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A variational eigenvalue solver on a photonic quantum processor
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Cited by:
- Manuel S. Rudolph & Jacob Miller & Danial Motlagh & Jing Chen & Atithi Acharya & Alejandro Perdomo-Ortiz, 2023. "Synergistic pretraining of parametrized quantum circuits via tensor networks," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
- Samson Wang & Enrico Fontana & M. Cerezo & Kunal Sharma & Akira Sone & Lukasz Cincio & Patrick J. Coles, 2021. "Noise-induced barren plateaus in variational quantum algorithms," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
- Eric R. Anschuetz & Bobak T. Kiani, 2022. "Quantum variational algorithms are swamped with traps," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
- F. H. B. Somhorst & R. Meer & M. Correa Anguita & R. Schadow & H. J. Snijders & M. Goede & B. Kassenberg & P. Venderbosch & C. Taballione & J. P. Epping & H. H. Vlekkert & J. Timmerhuis & J. F. F. Bul, 2023. "Quantum simulation of thermodynamics in an integrated quantum photonic processor," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
- Camille Grange & Michael Poss & Eric Bourreau, 2023. "An introduction to variational quantum algorithms for combinatorial optimization problems," 4OR, Springer, vol. 21(3), pages 363-403, September.
- Junyu Liu & Minzhao Liu & Jin-Peng Liu & Ziyu Ye & Yunfei Wang & Yuri Alexeev & Jens Eisert & Liang Jiang, 2024. "Towards provably efficient quantum algorithms for large-scale machine-learning models," Nature Communications, Nature, vol. 15(1), pages 1-6, December.
- Bingzhi Zhang & Junyu Liu & Xiao-Chuan Wu & Liang Jiang & Quntao Zhuang, 2024. "Dynamical transition in controllable quantum neural networks with large depth," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
- Enrico Fontana & Dylan Herman & Shouvanik Chakrabarti & Niraj Kumar & Romina Yalovetzky & Jamie Heredge & Shree Hari Sureshbabu & Marco Pistoia, 2024. "Characterizing barren plateaus in quantum ansätze with the adjoint representation," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
- Xinbiao Wang & Yuxuan Du & Zhuozhuo Tu & Yong Luo & Xiao Yuan & Dacheng Tao, 2024. "Transition role of entangled data in quantum machine learning," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
- Ye, Zi & Yu, Kai & Guo, Gong-De & Lin, Song, 2024. "Quantum self-organizing feature mapping neural network algorithm based on Grover search algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 639(C).
- Kamila Zaman & Alberto Marchisio & Muhammad Kashif & Muhammad Shafique, 2024. "PO-QA: A Framework for Portfolio Optimization using Quantum Algorithms," Papers 2407.19857, arXiv.org.
- He, Zhimin & Deng, Maijie & Zheng, Shenggen & Li, Lvzhou & Situ, Haozhen, 2023. "GSQAS: Graph Self-supervised Quantum Architecture Search," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
- Dylan Herman & Cody Googin & Xiaoyuan Liu & Alexey Galda & Ilya Safro & Yue Sun & Marco Pistoia & Yuri Alexeev, 2022. "A Survey of Quantum Computing for Finance," Papers 2201.02773, arXiv.org, revised Jun 2022.
- Martin Vesely, 2023. "Finding the Optimal Currency Composition of Foreign Exchange Reserves with a Quantum Computer," Working Papers 2023/1, Czech National Bank.
- Huang, Chenyi & Zhang, Shibin & Chang, Yan & Yan, Lily, 2024. "Quantum metric learning with fuzzy-informed learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
- E Schuyler Fried & Nicolas P D Sawaya & Yudong Cao & Ian D Kivlichan & Jhonathan Romero & Alán Aspuru-Guzik, 2018. "qTorch: The quantum tensor contraction handler," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-20, December.
- Ajagekar, Akshay & You, Fengqi, 2022. "Quantum computing and quantum artificial intelligence for renewable and sustainable energy: A emerging prospect towards climate neutrality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
- Wang, Shaoxuan & Shen, Yingtong & Liu, Xinjian & Zhang, Haoying & Wang, Yukun, 2024. "Variational quantum entanglement classification discrimination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
- Michael Ragone & Bojko N. Bakalov & Frédéric Sauvage & Alexander F. Kemper & Carlos Ortiz Marrero & Martín Larocca & M. Cerezo, 2024. "A Lie algebraic theory of barren plateaus for deep parameterized quantum circuits," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
- Antoine Jacquier & Oleksiy Kondratyev & Gordon Lee & Mugad Oumgari, 2023. "Quantum Computing for Financial Mathematics," Papers 2311.06621, arXiv.org.
- Zhao, Xiumei & Li, Yongmei & Li, Jing & Wang, Shasha & Wang, Song & Qin, Sujuan & Gao, Fei, 2024. "Near-term quantum algorithm for solving the MaxCut problem with fewer quantum resources," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 648(C).
- Alexander Gresch & Martin Kliesch, 2025. "Guaranteed efficient energy estimation of quantum many-body Hamiltonians using ShadowGrouping," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
- Daniel J. Egger & Claudio Gambella & Jakub Marecek & Scott McFaddin & Martin Mevissen & Rudy Raymond & Andrea Simonetto & Stefan Woerner & Elena Yndurain, 2020. "Quantum Computing for Finance: State of the Art and Future Prospects," Papers 2006.14510, arXiv.org, revised Jan 2021.
- Abha Naik & Esra Yeniaras & Gerhard Hellstern & Grishma Prasad & Sanjay Kumar Lalta Prasad Vishwakarma, 2023. "From Portfolio Optimization to Quantum Blockchain and Security: A Systematic Review of Quantum Computing in Finance," Papers 2307.01155, arXiv.org.
- Sitan Chen & Jordan Cotler & Hsin-Yuan Huang & Jerry Li, 2023. "The complexity of NISQ," Nature Communications, Nature, vol. 14(1), pages 1-6, December.
- Ke Wan & Yiwen Liu, 2023. "Hybrid Quantum Algorithms integrating QAOA, Penalty Dephasing and Zeno Effect for Solving Binary Optimization Problems with Multiple Constraints," Papers 2305.08056, arXiv.org.
- Sofiene Jerbi & Lukas J. Fiderer & Hendrik Poulsen Nautrup & Jonas M. Kübler & Hans J. Briegel & Vedran Dunjko, 2023. "Quantum machine learning beyond kernel methods," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
- Alexander McCaskey & Eugene Dumitrescu & Mengsu Chen & Dmitry Lyakh & Travis Humble, 2018. "Validating quantum-classical programming models with tensor network simulations," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-19, December.