Alán Aspuru-Guzik
University of Toronto
664 Papers
4.7K Citations
Alán Aspuru-Guzik is an academic researcher from University of Toronto. The author has contributed to research in topics: Quantum computer & Quantum. The author has an hindex of 97, co-authored 628 publications. Previous affiliations of Alán Aspuru-Guzik include D-Wave Systems & National Autonomous University of Mexico.
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Papers
Scientific intuition inspired by machine learning generated hypotheses
TL;DR: In this article, the authors apply gradient boosting in decision trees to extract human interpretable insights from big data sets from chemistry and physics, and find new interesting motifs that tell us how to control solubility and energy levels of organic molecules.
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Demonstration of Tunable Three-Body Interactions between Superconducting Qubits.
Tim Menke,William Banner,Thomas R. Bergamaschi,Agustin Di Paolo,Antti Vepsäläinen,S. J. Weber,Roni Winik,A. Melville,Bethany Niedzielski,Danna Rosenberg,Kyle Serniak,Mollie Schwartz,Jonilyn Yoder,Alán Aspuru-Guzik,Simon Gustavsson,Jeffrey Grover,Cyrus F. Hirjibehedin,Andrew J. Kerman,William D. Oliver +18 more
TL;DR: In this article , a superconducting circuit architecture is presented in which a coupling module mediates two-local and three-local interactions between three flux qubits by design, and the system Hamiltonian is estimated via multiqubit pulse sequences that implement Ramsey-type interferometry.
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Spin models and boson sampling
TL;DR: It is proof that boson sampling with particles in M modes is equivalent to short-time evolution with N excitations in an XY model of XY spins, and this mapping opens the door to bosons sampling with quantum simulators or general purpose quantum computers.
Force-field functor theory: classical force-fields which reproduce equilibrium quantum distributions
TL;DR: The existence of a map between the local potential and an effective classical potential which matches the exact quantum equilibrium density and partition function is examined and it is shown that such a map is unique and must exist.
Automatic discovery of chemical reactions using imposed activation
TL;DR: A simple computational approach that automatically and robustly explores chemical reaction pathways from knowledge only of the reactants and their reactive bonds is described and it is shown that these pathways can be obtained by conformational exploration with a chemically activating constraint.