Aspuru-Guzik A.: Quantum algorithm for molecular properties and geometry optimization. J. Chem. Phys. 131, 224102

Nouhaila Innan, Muhammad Al-Zafar Khan, Mohamed Bennai

James Daniel Whitfield, Jacob Biamonte, Alán Aspuru‐Guzik

Over the last century, ingenious physical and mathematical insights paired with rapidly advancing technology have allowed the field of quantum chemistry to advance dramatically. However, efficient methods for the exact simulation of quantum systems on classical computers do not exist. The present paper reports an extension of one of the authors’ previous work [Aspuru-Guzik et al., Science 309 p. 1704, (2005)] where it was shown that the chemical Hamiltonian can be efficiently simulated using a quantum computer. In particular, we report in detail how a set of molecular integrals can be used to create a quantum circuit that allows the energy of a molecular system with fixed nuclear geometry to be extracted using the phase estimation algorithm proposed by Abrams and Lloyd [Phys. Rev. Lett. 83 p. 5165, (1999)]. We extend several known results related to this idea and present numerical examples of the state preparation procedure required in the algorithm. With future quantum devices in mind, we provide a complete example using the Hydrogen molecule, of how a chemical Hamiltonian can be simulated using a quantum computer. Some of the results we present here represent an extension of our recent collaboration appearing in B. P. Lanyon et al. [Nature Chem., advance online publication, doi: 10.1038/nchem.483 (2010)].

Srinivasan S. Iyengar, Debadrita Saha, Anurag Dwivedi +6 more

Roberto D’Agosta, Massimiliano Di Ventra

We comment on a recent paper by Yuen-Zhou et al. [ Phys. Chem. Chem. Phys. 2009, 11, 4509 ] which extends some of the results of Time-Dependent Current Density Functional Theory applied to open quantum systems. Besides pointing out some incorrect statements in the theorems, we show that in the proof of the main result of the paper an arbitrary condition is introduced. Moreover, we argue that, since this condition has not a physical origin, one can find two systems with different vector potentials that lead to the same dynamics of the physical quantities of interest, the current and particle densities.

special to C EN Bec Roldan

Alán Aspuru-Guzik’s nearly 2 decades of research can’t be narrowed down to a single scientific field. But the flurry of ideas coming from his lab fits, if precariously, under a grander theme: expansion. “I’m very interested in exploring life,” he says. “When there are opportunities that expand my horizon, I will take them.” For Aspuru-Guzik, a professor of chemistry and computer science at the University of Toronto, the possibilities of the unknown are what have driven his laboratory to the interfaces of quantum computing, machine learning, and chemistry. Aspuru-Guzik blurs the lines between everything: theoretical and experimental chemistry, art and science, and creativity and stiffness. “For Alán, disciplines are artificial,” says Joel Yuen-Zhou, who received his PhD from Aspuru- Guzik’s lab in 2012 and now serves as an associate professor of chemistry at the University of California San Diego. Aspuru-Guzik’s interests span art, literature, music, and science, which made him

和也 石村, カズヤ イシムラ, Kazuya Ishimura