{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# LOCCNet: A Machine Learning Framework for LOCC Protocols\n", "\n", " Copyright (c) 2021 Institute for Quantum Computing, Baidu Inc. All Rights Reserved. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Overview\n", "\n", "Quantum entanglement is an essential physical resource for quantum communication, quantum computation, and many other quantum technologies. Therefore, the ability to manipulate quantum entanglement reliably is an essential task if we want to build real applications in those fields. In the Noisy Intermediate-Scale Quantum (NISQ) era, directly transferring quantum information between the communication nodes inside a quantum network is an arduous task. Hence, the most natural set of operations to manipulate entanglement at this stage is the so-called Local Operations and Classical Communication (LOCC) [1] instead of global operations. Under this setup, several spatially separated parties can only implement local operations in their own labs and later communicates their measurement results (classical information) through a classical channel. Still, it is very challenging to design LOCC protocols for entanglement manipulation and further distributed quantum information processing tasks since the structure of LOCC is in general complicated and hard to characterize mathematically. To better explore the possibilities of near-term entanglement manipulation and long-term quantum information processing, we introduce **LOCCNet**, a machine learning framework for LOCC protocol design [2]." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What is LOCC?\n", "\n", "As we explained above, LOCC stands for Local Operations and Classical Communication. It is also known as the \"distant lab\" paradigm, where a multipartite quantum system is distributed to some spatially separated labs. Suppose there are $N$ labs involved, and each lab is allowed to implement a sequence of quantum operations $\\{\\mathcal{E}^{(k)}_j\\}_{j=0}^{r}$ with respect to their own subsystems $k \\in [1,\\cdots,N]$. These labs are allowed to communicate any classical data including all the measurement results. A general LOCC protocol can be categorized according to the communication rounds $r$ applied and the number of distant labs involved, denoted as LOCC$_r(N)$, and pictorially described by a tree graph. For example, the famous quantum teleportation protocol [3] belongs to the 1-round LOCC$_1(2)$ family where only two parties are involved (Alice and Bob). The basic idea is to transfer an unknown quantum state $|\\psi\\rangle$ from Alice to Bob and the workflow is summarized in Figure 1,\n", "\n", "\n", "