Andrew Darmawan
Title
Cited by
Cited by
Year
Restricted Boltzmann machine learning for solving strongly correlated quantum systems
Y Nomura, AS Darmawan, Y Yamaji, M Imada
Physical Review B 96 (20), 205152, 2017
1192017
Tensor-network simulations of the surface code under realistic noise
AS Darmawan, D Poulin
Physical Review Letters 119 (4), 040502, 2017
432017
Measurement-based quantum computation in a two-dimensional phase of matter
AS Darmawan, GK Brennen, SD Bartlett
New Journal of Physics 14 (1), 013023, 2012
422012
Stripe and superconducting order competing in the Hubbard model on a square lattice studied by a combined variational Monte Carlo and tensor network method
AS Darmawan, Y Nomura, Y Yamaji, M Imada
Physical Review B 98 (20), 205132, 2018
242018
Optical spin-1 chain and its use as a quantum-computational wire
AS Darmawan, SD Bartlett
Physical Review A 82 (1), 012328, 2010
222010
Linear-time general decoding algorithm for the surface code
AS Darmawan, D Poulin
Physical Review E 97 (5), 051302, 2018
212018
Graph states as ground states of two-body frustration-free Hamiltonians
AS Darmawan, SD Bartlett
New Journal of Physics 16 (7), 073013, 2014
182014
Tailoring surface codes for highly biased noise
DK Tuckett, AS Darmawan, CT Chubb, S Bravyi, SD Bartlett, ST Flammia
Physical Review X 9 (4), 041031, 2019
152019
Spectral properties for a family of two-dimensional quantum antiferromagnets
AS Darmawan, SD Bartlett
Physical Review B 93 (4), 045129, 2016
62016
Critical noise parameters for fault-tolerant quantum computation
A Darmawan, P Iyer, D Poulin
22016
Quantum computational phases of matter
A Darmawan
University of Sydney, 2014
2014
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