes: This circuit construction for QAOA works for quadratic terms in `Z` and will be\n", + " extended to first-order terms in `Z`. Higher-orders are not supported.\n", + "\n", + " Args:\n", + " cost_operator: the cost operator.\n", + " swap_strategy: selected swap strategy\n", + " edge_coloring: A coloring of edges that should correspond to the coupling\n", + " map of the hardware. It defines the order in which we apply the Rzz\n", + " gates. This allows us to choose an ordering such that `Rzz` gates will\n", + " immediately precede SWAP gates to leverage CNOT cancellation.\n", + " theta: The QAOA angles.\n", + " qaoa_layers: The number of layers of the cost-operator and the mixer operator.\n", + " initial_state: The initial state on which we apply layers of cost-operator\n", + " and mixer.\n", + " mixer: The QAOA mixer. It will be applied as is onto the QAOA circuit. Therefore,\n", + " its output must have the same ordering of qubits as its input.\n", + " \"\"\"\n", + "\n", + " num_qubits = cost_operator.num_qubits\n", + "\n", + " if theta is not None:\n", + " gamma = theta[: len(theta) // 2]\n", + " beta = theta[len(theta) // 2 :]\n", + " qaoa_layers = len(theta) // 2\n", + " else:\n", + " gamma = beta = None\n", + "\n", + " # First, create the ansatz of 1 layer of QAOA without mixer\n", + " cost_layer = QAOAAnsatz(\n", + " cost_operator,\n", + " reps=1,\n", + " initial_state=QuantumCircuit(num_qubits),\n", + " mixer_operator=QuantumCircuit(num_qubits),\n", + " ).decompose()\n", + "\n", + " # This will allow us to recover the permutation of the measurements that the swap introduce.\n", + " cost_layer.measure_all()\n", + "\n", + " # Now, apply the swap strategy for commuting pauli evolution gates\n", + " cost_layer = apply_swap_strategy(cost_layer, swap_strategy, edge_coloring)\n", + "\n", + " # Compute the measurement map (qubit to classical bit).\n", + " # we will apply this for qaoa_layers % 2 == 1.\n", + " if qaoa_layers % 2 == 1:\n", + " meas_map = make_meas_map(cost_layer)\n", + " else:\n", + " meas_map = {idx: idx for idx in range(num_qubits)}\n", + "\n", + " cost_layer.remove_final_measurements()\n", + "\n", + " # Finally, introduce the mixer circuit and add measurements following measurement map\n", + " circuit = apply_qaoa_layers(\n", + " cost_layer, meas_map, qaoa_layers, gamma, beta, initial_state, mixer\n", + " )\n", + "\n", + " return circuit" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# We define the edge_coloring map so that RZZGates are positioned next to SWAP gates to exploit CX cancellations\n", + "edge_coloring = {(idx, idx + 1): (idx + 1) % 2 for idx in range(remapped_cost_operator.num_qubits)}\n", + "\n", + "qaoa_circ = create_qaoa_swap_circuit(\n", + " remapped_cost_operator, swap_strategy, edge_coloring, qaoa_layers=2\n", + ")\n", + "qaoa_circ.draw(output=\"mpl\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 2.3 Transpile the circuit\n", + "#### Choose backend\n", + "This notebook currently runs on a simulated fake backend, using the BackendSampler from qiskit. To run on real devices, and make use of the error suppression, mitigation and additional capabilities of Qiskit Runtime, you must uncomment the cell that uses the runtime Sampler." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "# SIMULATED FAKE BACKEND --> BackendSampler\n", + "from qiskit.providers.fake_provider.backends_v1 import Fake20QV1\n", + "from qiskit.primitives import BackendSampler\n", + "\n", + "backend = Fake20QV1()\n", + "sampler = BackendSampler(backend=backend, skip_transpilation=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/matsuo/envs/qeet/lib/python3.11/site-packages/numpy/linalg/linalg.py:2180: RuntimeWarning: divide by zero encountered in det\n", + " r = _umath_linalg.det(a, signature=signature)\n", + "/Users/matsuo/envs/qeet/lib/python3.11/site-packages/numpy/linalg/linalg.py:2180: RuntimeWarning: invalid value encountered in det\n", + " r = _umath_linalg.det(a, signature=signature)\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from qiskit.transpiler.preset_passmanagers import generate_preset_pass_manager\n", + "\n", + "\n", + "basis_gates = [\"rz\", \"sx\", \"x\", \"cx\"]\n", + "\n", + "pass_manager = generate_preset_pass_manager(\n", + " backend=backend, optimization_level=3, basis_gates=basis_gates\n", + ")\n", + "\n", + "transpiled_qaoa_circ = pass_manager.run(qaoa_circ)\n", + "transpiled_qaoa_circ.draw(output=\"mpl\", idle_wires=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step3: Executing the optimized circuit using Qiskit Runtime primitives.