{
  "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": "linear-systems",
  "nombre": "Linear Systems",
  "categoria": "Optimization, Numerics, and Machine Learning",
  "categoria_id": "ONML",
  "problema": "Resolver Ax = b. Es HHL, y el asterisco importa: entrega un estado cuantico que codifica la solucion, no el vector de respuesta.",
  "speedup_declarado": "Superpolynomial",
  "declarado_por": "Quantum Algorithm Zoo",
  "fuente_url": "https://quantumalgorithmzoo.org/#ONML",
  "implementaciones": [
    {
      "nombre": "Classiq (HHL)",
      "url": "https://short.classiq.io/hhl"
    },
    {
      "nombre": "Classiq (QSVT)",
      "url": "https://short.classiq.io/qsvt_inversion"
    },
    {
      "nombre": "Cirq (HHL)",
      "url": "https://github.com/quantumlib/Cirq/blob/main/examples/grover.py"
    },
    {
      "nombre": "Qrisp/Pennylane (HHL)",
      "url": "https://pennylane.ai/qml/demos/linear_equations_hhl_qrisp_catalyst"
    }
  ],
  "referencias": [
    {
      "n": 104,
      "cita": "Aram W. Harrow, Avinatan Hassidim, and Seth Lloyd Quantum algorithm for solving linear systems of equations. Physical Review Letters 15(103):150502, 2009. [ arXiv:0811.3171 ]",
      "url": "http://arxiv.org/abs/0811.3171"
    },
    {
      "n": 138,
      "cita": "Andris Ambainis Variable time amplitude amplification and a faster quantum algorithm for solving systems of linear equations. arXiv:1010.4458 , 2010.",
      "url": "http://arxiv.org/abs/1010.4458"
    },
    {
      "n": 156,
      "cita": "Dominic Berry Quantum algorithms for solving linear differential equations. J. Phys. A: Math. Theor. 47, 105301, 2014. [ arXiv:1010.2745 ].",
      "url": "http://arxiv.org/abs/1010.2745"
    },
    {
      "n": 169,
      "cita": "Nathan Wiebe, Daniel Braun, and Seth Lloyd Quantum data-fitting. Physical Review Letters 109, 050505, 2012. [ arXiv:1204.5242 ]",
      "url": "http://arxiv.org/abs/1204.5242"
    },
    {
      "n": 210,
      "cita": "Guoming Wang Quantum algorithms for approximating the effective resistances of electrical networks. arXiv:1311.1851",
      "url": "http://arxiv.org/abs/1311.1851"
    },
    {
      "n": 214,
      "cita": "Seth Lloyd, Masoud Mohseni, and Patrick Robentrost Quantum algorithms for supervised and unsupervised machine learning arXiv:1307.0411",
      "url": "http://arxiv.org/abs/1307.0411"
    },
    {
      "n": 220,
      "cita": "Amnon Ta-Shma Inverting well conditioned matrices in quantum logspace In Proceedings of STOC 2013 pg. 881-890.",
      "url": null
    },
    {
      "n": 222,
      "cita": "Seth Lloyd, Silvano Garnerone, and Paolo Zanardi Quantum algorithms for topological and geometric analysis of big data arXiv:1408.3106",
      "url": "http://arxiv.org/abs/1408.3106"
    },
    {
      "n": 246,
      "cita": "Scott Aaronson Read the fine print Nature Physics 11:291-293, 2015. [ fulltext ]",
      "url": "http://www.scottaaronson.com/papers/qml.pdf"
    },
    {
      "n": 249,
      "cita": "B. D. Clader, B. C. Jacobs, and C. R. Sprouse Preconditioned quantum linear system algorithm Phys. Rev. Lett. 110:250504, 2013. [ arXiv:1301.2340 ]",
      "url": "http://arxiv.org/abs/1301.2340"
    },
    {
      "n": 250,
      "cita": "S. Lloyd, M. Mohseni, and P. Rebentrost Quantum principal component analysis Nature Physics. 10(9):631, 2014. [ arXiv:1307.0401 ]",
      "url": "http://arxiv.org/abs/1307.0401"
    },
    {
