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On quantum backpropagation, information reuse, and cheating measurement collapse


May 22, 2023
Amira Abbas, Robbie King, Hsin-Yuan Huang, William J. Huggins, Ramis Movassagh, Dar Gilboa, Jarrod R. McClean

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* 29 pages, 2 figures 

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The power and limitations of learning quantum dynamics incoherently


Mar 22, 2023
Sofiene Jerbi, Joe Gibbs, Manuel S. Rudolph, Matthias C. Caro, Patrick J. Coles, Hsin-Yuan Huang, Zoë Holmes

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* 6+9 pages, 7 figures 

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Challenges and Opportunities in Quantum Machine Learning


Mar 16, 2023
M. Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, Patrick J. Coles

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* Nature Computational Science 2, 567-576 (2022) 
* 14 pages, 5 figures 

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Improved machine learning algorithm for predicting ground state properties


Jan 30, 2023
Laura Lewis, Hsin-Yuan Huang, Viet T. Tran, Sebastian Lehner, Richard Kueng, John Preskill

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* 8 pages, 5 figures + 32-page appendix 

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Hardware-efficient learning of quantum many-body states


Dec 12, 2022
Katherine Van Kirk, Jordan Cotler, Hsin-Yuan Huang, Mikhail D. Lukin

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* 7+28 pages, 6 figures 

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Learning to predict arbitrary quantum processes


Oct 27, 2022
Hsin-Yuan Huang, Sitan Chen, John Preskill

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* 10 pages, 1 figure + 38-page appendix; v2: Added a figure and fixed a minor formatting issue 

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The Complexity of NISQ


Oct 13, 2022
Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li

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* 15+37 pages, 3 figures 

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Learning many-body Hamiltonians with Heisenberg-limited scaling


Oct 06, 2022
Hsin-Yuan Huang, Yu Tong, Di Fang, Yuan Su

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* 11 pages, 1 figure + 27-page appendix 

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Foundations for learning from noisy quantum experiments


Apr 28, 2022
Hsin-Yuan Huang, Steven T. Flammia, John Preskill

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* 10 pages, 1 figure + 70 page appendix 

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Dynamical simulation via quantum machine learning with provable generalization


Apr 21, 2022
Joe Gibbs, Zoë Holmes, Matthias C. Caro, Nicholas Ezzell, Hsin-Yuan Huang, Lukasz Cincio, Andrew T. Sornborger, Patrick J. Coles

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* Main text: 5 pages & 3 Figures. Supplementary Information: 12 pages & 2 Figures 

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