the theory of quantum information processing, especially quantum algorithms.
单位：University of Maryland
研究方向：the theory of quantum information processing, especially quantum algorithms.
Andrew Childs, co-director of QuICS, is a professor in the Department of Computer Science and the Institute for Advanced Computer Studies (UMIACS).
Childs's research interests are in the theory of quantum information processing, especially quantum algorithms.
He has explored the computational power of quantum walk, providing an example of exponential speedup, demonstrating computational universality, and constructing algorithms for problems including search and formula evaluation. Childs has also developed fast quantum algorithms for simulating Hamiltonian dynamics. His other areas of interest include quantum query complexity and quantum algorithms for algebraic problems.
Before coming to UMD, Childs was a DuBridge Postdoctoral Scholar at Caltech from 2004-2007 and a faculty member in Combinatorics & Optimization and the Institute for Quantum Computing at the University of Waterloo from 2007-2014. He is also a Senior Fellow of the Canadian Institute for Advanced Research.
Childs received his doctorate in physics from MIT in 2004.
A. M. Childs, Maslov, D., Nam, Y., Ross, N. J., and Su, Y., “Toward the first quantum simulation with quantum speedup”, 2017.
Y. Nam, Ross, N. J., Su, Y., Childs, A. M., and Maslov, D., “Automated optimization of large quantum circuits with continuous parameters”, 2017.
A. M. Childs and Li, T., “Efficient simulation of sparse Markovian quantum dynamics”, Quantum Information and Computation, vol. 17, pp. 901-947, 2017.
J. Chen, Childs, A. M., and Hung, S. - H., “Quantum algorithm for multivariate polynomial interpolation”, 2017.
D. W. Berry, Childs, A. M., Ostrander, A., and Wang, G., “Quantum algorithm for linear differential equations with exponentially improved dependence on precision”, in to be presented at the 17th Asian Quantum Information Science Conference (AQIS’17), 2017.
A. M. Childs, van Dam, W., Hung, S. - H., and Shparlinski, I. E., “Optimal quantum algorithm for polynomial interpolation”, 43rd International Colloquium on Automata, Languages, and Programming (ICALP 2016), vol. 55, p. 16:1--16:13, 2016.
A. M. Childs and Young, J., “Optimal state discrimination and unstructured search in nonlinear quantum mechanics”, Physical Review A, vol. 93, no. 2, p. 022314, 2016.
A. M. Childs, Gosset, D., and Webb, Z., “Complexity of the XY antiferromagnet at fixed magnetization”, Quantum Information and Computation, vol. 16, no. 1-2, pp. 1-18, 2016.