\n", + "### 3.1 Define a cost function\n", + "The QAOA cost function using the Sampler requires the manual computation of the expectation values from the measurement results. For this means, we use the `evaluate_sparse_pauli` helper function." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "_PARITY = np.array([-1 if bin(i).count(\"1\") % 2 else 1 for i in range(256)], dtype=np.complex128)\n", + "\n", + "\n", + "def evaluate_sparse_pauli(state: int, observable: SparsePauliOp) -> complex:\n", + " \"\"\"Utility for the evaluation of the expectation value of a measured state.\"\"\"\n", + " packed_uint8 = np.packbits(observable.paulis.z, axis=1, bitorder=\"little\")\n", + " state_bytes = np.frombuffer(state.to_bytes(packed_uint8.shape[1], \"little\"), dtype=np.uint8)\n", + " reduced = np.bitwise_xor.reduce(packed_uint8 & state_bytes, axis=1)\n", + " return np.sum(observable.coeffs * _PARITY[reduced])" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "def cost_func_sampler(params, ansatz, hamiltonian, sampler):\n", + " job = sampler.run(ansatz, params)\n", + " sampler_result = job.result()\n", + " sampled = sampler_result.quasi_dists[0]\n", + " # a dictionary containing: {state: (measurement probability, value)}\n", + " evaluated = {\n", + " state: (probability, evaluate_sparse_pauli(state, hamiltonian))\n", + " for state, probability in sampled.items()\n", + " }\n", + "\n", + " result = sum(probability * value for probability, value in evaluated.values())\n", + "\n", + " return result" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 3.2 Define Initial Point\n", + "In this example, we use the TQA initialization technique [(Sack et al. 2021)](https://arxiv.org/abs/2101.05742) to define the initial point of the parameter optimization:" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.8125 0.4375 0.1875 0.5625]\n" + ] + } + ], + "source": [ + "# TQA initialization parameters\n", + "dt = 0.75\n", + "p = 2 # 2 qaoa layers\n", + "grid = np.arange(1, p + 1) - 0.5\n", + "init_params = np.concatenate((1 - grid * dt / p, grid * dt / p))\n", + "print(init_params)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 3.3 Execute the QAOA circuit using Qiskit Runtime Primitives and iterate over the optimization routine\n", + "We can plug our sampler-based cost function into the scipy minimizing routine to find our optimal parameters" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/matsuo/envs/qeet/lib/python3.11/site-packages/qiskit/providers/fake_provider/fake_backend.py:558: RuntimeWarning: Aer not found using BasicAer and no noise\n", + " warnings.warn(\"Aer not found using BasicAer and no noise\", RuntimeWarning)\n", + "/Users/matsuo/envs/qeet/lib/python3.11/site-packages/scipy/optimize/_cobyla_py.py:293: ComplexWarning: Casting complex values to real discards the imaginary part\n", + " xopt, info = cobyla.minimize(calcfc, m=m, x=np.copy(x0), rhobeg=rhobeg,\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " message: Optimization terminated successfully.\n", + " success: True\n", + " status: 1\n", + " fun: -6.447265625\n", + " x: [ 1.990e+00 2.408e-01 2.439e-01 4.419e-01]\n", + " nfev: 46\n", + " maxcv: 0.0\n" + ] + } + ], + "source": [ + "from scipy.optimize import minimize\n", + "\n", + "result = minimize(\n", + " cost_func_sampler,\n", + " init_params,\n", + " args=(transpiled_qaoa_circ, remapped_cost_operator, sampler),\n", + " method=\"COBYLA\",\n", + ")\n", + "print(result)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 4: Post-processing the results and returning them in classical format.\n", + "### 4.1 Sample the best result\n", + "We can use the best parameters found by the optimization routine to sample the best result from the QAOA circuit." