moved tutorial

MQT Tutorial/MQT Qudits in Short.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "69b78731",
+   "metadata": {},
+   "source": [
+    "# MQT Qudits 🌌\n",
+    "*Discover a New Dimension in Quantum Computing*\n",
+    "\n",
+    "Embark on a journey with MQT Qudits, a cutting-edge toolkit for Mixed-Dimensional Quantum Computing.\n",
+    "\n",
+    "<br>\n",
+    "<p>Delve into the realm of mixed-dimensional quantum computing with NeQST—a project funded by the European Union and developed at the <a href=\"https://www.cda.cit.tum.de/\" target=\"_blank\">Chair for Design Automation</a> at the Technical University of Munich, as part of the <a href=\"https://www.cda.cit.tum.de/research/quantum/mqt/\" target=\"_blank\">Munich Quantum Toolkit</a>.</p> Our team is focused on creating design automation methods and software for quDit-based systems. Explore our Jupyter file to discover the initial tools and contributions we've made to advance Quantum Information Processing for Science and Technology.\n",
+    "<img src=\"foot.png\" alt=\"Logo 1\" width=\"400\"/> \n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b95c4040",
+   "metadata": {},
+   "source": [
+    "# User Inputs 💻\n",
+    "\n",
+    "🚀 **New QASM Extension:**\n",
+    "Dive into a language meticulously designed to express quantum algorithms and circuits. MQT extends the openQASM 2.0 grammar, effortlessly adapting to registers that feature a harmonious mix of qudits and qubits in diverse combinations. \n",
+    "\n",
+    "🐍 **Python Interface** \n",
+    "\n",
+    "Constructing and manipulating quantum programs becomes a breeze with Python. You have the flexibility to:\n",
+    "\n",
+    "1. **Initialize Quantum Circuits:** Start by creating your quantum circuits effortlessly.\n",
+    "\n",
+    "2. **Create Quantum Registers:** Build dedicated quantum registers tailored to your needs.\n",
+    "\n",
+    "3. **Compose Circuits:** Seamlessly bring together your quantum registers, forming a unified and powerful circuit.\n",
+    "\n",
+    "4. **Apply Operations:** Easily apply a variety of qudit operations, without worrying about the right representation. \n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7bc57c87",
+   "metadata": {},
+   "source": [
+    "<img src=\"2dqed.png\" alt=\"2dqed.png\" width=\"350\"/>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ac47688d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from mqt.qudits.qudit_circuits.circuit import QuantumCircuit"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f0157fd8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "qasm = \"\"\"\n",
+    "        DITQASM 2.0;\n",
+    "        \n",
+    "        qreg fields [3][5,5,5];\n",
+    "        qreg matter [2][2,2];\n",
+    "        \n",
+    "        h fields[2] ctl matter[0] matter[1] [0,0];\n",
+    "        cx fields[2], matter[0];\n",
+    "        cx fields[2], matter[1];\n",
+    "        rxy (0, 1, pi, pi/2) fields[2];\n",
+    "        \n",
+    "        measure q[0] -> meas[0];\n",
+    "        measure q[1] -> meas[1];\n",
+    "        measure q[2] -> meas[2];\n",
+    "        \"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3c421902",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "circuit = QuantumCircuit()\n",
+    "circuit.from_qasm(qasm)\n",
+    "\n",
+    "print(f\"\\n Number of operations: {len(circuit.instructions)}, \\n Number of qudits in the circuit: {circuit.num_qudits}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fdd6eef4",
+   "metadata": {},
+   "source": [
+    "##### Let's construct a quantum circuit from scratch.\n",
+    "<br>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "468735a3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from mqt.qudits.qudit_circuits.components.registers.quantum_register import QuantumRegister\n",
+    "\n",
+    "\n",
+    "circuit = QuantumCircuit()\n",
+    "\n",
+    "field_reg = QuantumRegister(\"fields\", 1, [3])\n",
+    "ancilla_reg = QuantumRegister(\"ancillas\", 1, [3])\n",
+    "\n",
+    "circuit.append(field_reg)\n",
+    "circuit.append(ancilla_reg)\n",
+    "\n",
+    "h = circuit.h(field_reg[0])\n",
+    "csum = circuit.csum([field_reg[0], ancilla_reg[0]])\n",
+    "\n",
+    "print(h.to_matrix())\n",
+    "print(f\"\\n Number of operations: {len(circuit.instructions)}, \\n Number of qudits in the circuit: {circuit.num_qudits}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "53329ff9",
+   "metadata": {},
+   "source": [
+    "\n",
+    "##### It is possible to export the code and share your program in a QASM file.\n",
+    "<br>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "32658fe9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(circuit.to_qasm())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3a6b2672",
+   "metadata": {},
+   "source": [
+    "# Simulation 🚀\n",
+    "\n",
+    "After crafting your quantum circuit with precision, take it for a spin using two distinct engines, each flaunting its unique set of data structures.\n",
+    "\n",
+    "- **External Tensor-Network Simulator:** Delve into the quantum realm with a robust external tensor-network simulator.\n",
+    "\n",
+    "- **MiSiM (C++-Powered):** Unleash the power of decision-diagram-based simulation with MiSiM, seamlessly interfaced with Python for a fluid and efficient experience. 🌐💡"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9d2a8eb0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from mqt.qudits.simulation.provider.qudit_provider import MQTQuditProvider\n",
+    "\n",
+    "\n",
+    "provider = MQTQuditProvider()\n",
+    "provider.backends(\"sim\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5b16d935",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from mqt.qudits.visualisation.plot_information import plot_counts, plot_state\n",
+    "\n",
+    "backend = provider.get_backend(\"tnsim\")\n",
+    "\n",
+    "job = backend.run(circuit)\n",
+    "result = job.result()\n",
+    "\n",
+    "state_vector = result.get_state_vector()\n",
+    "\n",
+    "plot_state(state_vector, circuit)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cc320e6b",
+   "metadata": {},
+   "source": [
+    "# Compilation ⚙️\n",
+    "\n",
+    "Emulate the features of the best experimental laboratories in your compilation process. Leverage modern compiler passes to customize optimization, gate decomposition, and noise-aware strategies, creating compiled circuits that closely resemble the challenges and advantages of cutting-edge quantum hardware.\n",
+    "\n",
+    "Customize, compile, and push the boundaries of quantum algorithms with a tailored approach to quantum compilation. 🛠️🔧🚀\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dd61551f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from mqt.qudits.compiler.dit_manager import QuditManager\n",
+    "\n",
+    "backend_ion = provider.get_backend(\"faketraps2trits\", shots=1000)\n",
+    "\n",
+    "qudit_compiler = QuditManager()\n",
+    "\n",
+    "passes = [\"LocQRPass\"]\n",
+    "\n",
+    "compiled_circuit_qr = qudit_compiler.compile(backend_ion, circuit, passes)\n",
+    "\n",
+    "print(\n",
+    "    f\"\\n Number of operations: {len(compiled_circuit_qr.instructions)}, \\n Number of qudits in the circuit: {compiled_circuit_qr.num_qudits}\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "21a11514",
+   "metadata": {},
+   "source": [
+    "### Extending Simulation with Noise Model Integration\n",
+    "\n",
+    "Introduce realism into your simulations by incorporating a noise model. Simulate the effects of environmental factors and imperfections, bringing your quantum algorithms closer to real-world scenarios."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a7fa4150",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "job = backend_ion.run(compiled_circuit_qr)\n",
+    "result = job.result()\n",
+    "counts = result.get_counts()\n",
+    "\n",
+    "plot_counts(counts, compiled_circuit_qr)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "91b7145d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}