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

I am an assistant professor of computer science at the University of British Columbia, where I research quantum computation and information.

Previously, I obtained my PhD from the University of Maryland under advisors Andrew Childs and Carl Miller. Before that, I obtained my BA and MMath from the University of Cambridge.

Name in Chinese: 王道辰.

I'm interested in the structures beneath quantum speed-ups, algorithm design, and real-world applications. Recently, I've also become interested in quantum cryptography. Works below are listed in order of first appearance online.

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

We ground the security of the primary post-quantum digital signature scheme, undergoing standardization by NIST, in the hardness of Module-LWE and Module-SIS.

We prove some special cases of a thirty-year-old conjecture from the analysis of Boolean functions, which has connections to post-selected quantum query complexity.

We prove that quantum algorithms generally work best when simulating quantum dynamics but can sometimes be fast-forwarded when simulating non-quantum dynamics.

We give a simpler protocol for a quantum computer to prove its quantumness to a classical computer and we explicitly tie the protocol's security to that of LWE.

We quantumly speed up divide and conquer in certain settings and apply it to string problems, including longest increasing subsequence and longest common subsequence.

We show how to efficiently self-test the preparation and measurement of multiple EPR pairs assuming LWE cannot be solved quickly by quantum computers. Applications include device-independent quantum key distribution and dimension testing.

We quantify the quantum speedups achievable for reinforcement learning in terms of calls to a generative model of the underlying Markov decision process.

We construct an optimal quantum algorithm for identifying the best arm in a multi-armed bandit that is quadratically faster than any classical algorithm.

We reduce the number of measurements needed to estimate the expectation value of an observable by a few orders of magnitude via simultaneous measurements.

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.

We enable the variational quantum eigensolver to compute excited states at little extra cost by penalising overlaps between quantum states.

We accelerate the variational quantum eigensolver by making it behave more like quantum phase estimation as more coherence time becomes available.

We find that super-short yet super-intense pulses of light can drive Rabi oscillations between bound states of negative energy and a pseudo-bound state of positive energy.

I contributed code that allows you to automatically retrieve molecular geometries from the PubChem database - try: geometry_from_pubchem('water').

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

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

This is my PhD thesis, which I defended in Spring 2023.

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.

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: 31st Jan 2024
From Jon Barron