Pull in updates from Qiskit/textbook (#2171)

* Pull in updates from Qiskit/textbook * adjust toc
Qiskit · Jul 20, 2023 · 543b658 · 543b658
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diff --git a/notebooks/toc.yaml b/notebooks/toc.yaml
@@ -760,7 +760,7 @@
   title: Applied quantum algorithms
   type: chapter
   url: /v1_ch-applications
-- id: quantum-hardware
+- id: ch-quantum-hardware
   overviewInfo:
     description:
       long: 'Most gate-based quantum computers share similar challenges with noise
@@ -817,51 +817,6 @@
     title: The density matrix and mixed states
     url: v1/ch-quantum-hardware/density-matrix
     uuid: 9f785388-6fab-4c13-b323-4d98cf215c03
-  title: Investigating quantum hardware using quantum circuits
-  type: chapter
-  url: /v1_quantum-hardware
-- id: quantum-hardware-pulses
-  overviewInfo:
-    description:
-      long: 'The Qiskit Textbook mostly assumes we have a quantum computer that can
-
-        carry out quantum operations, and doesn''t worry about how the devices
-
-        actually work. These pages go a step deeper, exploring the physics of
-
-        superconducting qubits, and using Qiskit to program operations on these
-
-        devices at the level of microwave pulses.
-
-        '
-      short: 'In this chapter, we get a level closer to the real quantum machines.
-
-        Learn about the physics of these devices, and how to program them at
-
-        the level of microwave pulses.
-
-        '
-    prerequisites:
-    - description: 'With the basics down, this chapter explores the consequences of
-        these
-
-        new quantum effects, and sets us up with tools to understand quantum
-
-        algorithms.
-
-        '
-      link: https://learn.qiskit.org/course/ch-gates/introduction
-      title: Multiple Qubits and Entanglement
-    - description: 'Python is a programming language where you don''t need to compile.
-        You
-
-        can just run it line by line...
-
-        '
-      link: https://learn.qiskit.org/course/ch-prerequisites/introduction-to-python-and-jupyter-notebooks
-      title: Python and Jupyter Notebooks
-    thumbnailUrl: /ch-quantum-hardware/overview/header-pulses.png
-  sections:
   - id: calibrating-qubits-pulse
     previewImgUrl: /ch-quantum-hardware/overview/calibrating-qubits-pulse.png
     title: Calibrating qubits with Qiskit Pulse
@@ -897,9 +852,9 @@
     title: Hamiltonian tomography
     url: v1/ch-quantum-hardware/hamiltonian-tomography
     uuid: 37cc881f-a795-43b1-85b6-cb94f9cda622
-  title: Investigating quantum hardware using microwave pulses
+  title: Investigating quantum hardware
   type: chapter
-  url: /v1_quantum-hardware-pulses
+  url: /v1_ch-quantum-hardware
 - id: ch-labs
   overviewInfo:
     description:
@@ -1078,8 +1033,6 @@
   url: /v1_ch-demos
 
