{
  "aviso": "speedup_declarado es lo que declara la fuente citada, NO una medición de Rosetta. Lo que Rosetta midió va en evidencia_rosetta, y para la mayoría del catálogo está vacío.",
  "procedencia": {
    "fuente": "Quantum Algorithm Zoo",
    "fuente_url": "https://quantumalgorithmzoo.org/",
    "instantanea_sha256": "dee7e76b5f19096ed329c88714744b93babf7b7d0296eb97e357b2582d16b75e",
    "generado_at": "2026-08-09"
  },
  "id": "gradient-estimation-and-learning-polynomials",
  "nombre": "Gradient Estimation and Learning Polynomials",
  "categoria": "Optimization, Numerics, and Machine Learning",
  "categoria_id": "ONML",
  "problema": "Estimar el gradiente de una funcion suave en un punto, o aprender los coeficientes de un polinomio, consultando un oraculo.",
  "speedup_declarado": "Polynomial",
  "declarado_por": "Quantum Algorithm Zoo",
  "fuente_url": "https://quantumalgorithmzoo.org/#gradients",
  "implementaciones": [],
  "referencias": [
    {
      "n": 20,
      "cita": "David Bulger Quantum basin hopping with gradient-based local optimisation. arXiv:quant-ph/0507193 , 2005.",
      "url": "http://arxiv.org/abs/quant-ph/0507193"
    },
    {
      "n": 61,
      "cita": "Stephen P. Jordan Fast quantum algorithm for numerical gradient estimation. Physical Review Letters , 95:050501, 2005. [ arXiv:quant-ph/0405146 ]",
      "url": "http://arxiv.org/abs/quant-ph/0405146"
    },
    {
      "n": 62,
      "cita": "Stephen P. Jordan Quantum Computation Beyond the Circuit Model . PhD thesis, Massachusetts Institute of Technology, 2008. [ arXiv:0809.2307 ]",
      "url": "http://arxiv.org/abs/0809.2307"
    },
    {
      "n": 94,
      "cita": "Andrew Yao On computing the minima of quadratic forms. In Proceedings of the 7th ACM Symposium on Theory of Computing , pages 23-26, 1975.",
      "url": null
    },
    {
      "n": 436,
      "cita": "András Gilyén, Srininvasan Arunachalam, and Nathan Wiebe Optimizing quantum optimization algorithms via faster quantum gradient computation Proceedings SODA 2019 , pp. 1425-1444 [ arXiv:1711.00465 ]",
      "url": "https://arxiv.org/abs/1711.00465"
    },
    {
      "n": 437,
      "cita": "Arjan Cornelissen Quantum gradient estimation of Gevrey functions arXiv:1909.13528 , 2019.",
      "url": "https://arxiv.org/abs/1909.13528"
    },
    {
      "n": 438,
      "cita": "Pan Gao, Keren Li, Shijie Wei, Jiancun Gao, and Guilu Long Quantum gradient algorithm for general polynomials Physical Review A 103:042403, 2021. [ arXiv:2004.11086 ]",
      "url": "https://arxiv.org/abs/2004.11086"
    },
    {
      "n": 439,
      "cita": "Yuxin Zhang and Changpeng Shao Quantum spectral method for gradient and Hessian estimation arXiv:2407.03833 , 2024.",
      "url": "https://arxiv.org/abs/2407.03833"
    }
  ],
  "n_referencias": 8,
  "remisiones": [
    {
      "ancla": "convex_optimization",
      "url": "https://quantumalgorithmzoo.org/#convex_optimization"
    }
  ],
  "evidencia_rosetta": {
    "medido": false,
    "lectura": "Rosetta no tiene ninguna corrida sellada sobre este algoritmo. Que esté catalogado no significa que lo hayamos medido ni que lo ofrezcamos."
  }
}