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The variational quantum-classical algorithms are the most promising approach for achieving quantum advantage on near-term quantum simulators.
“Subspace variational quantum simulator” (2019)
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“Symmetry: An introduction to group theory and its applications”
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“Optimal quantum circuits for general two-qubit gates”
Farrokh Vatan and Colin Williams · 2004
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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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“New perspectives on unitary coupled-cluster theory”
Andrew G Taube and Rodney J Bartlett · 2006
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“Mog-vqe: Multiobjective genetic variational quantum eigensolver” (2020)
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“Efficient quantum algorithm for preparing molecular-system-like states on a quantum computer”
Hefeng Wang, S Ashhab, and Franco Nori · 2009
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“Universal digital quantum simulation with trapped ions”
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“Generalized quantum assisted simulator” (2020)
Tobias Haug and Kishor Bharti · 2011
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“Photonic quantum simulators”
Alán Aspuru-Guzik and Philip Walther · 2012
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“Quantum circuit design search” (2020)
Mohammad Pirhooshyaran and Tamas Terlaky · 2012
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“Quantum mechanics: symmetries”
Walter Greiner and Berndt Müller · 2012
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“Molecular electronic-structure theory”
Trygve Helgaker, Poul Jorgensen, and Jeppe Olsen · 2013
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“Swap test and hong-ou-mandel effect are equivalent”
Juan Carlos Garcia-Escartin and Pedro Chamorro-Posada · 2013
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“A variational eigenvalue solver on a photonic quantum processor”
Alberto Peruzzo, Jarrod McClean, Peter Shadbolt, Man-Hong Yung, Xiao-Qi Zhou, Peter J Love, Alán Aspuru-Guzik, and Jeremy L O’brien · 2014
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“A quantum approximate optimization algorithm” (2014)
Edward Farhi, Jeffrey Goldstone, and Sam Gutmann · 2014
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“Linear-algebraic bath transformation for simulating complex open quantum systems”
Joonsuk Huh, Sarah Mostame, Takatoshi Fujita, Man-Hong Yung, and Alán Aspuru-Guzik · 2014
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“Observation of many-body localization of interacting fermions in a quasirandom optical lattice”
Michael Schreiber, Sean S Hodgman, Pranjal Bordia, Henrik P Lüschen, Mark H Fischer, Ronen Vosk, Ehud Altman, Ulrich Schneider, and Immanuel Bloch · 2015
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“Progress towards practical quantum variational algorithms”
Dave Wecker, Matthew B Hastings, and Matthias Troyer · 2015
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“Quantum simulation of the hubbard model with dopant atoms in silicon”
J Salfi, JA Mol, R Rahman, G Klimeck, MY Simmons, LCL Hollenberg, and S Rogge · 2016
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“Digitized adiabatic quantum computing with a superconducting circuit”
Rami Barends, Alireza Shabani, Lucas Lamata, Julian Kelly, Antonio Mezzacapo, Urtzi Las Heras, Ryan Babbush, Austin G Fowler, Brooks Campbell, Yu Chen, et al · 2016
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“The theory of variational hybrid quantum-classical algorithms”
Jarrod R McClean, Jonathan Romero, Ryan Babbush, and Alán Aspuru-Guzik · 2016
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“The su-schrieffer-heeger (ssh) model”
János K Asbóth, László Oroszlány, and András Pályi · 2016
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“Scalable quantum simulation of molecular energies”
Peter JJ O’Malley, Ryan Babbush, Ian D Kivlichan, Jonathan Romero, Jarrod R McClean, Rami Barends, Julian Kelly, Pedram Roushan, Andrew Tranter, Nan Ding, et al · 2016
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“Probing slow relaxation and many-body localization in two-dimensional quasiperiodic systems”
Pranjal Bordia, Henrik Lüschen, Sebastian Scherg, Sarang Gopalakrishnan, Michael Knap, Ulrich Schneider, and Immanuel Bloch · 2017
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“Quantum simulations with ultracold atoms in optical lattices”
Christian Gross and Immanuel Bloch · 2017
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“Quantum simulation of a fermi–hubbard model using a semiconductor quantum dot array”
Toivo Hensgens, Takafumi Fujita, Laurens Janssen, Xiao Li, CJ Van Diepen, Christian Reichl, Werner Wegscheider, S Das Sarma, and Lieven MK Vandersypen · 2017
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“Quantum machine learning”
Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd · 2017
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“A survey of quantum learning theory” (2017)
Srinivasan Arunachalam and Ronald de Wolf · 2017
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“Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets”
Abhinav Kandala, Antonio Mezzacapo, Kristan Temme, Maika Takita, Markus Brink, Jerry M Chow, and Jay M Gambetta · 2017
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“Hybrid quantum-classical hierarchy for mitigation of decoherence and determination of excited states”
Jarrod R McClean, Mollie E Kimchi-Schwartz, Jonathan Carter, and Wibe A De Jong · 2017
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“Unitary 2-designs from random x-and z-diagonal unitaries”
Yoshifumi Nakata, Christoph Hirche, Ciara Morgan, and Andreas Winter · 2017
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“Quantum computational finance: Monte carlo pricing of financial derivatives”
Patrick Rebentrost, Brajesh Gupt, and Thomas R Bromley · 2018
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“Quantum chemistry calculations on a trapped-ion quantum simulator”
Cornelius Hempel, Christine Maier, Jonathan Romero, Jarrod McClean, Thomas Monz, Heng Shen, Petar Jurcevic, Ben P Lanyon, Peter Love, Ryan Babbush, et al · 2018
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“Quantum computing in the nisq era and beyond”
John Preskill · 2018
Cited alongside, same era.
