Quantum machine learning J Biamonte, P Wittek, N Pancotti, P Rebentrost, N Wiebe, S Lloyd Nature 549 (7671), 195-202, 2017 | 2352 | 2017 |

Elucidating reaction mechanisms on quantum computers M Reiher, N Wiebe, KM Svore, D Wecker, M Troyer Proceedings of the national academy of sciences 114 (29), 7555-7560, 2017 | 552 | 2017 |

Circuit-centric quantum classifiers M Schuld, A Bocharov, KM Svore, N Wiebe Physical Review A 101 (3), 032308, 2020 | 468 | 2020 |

Quantum algorithm for data fitting N Wiebe, D Braun, S Lloyd Physical review letters 109 (5), 050505, 2012 | 463 | 2012 |

Hartree-Fock on a superconducting qubit quantum computer Google AI Quantum and Collaborators*†, F Arute, K Arya, R Babbush, ... Science 369 (6507), 1084-1089, 2020 | 405 | 2020 |

Hamiltonian Simulation Using Linear Combinations of Unitary Operations AM Childs, N Wiebe Quantum Information and Computation 12, 901-924, 2012 | 338 | 2012 |

Quantum Nearest-Neighbor Algorithms for Machine Learning N Wiebe, A Kapoor, K Svore Quantum Information and Computation 15, 318-358, 2015 | 323* | 2015 |

Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics A Gilyén, Y Su, GH Low, N Wiebe Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019 | 319 | 2019 |

Low-depth quantum simulation of materials R Babbush, N Wiebe, J McClean, J McClain, H Neven, GKL Chan Physical Review X 8 (1), 011044, 2018 | 311 | 2018 |

Quantum simulation of electronic structure with linear depth and connectivity ID Kivlichan, J McClean, N Wiebe, C Gidney, A Aspuru-Guzik, GKL Chan, ... Physical review letters 120 (11), 110501, 2018 | 307 | 2018 |

Theory of trotter error with commutator scaling AM Childs, Y Su, MC Tran, N Wiebe, S Zhu Physical Review X 11 (1), 011020, 2021 | 260 | 2021 |

Solving strongly correlated electron models on a quantum computer D Wecker, MB Hastings, N Wiebe, BK Clark, C Nayak, M Troyer Physical Review A 92 (6), 062318, 2015 | 251 | 2015 |

Encoding electronic spectra in quantum circuits with linear T complexity R Babbush, C Gidney, DW Berry, N Wiebe, J McClean, A Paler, A Fowler, ... Physical Review X 8 (4), 041015, 2018 | 243 | 2018 |

Quantum deep learning N Wiebe, A Kapoor, KM Svore Quantum Information and Computation 16, 0541-0587, 2016 | 224 | 2016 |

The Trotter Step Size Required for Accurate Quantum Simulation of Quantum Chemistry D Poulin, MB Hastings, D Wecker, N Wiebe, AC Doherty, M Troyer Quantum Information and Computation 15, 0361-0384, 2015 | 192 | 2015 |

Hamiltonian learning and certification using quantum resources N Wiebe, C Granade, C Ferrie, DG Cory Physical Review Letters 112, 190501, 2013 | 188 | 2013 |

Experimental quantum Hamiltonian learning J Wang, S Paesani, R Santagati, S Knauer, AA Gentile, N Wiebe, ... Nature Physics 13 (6), 551-555, 2017 | 185 | 2017 |

Efficient Bayesian phase estimation N Wiebe, CE Granade Physical Review Letters 117, 010503, 2016 | 184 | 2016 |

Robust online Hamiltonian learning CE Granade, C Ferrie, N Wiebe, DG Cory New Journal of Physics 14, 103013, 2012 | 183 | 2012 |

Chemical basis of Trotter-Suzuki errors in quantum chemistry simulation R Babbush, J McClean, D Wecker, A Aspuru-Guzik, N Wiebe Physical Review A 91 (2), 022311, 2015 | 180 | 2015 |