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Quantum Neuron: an elementary building block for machine learning on quantum computers
Yudong Cao, Gian Giacomo Guerreschi, Alán Aspuru-Guzik
Even the most sophisticated artificial neural networks are built by aggregating substantially identical units called neurons. A neuron receives multiple signals, internally combine…
QVECTOR: an algorithm for device-tailored quantum error correction
Peter D. Johnson, Jonathan Romero, Jonathan Olson +2
Current approaches to fault-tolerant quantum computation will not enable useful quantum computation on near-term devices of 50 to 100 qubits. Leading proposals, such as the color c…
OpenFermion: The Electronic Structure Package for Quantum Computers
Jarrod R. McClean, Kevin J. Sung, Ian D. Kivlichan +32
Quantum simulation of chemistry and materials is predicted to be an important application for both near-term and fault-tolerant quantum devices. However, at present, developing and…
Efficient optimization of perturbative gadgets
Yudong Cao, Sabre Kais
Perturbative gadgets are general techniques for reducing many-body spin interactions to two-body ones using perturbation theory. This allows for potential realization of effective…
qTorch: The Quantum Tensor Contraction Handler
E. Schuyler Fried, Nicolas P. D. Sawaya, Yudong Cao +3
Classical simulation of quantum computation is necessary for studying the numerical behavior of quantum algorithms, as there does not yet exist a large viable quantum computer on w…
Quantum Information and Computation for Chemistry
Jonathan Olson, Yudong Cao, Jonathan Romero +7
The NSF Workshop in Quantum Information and Computation for Chemistry assembled experts from directly quantum-oriented fields such as algorithms, chemistry, machine learning, optic…
Quasi-Reliable Estimates of Effective Sample Size
Youhan Fang, Yudong Cao, Robert D. Skeel
The efficiency of a Markov chain Monte Carlo algorithm might be measured by the cost of generating one independent sample, or equivalently, the total cost divided by the effective…