.

test_layer.ipynb

@@ -0,0 +1,124 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Test of generating alternating single qubit and two qubit layers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import qiskit\n",
+    "from qiskit import QuantumCircuit\n",
+    "import numpy as np\n",
+    "from utils.layers import alternating_sq_2q_layers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\c5517\\python\\lib\\site-packages\\qiskit\\visualization\\circuit\\matplotlib.py:266: FutureWarning: The default matplotlib drawer scheme will be changed to \"iqp\" in a following release. To silence this warning, specify the current default explicitly as style=\"clifford\", or the new default as style=\"iqp\".\n",
+      "  self._style, def_font_ratio = load_style(self._style)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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A3YjLR4CSW8Js26p9058eLVTu5mRuivSL+3H+aire8v8YEV/4o6r6wZ/LLu3H3bLbmP+ZD3p388GUEe9rZZtCzglVdL3vhSDFeS3FGiLFzJpQVTcszKzqrO/4lAsKi3IAAOWVJWhjbtvkbYu1fgD6UUMawmaoESW3xHmjqcZINbemPF3HIDVjJ/7575nwdB2Ly9dOKZYVl9yElaUdot9Oxoqtr+PX/J/Q3bFvs7epL/tWjKS475lZfFTVjfr06DQAXxxYjH0nNqCHY3883bZzk7fd2vetVPFtMpK80Z4hOJqxE6MGvqU0bmlmA3cnLwBA724+yLt1SYh4RCRCDdWN+uxOjcFk3/execElWJrb4PzVozpISLrEZogkTS6XY9uh5Zg84u/YcWSV0jLXLoORU3AeAHDlxjl0aNdViIhEJDKq6ka9ampgZdEOAGBtYYeyirstnJB0jc0QSdo3x9dhSK/xCPAKR07hz6h4WKZY5vmXMfjt5kXMi/NCTY0cPbsMFjApEYmFqrpxq/gaFsb7IrcwEwvjfVFYlIuxg2dh66GPMC/OC1cLzqOfi5+A6akl8JohkrRXhs1V/Pv9N3Yj/tv5WL0jGCumfQdLcxssmPil0vqZOcewN+1TTPBaoOOkRCQWqupGe9tnERVyqM7PrAlNVfqetaR1YTOkBeFx3rj02wnIZMYwNJShQ9uuCHwxAl69A4SOppJUc6sSMjZa5fJeXYdiwzundZSGhCDFeS3FzIB0cz+psbpRH9aS1oXNkJYE+S5DkO9SVFdXYW/ap1i5PRDODn3gYO8sdDSVpJqbSBUpzmspZgakm5vocbxmSMtkMiOMGjgD1fIqXLlxTug4apNqbmp54XHe8F9kirERbTBumQ1C1jyP1IxdQsdSixTntRQzA9LNTS1PCjWEZ4a07GHVA+xPiwMAONq7CJxGfVLNTboh1b/+pTivpZgZkG5u0g2x1xA2Q1qy/fAK7EqNRnllCWQyY8wL2ASnju4AgOu3s7Fi60SsnXMCxkYm2JmyGvcrSxDs95HAqVXnPvDjFzh05mvFugVFV+HWdRgWB24TKi4J7NFf/3H73sWVG+dEU8ieJMV5zRpC+kCsNUTUb5PJ5XJER0eje/fuMDMzQ+/evZGamooePXpg5syZQsdTEvhiBL5ZXozdH9zGgOf8kZGdrFjmYO+MoW6vIvHIShQU5SDlXCICX4wQMO2fVOUeNWA6YkJTEBOagoigRJiZWGLqyBUCpiWhSeWvfynOa9YQ0gdirSGiboamT5+O5cuXIyQkBAcOHMCECRMwadIkXL16FR4eHkLHq5eVRVvMC9iEk798h7TMvYrxCd4LkH5pPyK3TULoS7EwMTIVMGVdDeUGapvSlQlBmD5qJTq069LiWZLPJeLdDcMwbqk1/N6TzsnLank1Nu5fgNc+eAovLbXCh/96FXfLbgsdSyu2H16Bl5fZYswSc3z536V1zlrMivXAw6ra5zvtTFmNLf99v8FxXRLTvFYXa0jzsH6Ik9hriGiboYSEBGzZsgX79u3D/Pnz4ePjg4iICAwaNAhVVVXo27f5z5hqKdYW7fDqsHnYfHAJ5HI5AMBIZgw3p+EoLb+DXl2HCpywfvXlBoCvv/8QXTu4YUivl3WSo415W4wdNAuhL8XqZHvakpi8CmkX9uKTsJNIiKh9+NDHCVMETqUdTTlrIZazGWKZ15pgDWk61g9xEnsNEW0zFBkZiZEjR8LLy0tp3NnZGcbGxnB3r+0o33//fbi4uMDQ0BC7d+8WImq9xg97B0X3CvD9ma8AALmFF3Ah9zj6OPsi6eTnAqdr2JO5f/r1MM5k/Q8zRkfpLEP/Hn54oc8kPGPnpLNtakNS+kZM9HkPz9g5wdLcBjNGR+HU5YO4eec3oaNpjaZnLcRyNkMM81pTrCFNw/ohbmKtIaJshvLz85GZmYmAgLo37srLy0PPnj1halq7Q0aOHImDBw9i+PDhGm3DwMBAra/U1JRGXysmNAVBvkuVxizNrLHnoyL49Q+GXC7H2j1vI2z8erzlvwrfHP8Ed0puNvq6qakpaudsidxF9wrx6TdzsCQoAcZGJo2+nqaZ1ckoFFW/R325S8uLcas4D90d/nz7tqN9N1iYWePKjQxRZm4qTc5aqHM2Q9tzRuh53RpqiLrzReh9LcUaItb6oSqzmGtIY/NFXaJthgCgQ4cOSuPl5eVITU1Veots8ODBcHIS918A356IQ3cHD7g4esDCzArBfsuxYd9coWM1auuh5SiruIvVO4IRHueN8DhvxO4OETqWKN2vLAEAWJrbKI23MbPF/Yp7QkRqUeqetRDj2QwpzmvWkNZN3+oHIL4aIsqry+zt7QEAWVlZ8Pf3V4xHRUWhoKBAKxdP19TUqLXe6USgOL952xo3ZLbS90N6vazWe+deXt6oiVMv55O0kftvr6zH315Zr9HPaJJZGxlbiqrfo77cFqZWAICycuWnWZdWFMPCzLpFMj5J08zqiglNqTP26K9/AEpnLRztXfDO+sEY3HMcbCyfqne8rdXTaufW5u/xSEvP6ydJsYZo69hkDan7e4i1fgDSrCHNOTYfJ8ozQ05OTnB3d0dkZCS++uorHD58GKGhodi8eTMAiPaTZKS/2pjbor1tJ2Rf/0kxVvDHVdyvuAenZ9wFTNbyGjprIdWzGUS6ps/1AxBHDRHlmSFDQ0Ps2rULISEhCA0NhZ2dHd58803Mnj0bS5YsUVw8Ta1Ttbwa1dUPFR+nfPCwAgBgbGSq0XvAuubvORM7Uj5Gb2cfWFvY4fOk99DPxU9UH9tuCeqetVD3bAZRc7B+SI8YaogomyEAcHFxQXJystLYlClT4OrqCnNzc4FSkS4cOvM1ondOVXw/ekntf++vF+eIujC87rMIpffvYM7a/nhYXYm+3UdgUeBWoWMR6RXWD2oK0TZD9Tl9+jQ8PT2VxpYtW4Yvv/wSv//+O37++WfMnTsXqamp6Natm0Apqbn8+gfDr3+w0DE0JjOUIWRsNELGRgsdhUhvsX5QU4jymqH6lJaWIisrq87NFpcvX478/HxUVlbijz/+QH5+vqCNUFRiMMLWDURZ+V2cuPgtwj7xxN8+GYRdqTEAau+0GbLmeXx5cGkjr6Rbj+c+ffl/mLt+KMI+8cTmA7U3uMrMOYZpUc8h6eQmgZMSqfb4XM6+fhYzYtwwObKLYrkYj8vGMov1mGws9yPr976DVdsnAxBHbqInSaYZatOmDaqrqxEWFiZ0lEYtCtwGS3MbdHumN2JnH8faOWk4cXEfysrvwsHeGbPGxQodsV6Pcj/v7IPY2cfwSVg6Lv6WhuLS39Gr61BM9FkkdEQitTyayx3tnLEuLB32No6KZWI9LlVlFvMxqSo3ANwpuYnCohzF92LJTfQ4yTRDYpV+cT827l8AuVyOxZ+PxO/FeYpl7dt2gsxQBgMDA8gMjWBgIJ7drSq3kcwYQO2FiG2tOuj0o51EmlI1ly3MrGBuYqm0vhiOS00zi+WY1DQ3AOz5IRYvDxH/H7Gk38Tzf2eJ8nQdgzslN/HPf8+Ep+tYPGXbqc46P/5yAB3tusHCzEqAhPVrLPd36RsxLaoHrC3sRPdASKLHqXMM1kfI47IpmcVwTGqa+979IhSX/Q4H++46SkjUNGyGtGC0ZwiOZuzEqIFv1VlW8MdV7EyJwtsv/VOAZKqpyj3acya+XJiF23fzkX39rADpWqfwOG/4LzLF2Ig2GLfMBiFrnkdqxi6hY0meqrlcHzEcl5pmFssxqUnu//ywFuMGz250PVIP60fLkdSnycRILpdj26HlmDzi79hxZJXSsvsVJVi9IxgLJm6p9/SxkFTlflBVCRMjUxgaGsLMxBImxryVgTYF+S5DkO9SVFdXYW/ap1i5PRDODn3gYO8sdDRJUjWX6yOG41LTzGI5JjXNXViUgy+SFqOyqhzXb/+K1Iyd8Oo9QQdJWy/Wj5bBM0PN9M3xdRjSazwCvMKRU/gzKh6WKZbtTfsUhUU5iN45DeFx3ih47CJCoanK/d9TXyI8zhvvbhiGZ9o5oVP75wRM2nrJZEYYNXAGquVVuHLjnNBxJEvVXL5VfA0L432RW5iJhfG+KCzKFcVxqWlmsRyTmuZ+b9JXWDnjIBZO/Bf6dHuBjZAWsX5oF88MNdMrw+Yq/v3+G7sR/+18rN4RjBXTvsOkFxZj0guLlda/fjsbm5IWYbh7gI6TKlOVe+ygtzF20NtK62fmHMPetE8xwWuBjpO2Xg+rHmB/WhwAwNHeReA00qVqLre3fRZRIYeU1hfDcalpZrEck5rmfqRDuy6KGwiylmgH64d2sRnSssZumOVg74xPwtJ1lEZ9jeXu1XUoNrxzWkdpWrfth1dgV2o0yitLIJMZY17AJjh1rH3EzPXb2VixdSLWzjkBYyMT7ExZjfuVJRjh8Ua948F+Hwn824hPU25aJ/Rx2ZTMYjgmpZpbylg/WgaboUZYtZfmtoXKrcl2hdy3jWnJbIEvRiDIdylK7t9BzK7pyMhOxqgB0wHU/k95qNurSDyyEr793kDKuUTEzkmDiZFpveP6RgrzWps/21xN3bZUMutjDWH9aBlshhrR4wWhEzSNFHJLIWNLsrJoi3kBm/Dmqm5Iy9yLwb3GAQAmeC/AO58Oxo+XDyD0pVjFx6gbGtcnUpwzzNxypJKzJbB+aBcvoCYSkLVFO7w6bB42H1wCuVwOoPYGe25Ow1Fafge9ug5VrNvQOBHpJ9YP7WEzRCSw8cPeQdG9Anx/5isAQG7hBVzIPY4+zr5IOvm5Yr2GxolIf7F+aAffJiPSoZjQlDpjlmbW2PNREYDa+7is3fM2wsavh6O9C95ZPxiDe46DjeVT9Y63tXpax7/Bn6ISg3Ht1iWsmvE/VD4sx4ptr6MGNeho1w3zJ2xGZs4xrNn1Fl7zmg9/NW8sSEQNaw314/G6cT7nKLYfXgEDGGCY+2sI8AoHAMTtexdZ+afh7NAXs8etxfXb2fjoq9fg6ToGU0f+o0Vy8cwQkYh8eyIO3R084OLoAQszKwT7LceGfXMbHBfao4d0Hjm7HSP7T8Oa0FQYGshw5UYGH8hJpGNSqR+qHmb+a/5PKK8sxT9n/YCqqge4fO2UTh6kzDNDRCIybojyowuG9HoZQ3q9XGe9hsZbUvrF/Th/NRVv+X+MiC/8UVX9QLHM8SkXxZPJyytL0MbcVqfZiEic9UNV3Wjf9s9n2z16aPKlvHR4uIwAAPTt7ouLv51Aj2f7t3hOnhkiIrWoekhnj04D8N3JjZi2+i8wkpng6badBUxKRGKh6cPMS8uLYWFqDQCwNLNBaXmxTnKyGSIitTX0kM7dqTGY7Ps+Ni+4BEtzG5y/elSghEQkNpo8zNzSzAb3K+8BAMoq7+nsLDObISJSi8qHdNbUwMqiHQDA2sIOZRV3BUhIRGKjzsPMwwO+UDw02bXzIJz99TAA4Oyvh/CXTp46yclmiIjUouohnWMHz8LWQx9hXpwXrhacRz8XPwGTEpFYaPow8+6OfWFsbIZ3NwyDoaEMz3UaoJOcBjU1NTU62RJRK3E6ESjOFzpFXbaOQL/X61/WEpnjv52PS3npWDHtO1ia29RZnplzDBv2zcUErwXwfn5ig6+jKjdRayPW+gHopoY0Vjfqc/12NlYlTMZw9wDFx+8f0Vb94KfJiKhJ+HBfItKUWB+kzLfJiAQWlRiMsHUDUVZ+F/89tQXhcd4Ij/PG+PfbIvv6OVy/nY2QNc/jy4NLhY5KRCLyeO3Ivn4WM2LcMDmyi2J5WfldLN08BuFx3tjzQywAsJ40gM0QkQg8ugmZX/9gxISmIGrmIbS37YxuHXvr5IZjRCRNj2pHRztnrAtLh72No2LZdyc34oU+QYgJTcHPV3/A3bLbrCcN4Ntkjbh8BCi5Jcy2rdo3/anMQuVuTmZ9oeomZI+czzkKd6fhMDAwECCheElxXkuxhkgxsz5QVTsszKzqrF/wx1UMeM4fAND5aVdcvnYKA54bpbO8UsJmqBElt8R7sZsqUs2tDzxdxyA1Y6fiJmSXr52qs86xn/dgmNurAqQTNynOa2YmbVGndjzu2fY9cP5qKp5t/xzO5xxFp6dddZRUevg2GZEAVN2ErKamBpk5x+DmNFyAZEQkZqpqx5NGDZyBi7lpWLJpFOysOwr6YGexYzNEpGMqb14I4PK1U+ju2BcyQ5kA6YhIrBqrHU8yN7HEosCtiHzrAGpq5HDtPEgHKaWJzRCRjqm6CRkAHM/8D4b2ekWgdEQkVqpqx63ia1gY74vcwkwsjPdFYVEusvLPYP5nPli0cQT8+k2FqbG5gOnFjdcMEenYK8PmKv79/hu7Ef/tfKzeEay4Cdl0/5VK61+/nY1NSYsw3D1Ax0mJSExU1Y72ts8iKuSQ0vod2nVB9NvJSmOsJ/VjM6QF4XHeuPTbCchkxjA0lKFD264IfDECXr3FPdmkmru1aewmZLq44VhrIsV5LcXMgHRztxZivYGhFLEZ0pIg32UI8l2K6uoq7E37FCu3B8LZoQ8c7J2FjqaSVHMTqSLFeS3FzIB0cxM9jtcMaZlMZoRRA2egWl6FKzfOCR1HbVLNTaSKFOe1FDMD0s1NBLAZ0rqHVQ+wPy0OAOBo7yJwGvVJNTeRKlKc11LMDEg3NxEg8rfJ5HI51qxZg/j4eFy7dg09evTAunXrMHPmTHh5eWHjxo1CR1TYfngFdqVGo7yyBDKZMeYFbIJTR3cAtResrdg6EWvnnICxkQl2pqzG/coSBPt9JHBq1bkP/PgFDp35WrFuQdFVuHUdhsWB24SKS6QWKc5r1hAi4Yi6GZo+fTr27NmDZcuWwcPDA2lpaZg0aRJ+//13zJs3T+h4SgJfjECQ71KU3L+DmF3TkZGdjFEDpgOovWBtqNurSDyyEr793kDKuUTEzkkTOHEtVblHDZiu+HfRvULMj/fB1JErhIwrWsnnErEvbT2u3shAxcP7+O/HVUJHUku1vBpfJC3C/05vwYOqCnh0/yvmvhYPG0t7oaM1ixTnNWuIfmMNEZZo3yZLSEjAli1bsG/fPsyfPx8+Pj6IiIjAoEGDUFVVhb59+wodsV5WFm0xL2ATTv7yHdIy9yrGJ3gvQPql/YjcNgmhL8XCxMhUwJR1NZQbqD1DtzIhCNNHrUSHdl2ECShybczbYuygWQh9KVboKBpJTF6FtAt78UnYSSRE1D5/4eOEKQKn0h4pzmvWEP3EGiIs0TZDkZGRGDlyJLy8vJTGnZ2dYWxsDHd3d9y5cwdjxoyBi4sLevfujb/+9a/Izs4WKPGfrC3a4dVh87D54BLI5XIAgJHMGG5Ow1Fafge9ug4VOGH96ssNAF9//yG6dnDDkF4vCxdO5Pr38MMLfSbhGTsnoaNoJCl9Iyb6vIdn7JxgaW6DGaOjcOryQdy885vQ0bRGivOaNUT/sIYIS5TNUH5+PjIzMxEQUPdeFXl5eejZsydMTU1hYGCAuXPnIisrCxkZGRgzZgymTp0qQOK6xg97B0X3CvD9ma8AALmFF3Ah9zj6OPsi6eTnAqdr2JO5f/r1MM5k/Q8