{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Programming with qat.lang\n",
    "\n",
    "This folder contains various tutorials describing the usage of the `qat.lang` module.\n",
    "\n",
    "To begin:\n",
    "* this first [notebook](./writing_quantum_program.ipynb) shows how to write a simple circuit and display it\n",
    "* pyAQASM offers classical control and measure operations. [This notebook](./measurements_and_classic_operations.ipynb) presents these features.\n",
    "* All the basic features are summed up in a single [notebook.](py_aqasm.ipynb)\n",
    "* This [notebook.](./custom_gate_set.ipynb) presents how to construct custom gates in pyAQASM.\n",
    "* [this notebook](./qft.ipynb) presents an example of a QRoutine implementing a QFT\n",
    "* The gate set of pyAQASM is described in [this notebook](./available_gates.ipynb).\n",
    "\n",
    "Some algorithms:\n",
    "* [this notebook](./needle_vs_haystack.ipynb) introduce a basic Quantum Search algorithm to look for clean coloration of a graph\n",
    "* [this directory](./algorithms/algorithms_overview.ipynb) contains other basic quantum algorithms pre-coded in the QLM\n",
    "\n",
    "More advanced usage:\n",
    "* [this notebook](./gate_sets.ipynb) shows how to declare and use a custom gate set in pyAQASM.\n",
    "* [this notebook](./inlining_vs_not_inlining.ipynb) explains the inlining process that is happening when extracting a circuit\n",
    "* the ancillae management feature is presented [here](./advanced_usage_ancillae.ipynb).\n",
    "* the compute/uncompute scheme using `with` statements is described [here](./advanced_usage_compute_uncompute.ipynb)\n",
    "* [this notebook](./linking.ipynb) presents how to write and link circuit libraries in pyAQASM\n",
    "* [while this notebook](./very_advanced_linker.ipynb) goes even further and show how to link gate implementation under controlled operators\n",
    "* [this notebook](./quantum_types.ipynb) introduces the notion of quantum types and show how to generate powerful quantum oracles\n",
    "* [and this notebook](./differentiating_jobs.ipynb) presents two methods to compute the derivative of a job with a cost function $E(\\vec{\\theta})$ for gradient-based optimization\n",
    "\n",
    "Text format:\n",
    "* [this notebook](./aqasm.ipynb) presents the AQASM text format"
   ]
  }
 ],
 "metadata": {
  "authors": [
   "Simon Martiel"
  ],
  "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",
   "version": "3.10.4"
  },
  "vscode": {
   "interpreter": {
    "hash": "f9f85f796d01129d0dd105a088854619f454435301f6ffec2fea96ecbd9be4ac"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}