Daochen Wang

Daochen Wang
[last initial] [first name] at gmail dot com

I'm a fourth-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.

GitHub · LinkedIn

Research

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.

*: equal contribution
^†: alphabetical order, following convention in TCS

1. Computational self-testing of multi-qubit states and measurements
Honghao Fu, Daochen Wang^†, Qi Zhao
arXiv 2022

We show how to efficiently self-test multi-qubit quantum states, include EPR-pairs, and measurements in the computational setting.

	2. Quantum algorithms for reinforcement learning with a generative model Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler ICML 2021: slides, talk, poster [QTML 2021: slides] [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.
	3. Quantum exploration algorithms for multi-armed bandits Daochen Wang, Xuchen You, Tongyang Li, Andrew M. Childs AAAI 2021: talk [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.
	4. Symmetries, graph properties, and quantum speedups 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.
	5. Efficient quantum measurement of Pauli operators 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.
	6. Possibilistic simulation of quantum circuits by classical circuits 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.
	7. Variational quantum computation of excited states Oscar Higgott, Daochen Wang, Stephen Brierley Quantum 2019 [>200 citations] [QCTIP 2019] Penalising overlaps between quantum states enables the variational quantum eigensolver to compute excited states at little extra cost.
	8. Accelerated variational quantum eigensolver Daochen Wang, Oscar Higgott, Stephen Brierley Physical Review Letters 2019 [>100 citations] [Poster] Given greater coherence times, the variational quantum eigensolver can be made faster by making it behave more like quantum phase estimation.
	9. Driving Rabi oscillations at the giant dipole resonance in xenon 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.

Coding

OpenFermion: the electronic structure package for quantum computers
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').

Industry

I have worked with great mentors at great companies during my PhD

Summer 2020: Microsoft Research, mentors: Robin Kothari and Aarthi Sundaram.
Summer 2019: Riverlane, mentor: Steve Brierley.

Teaching

I was teaching assistant for the following class

Spring 2021: Quantum algorithms (CMSC 858Q), instructor: Andrew Childs; my responsibilities included grading homework and holding office hours.

Resources

Solutions to Theory of Quantum Information
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.

Past life

The Archimedeans

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!

Last updated: 1 Feb 2022
From Jon Barron