zRkcJnIy0rbS8GLeK89DdwUMx1tG+GyzMrHHlRoaAybRPivOaNYTErjXVENE2QwDQoUMHpfHy8nKkpqYq3iKztbWFr6+vYvngwYORk5Oj1jYMDAzU+kpNTWn0tWJCUxDku1RpzNLMGns+KoJf/2DI5XKs3fM2wsavx1v+q/DN8U9wp+Rmo6+bmpqids6WyF10rxCffjMHS4ISYGxk0ujrNTezVL7U2bdCULXv68t8v7IEAGBpbqM03sbMFvcr7ukiMgDN5owU57UUa4i6c1xs+1oKX2KtH4A0a0hj80VdoryA2t6+9sKrrKws+Pv7K8ajoqJQUFAADw+Pen8uNjYWL7/8si4iauTbE3Ho7uABF8fa3MF+y7Fh31xEBCUInEy1rYeWo6ziLlbvCFaMPftUD8x9LV64UKQ1FqZWAICy8rtK46UVxbAwsxYikk5IcV6zhpAYtaYaYlBTU1MjdIgnyeVy9OnTBwUFBYiOjoaDgwN2796NpKQk5OXlIT09HQMHDlT6mQ8//BAHDhzAkSNHYGFhobUspxOB4nytvZxGbB2Bfq837WeFyt2czFKhat9mXEnBwo2+gnwSRNW+byhz0IrOmDLi7xg5YBoAoOCPq3hjVTd8vThHZxe6ajJnpDivpVhDpJhZKhrbt6whmtHWfBHl22SGhobYtWsXevbsidDQUEydOhX29vaYPXs2ZDIZ3N3dldb/xz/+gf379+PgwYNabYSI1FUtr8aDhxV4WPUAAPDgYQUePKyACP/WUOLvORM7Uj5GQVEOyiru4fOk99DPxY+f+CHSMdYQYYnybTIAcHFxQXKy8tN2p0yZAldXV5ibmyvGPvzwQyQlJeH777+Hra2tjlMS1Tp05mtE7/zz4v3RS2rnqC7PsDTF6z6LUHr/Duas7Y+H1ZXo230EFgVuFToWkd5hDRGWaJuh+pw+fRqenp6K7y9cuIAPPvgA3bp1g7e3t2L83Llzug9Hes2vfzD8+gcLHUNjMkMZQsZGN+np10SkPawhwpJMM1RaWoqsrCzMmjVLMdazZ0/Rn0IkIiIicRPlNUP1adOmDaqrqxEWFiZ0FJWiEoMRtm6g0tX16/e+g1XbJwMAMnOOYVrUc0g6uUmoiPV6PHfGlRQEreiM8DhvfJzwBoDaZyOFrHkeXx5c2sgrEQnr8bmcff0sZsS4YXJkF8VyMc7vxjIDQGLyx1gY74vwOG/I5XJR1JLGcv/31BaEx3kjPM4b499vi+zr5wTf10T1kUwzJCWLArcp7rtwp+QmCov+vPdRr65DMdFnkVDRVHo8t6/HFMSEpuC9SbU3TnOwd8ascbECpiNS36O53NHOGevC0mFv46i0XIzzW1XmX/J+REVlKaJCDiEmNAWGhoaiqSWqcvv1D0ZMaAqiZh5Ce9vO6Naxtyj2NdGT2Aw1U/rF/di4fwHkcjkWfz4SvxfnKS3f80MsXh4ivrNZjeVOPpuAdzcMw5Gz4r6PCZGquWxhZgVzE8s6PyP0/NY0c/ql/bhbdhvzP/PB198L96T6puxrADifcxTuTsM1ugkekS6xGWomT9cxuFNyE//890x4uo7FU7adFMvu3S9CcdnvcLDvLmDC+qnK7eLYD5sX/oLItw7im2PrUFz6u4BJiVRTNZfrI4b5rWnm4pKbaGPRFtFvJyPv5kX8mv+TjpIq0zT3I8d+3oMhvca3cDqipmMzpAWjPUNwNGMnRg18S2n8Pz+sxbjBswVK1biGcpubtoGRzBjmJpZwcxqO67d/FSghkXoamsv1Ecv81iSzpZkN3J1qH1rdu5sP8m5daul4DdIkNwDU1NQgM+cY3JyGt3AyoqZjM9RMcrkc2w4tx+QRf8eOI6uUlhUW5eCLpMWI2vEmzl45gtSMnQKlrEtV7rL/f6ZMtbwaWddO4em2XQRISKQeVXO5PmKY35pmdu0yGDkF5wEAV26cQ4d2XVs6Yr00zQ0Al6+dQnfHvpAZylo4HVHTsRlqpm+Or8OQXuMR4BWOnMKfUfGwTLHsvUlfYeWMg1g48V/o0+0FePWeIGBSZapyp2bsxJx1AzB3/RAM6jkO9jYdBUxKpJqquXyr+BoWxvsitzATC+N9UViUK4r5rWlmz7+MwW83L2JenBdqauTo2WWwzjM3JTcAHM/8D4b2ekWQvETqEuWzycRE02f0xH87H5fy0rFi2nd1nuQL1H60fsO+uZjgtQDez09U+Vq6fB5SY7mv387GqoTJGO4egACv8AZfp7U/VwgQ9rlNqjTluUJioO1nkzU2l+vT2Pxu6WOxKZnVqSUt/Wwyse1rKZDqsSjW3NqaL2yGGnH5CFByS5htW7UHerzQtJ8VKndzMkuFkHNCFVX7XqyZAc3mjBTntRRriBQzS4VUj0Wx5tbWfGEzRERERHqN1wwRERGRXmMzRERERHqNzRARERHpNTZDREREpNfYDBEREZFeYzNEREREeo3NEBEREek1NkNERESk19gMERERkV5jM0RERER6jc0QERER6TU2Q0RERKTX2AwRERGRXmMzRERERHqNzRARERHpNTZDREREpNfYDBEREZFeYzNEREREeu3/ANDoHa95uw5SAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 748.797x204.68 with 1 Axes>"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "connectivity = [[0,1], [1,2], [2,0]]\n",
+    "circ = alternating_sq_2q_layers(3,2,'RXX', connectivity)\n",
+    "circ.draw('mpl')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "OPENQASM 2.0;\n",
+      "include \"qelib1.inc\";\n",
+      "qreg q[3];\n",
+      "rx(1.0) q[0];\n",
+      "rz(1.0) q[0];\n",
+      "rx(1.0) q[1];\n",
+      "rz(1.0) q[1];\n",
+      "rx(1.0) q[2];\n",
+      "rz(1.0) q[2];\n",
+      "rxx(1.0) q[0],q[1];\n",
+      "rxx(1.0) q[1],q[2];\n",
+      "rxx(1.0) q[2],q[0];\n",
+      "rz(1.0) q[0];\n",
+      "rx(1.0) q[0];\n",
+      "rz(1.0) q[0];\n",
+      "rz(1.0) q[1];\n",
+      "rx(1.0) q[1];\n",
+      "rz(1.0) q[1];\n",
+      "rz(1.0) q[2];\n",
+      "rx(1.0) q[2];\n",
+      "rz(1.0) q[2];\n",
+      "rxx(1.0) q[0],q[1];\n",
+      "rxx(1.0) q[1],q[2];\n",
+      "rxx(1.0) q[2],q[0];\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\c5517\\AppData\\Local\\Temp\\ipykernel_66640\\2418064179.py:2: DeprecationWarning: The method ``qiskit.circuit.quantumcircuit.QuantumCircuit.bind_parameters()`` is deprecated as of qiskit 0.45.0. It will be removed no earlier than 3 months after the release date. Use assign_parameters() instead\n",
+      "  print(qiskit.qasm2.dumps(circ.bind_parameters(np.ones(21))))\n"
+     ]
+    }
+   ],
+   "source": [
+    "# qasm convert\n",
+    "print(qiskit.qasm2.dumps(circ.bind_parameters(np.ones(21))))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.8.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}