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The Quantum Fisher Information matrix (QFIM) is a central metric in promising algorithms, such as Quantum Natural Gradient Descent and Variational Quantum Imaginary Time Evolution.
Quantum Algorithms for Mixed Binary Optimization applied to Transaction Settlement
Lee Braine, Daniel J. Egger, Jennifer Glick, and Stefan Woerner · 1910
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Grover Adaptive Search for Constrained Polynomial Binary Optimization
Austin Gilliam, Stefan Woerner, and Constantin Gonciulea · 1912
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A variational solution of the time-dependent Schrödinger equation
A.D. McLachlan · 1964
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Multivariate stochastic approximation using a simultaneous perturbation gradient approximation
J.C. Spall · 1992
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Accelerated second-order stochastic optimization using only function measurements
J. C. Spall · 1997
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Quantum statistical mechanics and Feller semigroup
Taku Matsui · 1998
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Why natural gradient?
S. Amari and S. C. Douglas · 1998
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Quantum fingerprinting
Harry Buhrman, Richard Cleve, John Watrous, and Ronald de Wolf · 2001
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A Variational Quantum Algorithm for Preparing Quantum Gibbs States
Anirban Chowdhury, Guang Hao Low, and Nathan Wiebe · 2002
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Simulated Quantum Computation of Molecular Energies
Alán Aspuru-Guzik, Anthony D. Dutoi, Peter J. Love, and Martin Head-Gordon · 2005
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An Invitation to Noncommutative Geometry
Masoud Khalkhali and Matilde Marcolli · 2008
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Sampling from the Thermal Quantum Gibbs State and Evaluating Partition Functions with a Quantum Computer
David Poulin and Pawel Wocjan · 2009
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Quantum Metropolis Sampling
Kristan Temme, Tobias J. Osborne, Karl Gerd H. Vollbrecht, David Poulin, and Frank Verstraete · 2011
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Finding low-energy conformations of lattice protein models by quantum annealing
Alejandro Perdomo-Ortiz, Neil Dickson, Marshall Drew-Brook, Geordie Rose, and Alán Aspuru-Guzik · 2012
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A quantum–quantum Metropolis algorithm
Man-Hong Yung and Alán Aspuru-Guzik · 2012
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A variational eigenvalue solver on a photonic quantum processor
Alberto Peruzzo et al · 2014
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A Quantum Approximate Optimization Algorithm
Edward Farhi, Jeffrey Goldstone, and Sam Gutmann · 2014
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Quantum many-body systems out of equilibrium
J. Eisert, M. Friesdorf, and C. Gogolin · 2015
Cited alongside, same era.
Quantum Gibbs Samplers: The Commuting Case
Michael J. Kastoryano and Fernando G. S. L. Brandão · 2016
Cited alongside, same era.
Unsupervised Machine Learning on a Hybrid Quantum Computer
J. S. Otterbach et al · 2017
Cited alongside, same era.
Quantum SDP Solvers: Large speed-ups, optimality, and applications to quantum learning
Fernando G. S. L. Brandão et al · 2017
Cited alongside, same era.
Efficient computation of the fisher information matrix in the em algorithm
Lingyao Meng and James C. Spall · 2017
Cited alongside, same era.
Error mitigation extends the computational reach of a noisy quantum processor
Abhinav Kandala, Kristan Temme, Antonio D. Corcoles, Antonio Mezzacapo, Jerry M. Chow, and Jay M. Gambetta · 2019
Later among the works it cites.
Simulating lattice gauge theories within quantum technologies
Mari Carmen Bañuls et al · 2020
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Quantum-enhanced simulation-based optimization
J. Gacon, C. Zoufal, and S. Woerner · 2020
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Quantum computing for finance: State-of-the-art and future prospects
D. J. Egger et al · 2020
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Variational quantum boltzmann machines
Christa Zoufal, Aurélien Lucchi, and Stefan Woerner · 2020
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Quantum natural gradient
James Stokes, Josh Izaac, Nathan Killoran, and Giuseppe Carleo · 2020
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Sergey Bravyi, Jay M. Gambetta, Antonio Mezzacapo, and Kristan Temme · 2017
Cited alongside, same era.
Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets
Abhinav Kandala et al · 2017
Cited alongside, same era.
A quantum alternating operator ansatz with hard and soft constraints for lattice protein folding
Mark Fingerhuth, Tomáš Babej, and Christopher Ing · 2018
Cited alongside, same era.
Quantum Boltzmann Machine
Mohammad H. Amin, Evgeny Andriyash, Jason Rolfe, Bohdan Kulchytskyy, and Roger Melko · 2018
Cited alongside, same era.
Learning the quantum algorithm for state overlap
Lukasz Cincio, Yiğit Subaşı, Andrew T. Sornborger, and Patrick J. Coles · 2018
Cited alongside, same era.
Supervised learning with quantum-enhanced feature spaces
Vojtěch Havlíček et al · 2019
Cited alongside, same era.
Theory of variational quantum simulation
Xiao Yuan, Suguru Endo, Qi Zhao, Ying Li, and Simon C. Benjamin · 2019
Cited alongside, same era.
Determining eigenstates and thermal states on a quantum computer using quantum imaginary time evolution
Mario Motta and et al · 2020
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An Adaptive Optimizer for Measurement-Frugal Variational Algorithms
Jonas M. Kübler, Andrew Arrasmith, Lukasz Cincio, and Patrick J. Coles · 2020
Later among the works it cites.
Quantum machine learning models are kernel methods
Maria Schuld · 2021
Closest in time.
Natural Gradient Optimization for Optical Quantum Circuits
Yuan Yao, Pierre Cussenot, Alex Vigneron, and Filippo M. Miatto · 2021
Closest in time.
Fisher Information in Noisy Intermediate-Scale Quantum Applications
Johannes Jakob Meyer · 2021
Closest in time.
Estimating the gradient and higher-order derivatives on quantum hardware
Andrea Mari, Thomas R. Bromley, and Nathan Killoran · 2021
Closest in time.
URL https://quantum-computing.ibm.com/services/docs/services/runtime/
IBM Quantum, 2021 · 2021
Closest in time.
Resource-efficient quantum algorithm for protein folding
Anton Robert, Panagiotis Kl. Barkoutsos, Stefan Woerner, and Ivano Tavernelli · 2056
Closest in time.
Variational ansatz-based quantum simulation of imaginary time evolution
Sam McArdle et al · 2056
Closest in time.
Quantum optimization using variational algorithms on near-term quantum devices
Nikolaj Moll et al · 2058
Closest in time.