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I'm a third-year PhD student at QuICS, Maryland, where I research quantum information and computation. I'm fortunate to be co-advised by Andrew Childs and Carl Miller. Name in Chinese: 王道辰. |
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I'm interested in structures beneath quantum speed-ups, algorithm design, and real-world applications.
Works below listed in order of first appearance online (most recent to least recent). Research award: NSF QISE-NET.
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Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler ICML 2021: slides, poster [QISE-NET: slides] We quantify the quantum speedups achievable for reinforcement learning in terms of calls to a generative model of the underlying Markov decision process. arXiv version in preparation. |
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Daochen Wang*, Xuchen You*, Tongyang Li, Andrew M. Childs AAAI 2021 [GMU: slides] [QTML 2020: slides, talk] [MSR: slides] Identifying the best arm in a quantum multi-armed bandit (I illustrate such an object on the left) can be done quadratically faster by quantum computation. |
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Shalev Ben-David, Andrew M. Childs, András Gilyén, William Kretschmer, Supartha Podder, Daochen Wang† FOCS 2020: short slides, short talk, long talk [APS 2021: slides] [QIP 2021: talk] [MSR: slides] [Property Testing Review] We characterise how a problem's symmetries determine whether quantum computation can substantially speed up its solution; it turns out graph symmetries play the key role. Subsumes our earlier work. |
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in the presence of finite sampling error Ophelia Crawford*, Barnaby van Straaten*, Daochen Wang*, Thomas Parks, Earl Campbell, Stephen Brierley Quantum 2021 [Q-Turn 2020] [QCTIP 2020: talk] The number of measurements needed to estimate the expectation value of an observable can be reduced by a few orders of magnitude via simultaneous measurements. |
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Daochen Wang arXiv 2019 (under review) [Poster] I extract a notion of "p-simulation" from a breakthrough paper in 2018 and then construct explicit classical circuits that can p-simulate any quantum circuit. |
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Oscar Higgott, Daochen Wang, Stephen Brierley Quantum 2019 [>100 citations] [QCTIP 2019] Penalising overlaps between quantum states enables the variational quantum eigensolver to compute excited states at little extra cost. |
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Daochen Wang, Oscar Higgott, Stephen Brierley Physical Review Letters 2019 [Poster] Given greater coherence times, the variational quantum eigensolver can be made faster by making it behave more like quantum phase estimation. |
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Stefan Pabst, Daochen Wang, Robin Santra Physical Review A 2015 Super-short yet super-intense pulses of light can drive electrons up and down between standard bound states of negative energy and a pseudo-bound state of positive energy. |
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Jarrod R. McClean, Kevin J. Sung, Ian D. Kivlichan, Yudong Cao, Chengyu Dai, E. Schuyler Fried, Craig Gidney, Brendan Gimby, Pranav Gokhale, Thomas Häner, Tarini Hardikar, Vojtěch Havlíček, Oscar Higgott, Cupjin Huang, Josh Izaac, Zhang Jiang, Xinle Liu, Sam McArdle, Matthew Neeley, Thomas O'Brien, Bryan O'Gorman, Isil Ozfidan, Maxwell D. Radin, Jhonathan Romero, Nicholas Rubin, Nicolas P. D. Sawaya, Kanav Setia, Sukin Sim, Damian S. Steiger, Mark Steudtner, Qiming Sun, Wei Sun, Daochen Wang, Fang Zhang, Ryan Babbush Quantum Science and Technology 2020 [GitHub] I contributed code that allows you to automatically retrieve molecular geometries from the PubChem database - try: geometry_from_pubchem('water'). |
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Sandesh Kalantre, Eddie Schoute, Daochen Wang Solutions to assignment problems from lecture course CS766/QIC820 Theory of Quantum Information (Fall 2017) at Waterloo by John Watrous. These problems also appear in the book on the left. |
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I used to be president (2014-15) of the Archimedeans, the Cambridge university mathematical society. We held meetings in Michaelmas 2014 and Lent 2015. We also published Eureka 64, click here for an electronic copy. Enjoy! |
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Last updated: 18 July 2021
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