“Quantum machine learning: a classical perspective”
Carlo Ciliberto, Mark Herbster, Alessandro Davide Ialongo, Massimiliano Pontil, Andrea Rocchetto, Simone Severini, and Leonard Wossnig · 2018
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“Machine learning & artificial intelligence in the quantum domain: a review of recent progress”
Vedran Dunjko and Hans J Briegel · 2018
Cited alongside, same era.
“Classification with quantum neural networks on near term processors” (2018)
Edward Farhi and Hartmut Neven · 2018
Cited alongside, same era.
“Witnessing eigenstates for quantum simulation of hamiltonian spectra”
Raffaele Santagati, Jianwei Wang, Antonio A Gentile, Stefano Paesani, Nathan Wiebe, Jarrod R McClean, Sam Morley-Short, Peter J Shadbolt, Damien Bonneau, Joshua W Silverstone, et al · 2018
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“Accelerated variational algorithms for digital quantum simulation of many-body ground states”
Chufan Lyu, Victor Montenegro, and Abolfazl Bayat · 2020
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“Variational quantum eigensolver for frustrated quantum systems”
Alexey Uvarov, Jacob D Biamonte, and Dmitry Yudin · 2020
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“Demonstration of adiabatic variational quantum computing with a superconducting quantum coprocessor”
Ming-Cheng Chen, Ming Gong, Xiaosi Xu, Xiao Yuan, Jian-Wen Wang, Can Wang, Chong Ying, Jin Lin, Yu Xu, Yulin Wu, et al · 2020
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“Quantum approximate optimization of the long-range ising model with a trapped-ion quantum simulator”
Guido Pagano, Aniruddha Bapat, Patrick Becker, Katherine S Collins, Arinjoy De, Paul W Hess, Harvey B Kaplan, Antonis Kyprianidis, Wen Lin Tan, Christopher Baldwin, et al · 2020
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“Measurement reduction in variational quantum algorithms”
Andrew Zhao, Andrew Tranter, William M Kirby, Shu Fay Ung, Akimasa Miyake, and Peter J Love · 2020
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“Quantum algorithms for electronic structure calculations: Particle-hole hamiltonian and optimized wave-function expansions”
Panagiotis Kl Barkoutsos, Jerome F Gonthier, Igor Sokolov, Nikolaj Moll, Gian Salis, Andreas Fuhrer, Marc Ganzhorn, Daniel J Egger, Matthias Troyer, Antonio Mezzacapo, et al · 2018
Cited alongside, same era.
“Constrained variational quantum eigensolver: Quantum computer search engine in the fock space”
Ilya G Ryabinkin, Scott N Genin, and Artur F Izmaylov · 2018
Cited alongside, same era.
“Strategies for quantum computing molecular energies using the unitary coupled cluster ansatz”
Jonathan Romero, Ryan Babbush, Jarrod R McClean, Cornelius Hempel, Peter J Love, and Alán Aspuru-Guzik · 2018
Cited alongside, same era.
“Barren plateaus in quantum neural network training landscapes”
Jarrod R McClean, Sergio Boixo, Vadim N Smelyanskiy, Ryan Babbush, and Hartmut Neven · 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.
“Self-verifying variational quantum simulation of lattice models”
Christian Kokail, Christine Maier, Rick van Bijnen, Tiff Brydges, Manoj K Joshi, Petar Jurcevic, Christine A Muschik, Pietro Silvi, Rainer Blatt, Christian F Roos, et al · 2019
Cited alongside, same era.
“Quantum computing for finance: Overview and prospects”
Roman Orus, Samuel Mugel, and Enrique Lizaso · 2019
Cited alongside, same era.
“Measurement optimization in the variational quantum eigensolver using a minimum clique cover”
Vladyslav Verteletskyi, Tzu-Ching Yen, and Artur F Izmaylov · 2020
Later among the works it cites.