 
-
-
 #---- Below was added by machine ---
 
 - id: basics-quantum-information

diff --git a/notebooks/v1/ch-algorithms/quantum-walk-search-algorithm.ipynb b/notebooks/v1/ch-algorithms/quantum-walk-search-algorithm.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "0f353c6f",
+   "id": "789a3892",
    "metadata": {
     "tags": [
      "remove_cell"
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6a696cd9",
+   "id": "7062b169",
    "metadata": {},
    "source": [
     "Quantum walks are the quantum equivalence of a classical Markov chain and have become key in many quantum algorithms. In this section, we implement a quantum walk search algorithm that finds marked elements in a graph. The algorithm has a quadratic speedup compared to its classical counterpart. \n",
@@ -168,7 +168,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "8402d335",
+   "id": "208ec8b2",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -188,7 +188,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "efc61c2b",
+   "id": "63b14e4b",
    "metadata": {},
    "source": [
     "The circuit will have 6 qubits, 4 that represents the position and 2 that represents the coin. As we mentioned previously, the coin is a Grover coin, which is the diffuser in Grover's algorithm. We start by implementing this. "
@@ -197,7 +197,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "7483f2e6",
+   "id": "1c565b0f",
    "metadata": {},
    "outputs": [
     {
@@ -226,7 +226,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2e2dcc18",
+   "id": "cacb9b5c",
    "metadata": {},
    "source": [
     "Now, let us implement the shift operator. We know that the walker can only move to neighboring nodes, and all neighboring nodes differ by only one bit. We want to move the walker according to the coin, and we move the walker by applying a NOT gate to one of the node qubits. If the coin is in state $\\ket{11}$, we move the walker to the state in which the first node qubit differ. If the coin is $\\ket{10}$ or $\\ket{01}$, the walker moves to the state where the second and third qubit, respectively, differ. Finally, if the Grover coin is $\\ket{00}$, we flip the fourth qubit. We implement this with CCNOT- and NOT gates after the Grover coin. Together, they are one step of a quantum walk on a 4-dimensional hypercube. "
@@ -235,7 +235,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "562d63b6",
+   "id": "7c99ea89",
    "metadata": {},
    "outputs": [
     {
@@ -269,7 +269,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "73e329ff",
+   "id": "86e61b23",
    "metadata": {},
    "source": [
     "## 4. Quantum walk search algorithm <a name=\"qwalkalgo\"></a>\n",
@@ -326,7 +326,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "78afba68",
+   "id": "e580d1d2",
    "metadata": {},
    "source": [
     "For this algorithm we will need to use the inverse of the one step gate implemented earlier. We get this by using the built in circuit function inverse()."
@@ -335,7 +335,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "257cb2e4",
+   "id": "fa21fd41",
    "metadata": {},
    "outputs": [
     {
@@ -358,7 +358,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c026ba67",
+   "id": "2182b987",
    "metadata": {},
    "source": [
     "The inversed one step gate will be used to reverse the phase estimation later. We need to make controlled gates from both the one step gate that we implemented in section 3 and its inverse. We will later use them depending on the value of the control qubit.  "
@@ -367,7 +367,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "c13dc3a1",
+   "id": "0520f182",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -380,7 +380,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e3b2de86",
+   "id": "33509a78",
    "metadata": {},
    "source": [
     "Both the controlled one step gate and the controlled inversed one step gate will be used in the phase estimation. Another thing we will use in the phase estimation is the Quantum Fourier Transform. Qiskit has a function, QFT, which implements the Quantum Fourier Transform. The phase estimation uses the inverse Quantum Fourier Transform but we also will need to use the ordinary QFT to reverse the phase estimation."
@@ -389,7 +389,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "de85ac13",
+   "id": "f9c7b584",
    "metadata": {},
    "outputs": [
     {
@@ -415,7 +415,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6096d0dd",
+   "id": "59c8de1b",
    "metadata": {},
    "source": [
     "Before we implement the phase estimation, we implement a phase oracle that marks the states 1011 and 1111. Then, we make it a circuit. This is step 2(a) of the algorithm."
@@ -424,7 +424,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "4a93bcfb",
+   "id": "5286be30",
    "metadata": {
     "scrolled": true
    },
@@ -464,7 +464,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a91335f4",
+   "id": "1e10513b",
    "metadata": {},
    "source": [
     "We will now implement a gate that rotates an auxiliary qubit if the other qubits are non-zero. We will use this gate in the phase estimation, where it will rotate the auxiliary qubit if $\\theta \\neq 0$. "
@@ -473,7 +473,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "825f9d6c",
+   "id": "ede560cd",
    "metadata": {},
    "outputs": [
     {
@@ -505,7 +505,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4fad4857",
+   "id": "f211880a",
    "metadata": {},
    "source": [
     "Now, we will implement step 2(b) of the algorithm. This step consists of a phase estimation one step of the quantum walk followed by an auxiliary qubit that we rotate if $\\theta \\neq 0$. For this, we use the mark_auxiliary_gate that we just created.  Thereafter, we reverse the phase estimation. "
@@ -514,7 +514,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "5bdc78d0",
+   "id": "cb444542",
    "metadata": {
     "scrolled": false
    },
@@ -565,7 +565,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5c8c53bc",
+   "id": "f95647a5",
    "metadata": {},
    "source": [
     "Now we implement the whole quantum walk search algorithm using the gates we made previously. We start by applying Hadamard gates to node and coin qubits, which is step 1 in the algorithm. Thereafter, we iteratively apply the phase oracle gate and the phase estimation gate (steps 2(a) and 2(b)). We need $O(1/\\sqrt{\\epsilon})$ iterations as stated in the description of the algorithm in section 4. Lastly, we measure the node qubits. "
@@ -574,7 +574,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "160eb345",
+   "id": "18f74668",
    "metadata": {},
    "outputs": [
     {
@@ -616,7 +616,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1b8ae6fa",
+   "id": "1571cb59",
    "metadata": {},
    "source": [
     "Finally we run the implementation on the qasm simulator. We see that the circuit collapse to the marked states a clear majority of the times. "
@@ -625,7 +625,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "ec69c953",
+   "id": "bf5d9a24",
    "metadata": {},
    "outputs": [
     {
@@ -651,7 +651,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3792ca7d",
+   "id": "ca83111a",
    "metadata": {},
    "source": [
     "## 6. References <a id='references'></a>\n",
@@ -665,7 +665,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "d257ed54",
+   "id": "f143caba",
    "metadata": {},
    "outputs": [
     {

diff --git a/notebooks/v1/ch-algorithms/shor.ipynb b/notebooks/v1/ch-algorithms/shor.ipynb
@@ -131,7 +131,7 @@
    "source": [
     "## 2. The Solution\n",
     "\n",
-    "Shor’s solution was to use [quantum phase estimation](./quantum-phase-estimation) on the unitary operator:\n",
+    "Shor’s solution was to use [quantum phase estimation](./quantum-phase-estimation.html) on the unitary operator:\n",
     "\n",
     "$$ U|y\\rangle \\equiv |ay \\bmod N \\rangle $$\n",
     "\n",