{
  "id": "2102.03879",
  "version": "v1",
  "published": "2021-02-07T18:49:28.000Z",
  "updated": "2021-02-07T18:49:28.000Z",
  "title": "Quantum computing models for artificial neural networks",
  "authors": [
    "Stefano Mangini",
    "Francesco Tacchino",
    "Dario Gerace",
    "Daniele Bajoni",
    "Chiara Macchiavello"
  ],
  "comment": "8 pages, 1 figure",
  "categories": [
    "quant-ph"
  ],
  "abstract": "Neural networks are computing models that have been leading progress in Machine Learning (ML) and Artificial Intelligence (AI) applications. In parallel, the first small scale quantum computing devices have become available in recent years, paving the way for the development of a new paradigm in information processing. Here we give an overview of the most recent proposals aimed at bringing together these ongoing revolutions, and particularly at implementing the key functionalities of artificial neural networks on quantum architectures. We highlight the exciting perspectives in this context and discuss the potential role of near term quantum hardware in the quest for quantum machine learning advantage.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2021-02-07T18:49:28.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "artificial neural networks",
      "quantum computing models",
      "small scale quantum computing devices",
      "first small scale quantum computing"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 8,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}