      "n": 251,
      "cita": "Patrick Rebentrost, Masoud Mohseni, and Seth Lloyd Quantum support vector machine for big data classification Phys. Rev. Lett. 113, 130503, 2014. [ arXiv:1307.0471 ]",
      "url": "http://arxiv.org/abs/1307.0471"
    },
    {
      "n": 263,
      "cita": "Andrew M. Childs, Robin Kothari, and Rolando D. Somma Quantum linear systems algorithm with exponentially improved dependence on precision arXiv:1511.02306 , 2015.",
      "url": "http://arxiv.org/abs/1511.02306"
    },
    {
      "n": 279,
      "cita": "Bill Fefferman and Cedric Yen-Yu Lin A complete characterization of unitary quantum space arXiv:1604.01384 , 2016.",
      "url": "http://arxiv.org/abs/1604.01384"
    },
    {
      "n": 296,
      "cita": "Ashley Montanaro and Sam Pallister Quantum algorithms and the finite element method arXiv:1512.05903 , 2015.",
      "url": "http://arxiv.org/abs/1512.05903"
    },
    {
      "n": 297,
      "cita": "Lin-Chun Wan, Chao-Hua Yu, Shi-Jie Pan, Fei Gao, and Qiao-Yan Wen Quantum algorithm for the Toeplitz systems arXiv:1608.02184 , 2016.",
      "url": "http://arxiv.org/abs/1608.02184"
    },
    {
      "n": 309,
      "cita": "Iordanis Kerenidis and Anupam Prakash Quantum recommendation systems Innovations in Theoretical Computer Science (ITCS 2017) , LIPIcs, vol. 67 , pg. 1868-8969 . [ arXiv:1603.08675 ]",
      "url": "http://drops.dagstuhl.de/opus/portals/lipics/index.php?semnr=16054"
    },
    {
      "n": 369,
      "cita": "Pedro C.S. Costa, Stephen Jordan, and Aaron Ostrander Quantum algorithm for simulating the wave equation arXiv:1711.05394 , 2017.",
      "url": "https://arxiv.org/abs/1711.05394"
    },
    {
      "n": 400,
      "cita": "Ewin Tang A quantum-inspired classical algorithm for recommendation systems In Proceedings of STOC 2019 , pg. 217-228. [ arXiv:1807.04271 ]",
      "url": "https://arxiv.org/abs/1807.04271"
    },
    {
      "n": 401,
      "cita": "Ewin Tang Quantum-inspired classical algorithms for principal component analysis and supervised clustering arXiv:1811.00414 , 2018.",
      "url": "https://arxiv.org/abs/1811.00414"
    },
    {
      "n": 402,
      "cita": "L. Wossnig, Z. Zhao, and A. Prakash A quantum linear system algorithm for dense matrices Physical Review Letters vol. 120, no. 5, pg. 050502, 2018. arXiv:1704.06174 , 2017.",
      "url": "https://arxiv.org/abs/1704.06174"
    },
    {
      "n": 433,
      "cita": "András Gilyén, Yuan Su, Guang Hao Low, and Nathan Wiebe Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics Proceedings of STOC 2019 , pg. 193-204 [ arXiv:1806.01838 ]",
      "url": "https://arxiv.org/abs/1806.01838"
    },
    {
      "n": 494,
      "cita": "Pedro C.S. Costa, Dong An, Yuval R. Sanders, Yuan Su, Ryan Babbush, and Dominic W. Berry Optimal Scaling Quantum Linear-Systems Solver via Discrete Adiabatic Theorem PRX Quantum , 3:040303, 2022. [ arXiv:2111.08152 ]",
      "url": "https://arxiv.org/abs/2111.08152"
    },
    {
      "n": 543,
      "cita": "B. Baskaran, A. S. Rawat, A. Jayashankar, D. Chakravarti, K. Sugisaki, S. Roy, S. Mandal, D. Mukherjee, and V. S. Prasannaa Adapting the Harrow-Hassidim-Lloyd algorithm to quantum many-body theory Phys. Rev. Research , 5:043113, 2023. [ arXiv:2212.14781 ]",
      "url": "https://arxiv.org/abs/2212.14781"
    }
  ],
  "n_referencias": 24,
  "remisiones": [],
  "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."
  }
}