edit bell test

toumix · toumix · commit 77251dd727ab · 2020-02-18T10:49:58.000Z
diff --git a/notebooks/bell-test.ipynb b/notebooks/bell-test.ipynb
@@ -7,7 +7,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -19,8 +19,8 @@
    "source": [
     "from discopy.circuit import *\n",
     "\n",
-    "snake = Circuit.caps(PRO(1), PRO(1)) @ Id(1) >> Id(1) @ Circuit.cups(PRO(1), PRO(1))\n",
-    "snake.draw(draw_types=False)"
+    "circuit = H @ Id(1) >> CX\n",
+    "circuit.draw()"
    ]
   },
   {
@@ -31,12 +31,7 @@
     {
      "data": {
       "text/plain": [
-       "[H q[0];,\n",
-       " CX q[0], q[1];,\n",
-       " CX q[1], q[2];,\n",
-       " H q[1];,\n",
-       " Measure q[2] --> c[1];,\n",
-       " Measure q[1] --> c[0];]"
+       "[H q[0];, CX q[0], q[1];]"
       ]
      },
      "execution_count": 2,
@@ -45,57 +40,65 @@
     }
    ],
    "source": [
-    "tk_circ, post_selection, scalar = snake.to_tk()\n",
+    "tk_circ = circuit.to_tk()\n",
     "list(tk_circ)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
-    "from pytket.backends.ibm import AerBackend"
+    "from pytket.backends.ibm import IBMQBackend"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Job Status: job has successfully run\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
-       "Matrix(dom=Dim(1), cod=Dim(2), array=[1.0078124, 0.0])"
+       "Matrix(dom=Dim(1), cod=Dim(2, 2), array=[0.5078125, 0.026367188, 0.009765625, 0.4560547])"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "snake.get_counts(AerBackend())"
+    "circuit.get_counts(IBMQBackend('ibmq_5_yorktown'))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "DeviceArray([0.99999976, 0.        ], dtype=float32)"
+       "DeviceArray([[0.49999997, 0.        ],\n",
+       "             [0.        , 0.49999997]], dtype=float32)"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "(Ket(0) >> snake).measure()"
+    "(Ket(0, 0) >> circuit).measure()"
    ]
   },
   {

Original file line number	Diff line number	Diff line change
`@@ -7,7 +7,7 @@`
`7`	`7`	`"outputs": [`
`8`	`8`	`{`
`9`	`9`	`"data": {`
`10`		- "image/png": "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\n",
	`10`	+ "image/png": "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\n",
`11`	`11`	`"text/plain": [`
`12`	`12`	`"<Figure size 432x288 with 1 Axes>"`
`13`	`13`	`]`
`@@ -19,8 +19,8 @@`
`19`	`19`	`"source": [`
`20`	`20`	`"from discopy.circuit import *\n",`
`21`	`21`	`"\n",`
`22`		`- "snake = Circuit.caps(PRO(1), PRO(1)) @ Id(1) >> Id(1) @ Circuit.cups(PRO(1), PRO(1))\n",`
`23`		`- "snake.draw(draw_types=False)"`
	`22`	`+ "circuit = H @ Id(1) >> CX\n",`
	`23`	`+ "circuit.draw()"`
`24`	`24`	`]`
`25`	`25`	`},`
`26`	`26`	`{`
`@@ -31,12 +31,7 @@`
`31`	`31`	`{`
`32`	`32`	`"data": {`
`33`	`33`	`"text/plain": [`
`34`		`- "[H q[0];,\n",`
`35`		`- " CX q[0], q[1];,\n",`
`36`		`- " CX q[1], q[2];,\n",`
`37`		`- " H q[1];,\n",`
`38`		`- " Measure q[2] --> c[1];,\n",`
`39`		`- " Measure q[1] --> c[0];]"`
	`34`	`+ "[H q[0];, CX q[0], q[1];]"`
`40`	`35`	`]`
`41`	`36`	`},`
`42`	`37`	`"execution_count": 2,`
`@@ -45,57 +40,65 @@`
`45`	`40`	`}`
`46`	`41`	`],`
`47`	`42`	`"source": [`
`48`		`- "tk_circ, post_selection, scalar = snake.to_tk()\n",`
	`43`	`+ "tk_circ = circuit.to_tk()\n",`
`49`	`44`	`"list(tk_circ)"`
`50`	`45`	`]`
`51`	`46`	`},`
`52`	`47`	`{`
`53`	`48`	`"cell_type": "code",`
`54`		`- "execution_count": 3,`
	`49`	`+ "execution_count": 6,`
`55`	`50`	`"metadata": {},`
`56`	`51`	`"outputs": [],`
`57`	`52`	`"source": [`
`58`		`- "from pytket.backends.ibm import AerBackend"`
	`53`	`+ "from pytket.backends.ibm import IBMQBackend"`
`59`	`54`	`]`
`60`	`55`	`},`
`61`	`56`	`{`
`62`	`57`	`"cell_type": "code",`
`63`		`- "execution_count": 4,`
	`58`	`+ "execution_count": 8,`
`64`	`59`	`"metadata": {},`
`65`	`60`	`"outputs": [`
	`61`	`+ {`
	`62`	`+ "name": "stdout",`
	`63`	`+ "output_type": "stream",`
	`64`	`+ "text": [`
	`65`	`+ "Job Status: job has successfully run\n"`
	`66`	`+ ]`
	`67`	`+ },`
`66`	`68`	`{`
`67`	`69`	`"data": {`
`68`	`70`	`"text/plain": [`
`69`		`- "Matrix(dom=Dim(1), cod=Dim(2), array=[1.0078124, 0.0])"`
	`71`	`+ "Matrix(dom=Dim(1), cod=Dim(2, 2), array=[0.5078125, 0.026367188, 0.009765625, 0.4560547])"`
`70`	`72`	`]`
`71`	`73`	`},`
`72`		`- "execution_count": 4,`
	`74`	`+ "execution_count": 8,`
`73`	`75`	`"metadata": {},`
`74`	`76`	`"output_type": "execute_result"`
`75`	`77`	`}`
`76`	`78`	`],`
`77`	`79`	`"source": [`
`78`		`- "snake.get_counts(AerBackend())"`
	`80`	`+ "circuit.get_counts(IBMQBackend('ibmq_5_yorktown'))"`
`79`	`81`	`]`
`80`	`82`	`},`
`81`	`83`	`{`
`82`	`84`	`"cell_type": "code",`
`83`		`- "execution_count": 5,`
	`85`	`+ "execution_count": 10,`
`84`	`86`	`"metadata": {},`
`85`	`87`	`"outputs": [`
`86`	`88`	`{`
`87`	`89`	`"data": {`
`88`	`90`	`"text/plain": [`
`89`		`- "DeviceArray([0.99999976, 0. ], dtype=float32)"`
	`91`	`+ "DeviceArray([[0.49999997, 0. ],\n",`
	`92`	`+ " [0. , 0.49999997]], dtype=float32)"`
`90`	`93`	`]`
`91`	`94`	`},`
`92`		`- "execution_count": 5,`
	`95`	`+ "execution_count": 10,`
`93`	`96`	`"metadata": {},`
`94`	`97`	`"output_type": "execute_result"`
`95`	`98`	`}`
`96`	`99`	`],`
`97`	`100`	`"source": [`
`98`		`- "(Ket(0) >> snake).measure()"`
	`101`	`+ "(Ket(0, 0) >> circuit).measure()"`
`99`	`102`	`]`
`100`	`103`	`},`
`101`	`104`	`{`