TY - JOUR T1 - Ground-state energy estimation of the water molecule on a trapped ion quantum computer Y1 - 2019 A1 - Yunseong Nam A1 - Jwo-Sy Chen A1 - Neal C. Pisenti A1 - Kenneth Wright A1 - Conor Delaney A1 - Dmitri Maslov A1 - Kenneth R. Brown A1 - Stewart Allen A1 - Jason M. Amini A1 - Joel Apisdorf A1 - Kristin M. Beck A1 - Aleksey Blinov A1 - Vandiver Chaplin A1 - Mika Chmielewski A1 - Coleman Collins A1 - Shantanu Debnath A1 - Andrew M. Ducore A1 - Kai M. Hudek A1 - Matthew Keesan A1 - Sarah M. Kreikemeier A1 - Jonathan Mizrahi A1 - Phil Solomon A1 - Mike Williams A1 - Jaime David Wong-Campos A1 - Christopher Monroe A1 - Jungsang Kim AB -

Quantum computing leverages the quantum resources of superposition and entanglement to efficiently solve computational problems considered intractable for classical computers. Examples include calculating molecular and nuclear structure, simulating strongly-interacting electron systems, and modeling aspects of material function. While substantial theoretical advances have been made in mapping these problems to quantum algorithms, there remains a large gap between the resource requirements for solving such problems and the capabilities of currently available quantum hardware. Bridging this gap will require a co-design approach, where the expression of algorithms is developed in conjunction with the hardware itself to optimize execution. Here, we describe a scalable co-design framework for solving chemistry problems on a trapped ion quantum computer, and apply it to compute the ground-state energy of the water molecule. The robust operation of the trapped ion quantum computer yields energy estimates with errors approaching the chemical accuracy, which is the target threshold necessary for predicting the rates of chemical reaction dynamics.

UR - https://arxiv.org/abs/1902.10171 ER -