Quantum computers and simulators may offer significant advantages over their classical counterparts, providing insights into quantum many-body systems and possibly solving exponentially hard problems, such as optimization and satisfiability. Here we report the first implementation of a shallow-depth Quantum Approximate Optimization Algorithm (QAOA) using an analog quantum simulator to estimate the ground state energy of the transverse field Ising model with tunable long-range interactions. First, we exhaustively search the variational control parameters to approximate the ground state energy with up to 40 trapped-ion qubits. We then interface the quantum simulator with a classical algorithm to more efficiently find the optimal set of parameters that minimizes the resulting energy of the system. We finally sample from the full probability distribution of the QAOA output with single-shot and efficient measurements of every qubit.

%8 06/06/2019 %G eng %U https://arxiv.org/abs/1906.02700 %0 Journal Article %D 2018 %T Cryogenic Trapped-Ion System for Large Scale Quantum Simulation %A G. Pagano %A P. W. Hess %A H. B. Kaplan %A W. L. Tan %A P. Richerme %A P. Becker %A A. Kyprianidis %A J. Zhang %A E. Birckelbaw %A M. R. Hernandez %A Y. Wu %A C. Monroe %XWe present a cryogenic ion trapping system designed for large scale quantum simulation of spin models. Our apparatus is based on a segmented-blade ion trap enclosed in a 4 K cryostat, which enables us to routinely trap over 100 171Yb+ ions in a linear configuration for hours due to a low background gas pressure from differential cryo-pumping. We characterize the cryogenic vacuum by using trapped ion crystals as a pressure gauge, measuring both inelastic and elastic collision rates with the molecular background gas. We demonstrate nearly equidistant ion spacing for chains of up to 44 ions using anharmonic axial potentials. This reliable production and lifetime enhancement of large linear ion chains will enable quantum simulation of spin models that are intractable with classical computer modelling.

%G eng %U https://arxiv.org/abs/1802.03118 %0 Journal Article %J Nature %D 2017 %T Observation of a Many-Body Dynamical Phase Transition with a 53-Qubit Quantum Simulator %A J. Zhang %A G. Pagano %A P. W. Hess %A A. Kyprianidis %A P. Becker %A H. Kaplan %A Alexey V. Gorshkov %A Z. -X. Gong %A C. Monroe %XA quantum simulator is a restricted class of quantum computer that controls the interactions between quantum bits in a way that can be mapped to certain difficult quantum many-body problems. As more control is exerted over larger numbers of qubits, the simulator can tackle a wider range of problems, with the ultimate limit being a universal quantum computer that can solve general classes of hard problems. We use a quantum simulator composed of up to 53 qubits to study a non-equilibrium phase transition in the transverse field Ising model of magnetism, in a regime where conventional statistical mechanics does not apply. The qubits are represented by trapped ion spins that can be prepared in a variety of initial pure states. We apply a global long-range Ising interaction with controllable strength and range, and measure each individual qubit with near 99% efficiency. This allows the single-shot measurement of arbitrary many-body correlations for the direct probing of the dynamical phase transition and the uncovering of computationally intractable features that rely on the long-range interactions and high connectivity between the qubits.

%B Nature %V 551 %P 601-604 %8 2017/11/29 %G eng %U https://www.nature.com/articles/nature24654 %R 10.1038/nature24654