“ o ( n 3 ) o(n^{3}) measurement cost for variational quantum eigensolver on molecular hamiltonians”
Pranav Gokhale, Olivia Angiuli, Yongshan Ding, Kaiwen Gui, Teague Tomesh, Martin Suchara, Margaret Martonosi, and Frederic T. Chong · 2020
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“Quantum natural gradient”
James Stokes, Josh Izaac, Nathan Killoran, and Giuseppe Carleo · 2020
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“Learning to optimize variational quantum circuits to solve combinatorial problems”
Sami Khairy, Ruslan Shaydulin, Lukasz Cincio, Yuri Alexeev, and Prasanna Balaprakash · 2020
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“Symmetry-adapted variational quantum eigensolver”
Kazuhiro Seki, Tomonori Shirakawa, and Seiji Yunoki · 2020
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“Efficient symmetry-preserving state preparation circuits for the variational quantum eigensolver algorithm”
Bryan T. Gard, Linghua Zhu, George S. Barron, Nicholas J. Mayhall, Sophia E. Economou, and Edwin Barnes · 2020
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“Variational quantum algorithms”
Marco Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C Benjamin, Suguru Endo, Keisuke Fujii, Jarrod R McClean, Kosuke Mitarai, Xiao Yuan, Lukasz Cincio, et al · 2021
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“Long-time simulations with high fidelity on quantum hardware” (2021)
Joe Gibbs, Kaitlin Gili, Zoë Holmes, Benjamin Commeau, Andrew Arrasmith, Lukasz Cincio, Patrick J. Coles, and Andrew Sornborger · 2021
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“A variational toolbox for quantum multi-parameter estimation”
Johannes Jakob Meyer, Johannes Borregaard, and Jens Eisert · 2021
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“Fisher information in noisy intermediate-scale quantum applications”
Johannes Jakob Meyer · 2021
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“Adaptive circuit learning for quantum metrology”
Ziqi Ma, Pranav Gokhale, Tian-Xing Zheng, Sisi Zhou, Xiaofei Yu, Liang Jiang, Peter Maurer, and Frederic T. Chong · 2021
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Changsu Cao, Jiaqi Hu, Wengang Zhang, Xusheng Xu, Dechin Chen, Fan Yu, Jun Li, Hanshi Hu, Dingshun Lv, and Man-Hong Yung · 2021
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“Quantum approximate optimization of non-planar graph problems on a planar superconducting processor”
Matthew P Harrigan, Kevin J Sung, Matthew Neeley, Kevin J Satzinger, Frank Arute, Kunal Arya, Juan Atalaya, Joseph C Bardin, Rami Barends, Sergio Boixo, et al · 2021
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“Implementation of measurement reduction for the variational quantum eigensolver”
Alexis Ralli, Peter J Love, Andrew Tranter, and Peter V Coveney · 2021
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“Measurement cost of metric-aware variational quantum algorithms”
Barnaby van Straaten and Bálint Koczor · 2021
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“Large gradients via correlation in random parameterized quantum circuits”
Tyler Volkoff and Patrick J Coles · 2021
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“Reinforcement learning for optimization of variational quantum circuit architectures” (2021)
Mateusz Ostaszewski, Lea M. Trenkwalder, Wojciech Masarczyk, Eleanor Scerri, and Vedran Dunjko · 2021
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“Quantum circuit optimization with deep reinforcement learning” (2021)
Thomas Fösel, Murphy Yuezhen Niu, Florian Marquardt, and Li Li · 2021
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“Preserving symmetries for variational quantum eigensolvers in the presence of noise”
George S Barron, Bryan T Gard, Orien J Altman, Nicholas J Mayhall, Edwin Barnes, and Sophia E Economou · 2021
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“Shallow-circuit variational quantum eigensolver based on symmetry-inspired hilbert space partitioning for quantum chemical calculations”
Feng Zhang, Niladri Gomes, Noah F Berthusen, Peter P Orth, Cai-Zhuang Wang, Kai-Ming Ho, and Yong-Xin Yao · 2021
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“Speeding up learning quantum states through group equivariant convolutional quantum ansätze” (2021)
Han Zheng, Zimu Li, Junyu Liu, Sergii Strelchuk, and Risi Kondor · 2021
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“Penalty methods for a variational quantum eigensolver”
Kohdai Kuroiwa and Yuya O Nakagawa · 2021
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“Noisy intermediate-scale quantum algorithms”
Kishor Bharti, Alba Cervera-Lierta, Thi Ha Kyaw, Tobias Haug, Sumner Alperin-Lea, Abhinav Anand, Matthias Degroote, Hermanni Heimonen, Jakob S. Kottmann, Tim Menke, Wai-Keong Mok, Sukin Sim, Leong-Chuan Kwek, and Alán Aspuru-Guzik · 2022
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“Exploiting symmetry in variational quantum machine learning” (2022)
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