Dissipation can usually induce detrimental decoherence in a quantum system. However, engineered dissipation can be used to prepare and stabilize coherent quantum many-body states. Here, we show that by engineering dissipators containing photon pair operators, one can stabilize an exotic dark state, which is a condensate of photon pairs with a phase-nematic order. In this system, the usual superfluid order parameter, i.e. single-photon correlation, is absent, while the photon pair correlation exhibits long-range order. Although the dark state is not unique due to multiple parity sectors, we devise an additional type of dissipators to stabilize the dark state in a particular parity sector via a diffusive annihilation process which obeys Glauber dynamics in an Ising model. Furthermore, we propose an implementation of these photon-pair dissipators in circuit-QED architecture.

UR - https://arxiv.org/abs/1904.00016 ER - TY - JOUR T1 - Machine learning assisted readout of trapped-ion qubits JF - J. Phys. B: At. Mol. Opt. Phys. Y1 - 2018 A1 - Alireza Seif A1 - Kevin A. Landsman A1 - Norbert M. Linke A1 - Caroline Figgatt A1 - C. Monroe A1 - Mohammad Hafezi AB -We reduce measurement errors in a quantum computer using machine learning techniques. We exploit a simple yet versatile neural network to classify multi-qubit quantum states, which is trained using experimental data. This flexible approach allows the incorporation of any number of features of the data with minimal modifications to the underlying network architecture. We experimentally illustrate this approach in the readout of trapped-ion qubits using additional spatial and temporal features in the data. Using this neural network classifier, we efficiently treat qubit readout crosstalk, resulting in a 30\% improvement in detection error over the conventional threshold method. Our approach does not depend on the specific details of the system and can be readily generalized to other quantum computing platforms.

VL - 51 UR - https://arxiv.org/abs/1804.07718 U5 - https://doi.org/10.1088/1361-6455/aad62b ER -