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "qc = transpiled_qaoa_circ.assign_parameters(result.x)\n", + "samp_dist = sampler.run(qc, shots=int(1e4)).result().quasi_dists[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "# draw histogram\n", + "fig = plt.figure(figsize=(11, 6))\n", + "ax = fig.add_subplot(1, 1, 1)\n", + "plt.bar(samp_dist.keys(), samp_dist.values())\n", + "max_value_bin = max(samp_dist, key=samp_dist.get)\n", + "position = list(samp_dist.keys()).index(max_value_bin)\n", + "ax.get_children()[position].set_color(\"red\")\n", + "plt.ylabel(\"Probability\")\n", + "plt.xlabel(\"Bitstrings\")\n", + "plt.xticks([])\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 4.2 Visualize the solution\n", + "We can visualize the solution using the following function.\n", + "\n", + "Note that the result is for the remapped max-cut problem with Big Endian, so we need to remap it back to the original graph." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0, 0, 0, 0, 0, 1, 1, 0, 0, 1]\n" + ] + } + ], + "source": [ + "def bitfield(n, L):\n", + " # Convert an integer into a bitfield, a list of 0s and 1s\n", + " result = np.binary_repr(n, width=L)\n", + " return [int(digit) for digit in result]\n", + "\n", + "\n", + "def sample_best_result(sample_distribution, num_qubits):\n", + " evaluated = [\n", + " evaluate_sparse_pauli(bitstr, remapped_cost_operator) for bitstr in sample_distribution\n", + " ]\n", + " k = np.argmin(evaluated)\n", + " x = bitfield(k, num_qubits)\n", + " x.reverse()\n", + " return np.asarray(x)\n", + "\n", + "\n", + "best_result = sample_best_result(samp_dist, num_qubits)\n", + "\n", + "# sort nodes in the ascending order\n", + "node_view = list(remapped_g.nodes())\n", + "sorted_best_result = [best_result[node_view.index(node)] for node in range(num_qubits)]\n", + "print(sorted_best_result)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cut_size: 5\n", + "[5, 6, 9] [0, 1, 2, 3, 4, 7, 8]\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "\n", + "# auxiliary function to plot graphs\n", + "def plot_result(G, x):\n", + " colors = [\"salmon\" if i == 0 else \"deepskyblue\" for i in x]\n", + " pos, default_axes = nx.spring_layout(remapped_g, seed=seed), plt.axes(frameon=True)\n", + " nx.draw(remapped_g, with_labels=True, node_size=1000, node_color=colors, pos=pos)\n", + "\n", + "\n", + "plot_result(remapped_g, best_result)\n", + "cut = [node_view[i] for i, var in enumerate(best_result) if var == 1]\n", + "print(f\"cut_size: {nx.cut_size(remapped_g, cut)}\")\n", + "print(sorted(cut), [i for i in range(num_qubits) if i not in cut])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The final solution is not the optimal solution, but it is a good approximation of the optimal solution. \n", + "\n", + "*In the example, we used the most probable result as the final solution. However, in a real-world scenario, we would use the solution with the largest cut values as the final solution instead.*" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In the tutorial, we showcased how to use the QAOA to solve a Max-Cut problem. We also demonstrated how to build and optimize QAOA circuits using the SWAP strategy\n", + ", a specifically designed transpiler pass for QAOA applied to quadratic problems. We hope this tutorial will help you to understand how to use Qiskit Patterns to solve combinatorial optimization problems using the QAOA algorithm." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## References\n", + "1. Weidenfeller, J., Valor, L. C., Gacon, J., Tornow, C., Bello, L., Woerner, S., & Egger, D. J. (2022). Scaling of the quantum approximate optimization algorithm on superconducting qubit based hardware. Quantum, 6, 870.\n", + "2. Matsuo, A., Yamashita, S., & Egger, D. J. (2023). A SAT approach to the initial mapping problem in SWAP gate insertion for commuting gates. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2022EAP1159.\n", + "3. Best practices in quantum optimization. Available online: https://github.com/qiskit-community/qopt-best-practices." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "qopt-bp", + "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": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +}