Nondeterminstic ultrafast ground state cooling of a mechanical resonator

We present an ultrafast feasible scheme for ground state cooling of a mechanical resonator via repeated random time-interval measurements on an auxiliary flux qubit. We find that the ground state cooling can be achieved with \emph{several} such measurements. The cooling efficiency hardly depends on the time-intervals between any two consecutive measurements. The scheme is also robust against environmental noises.Comment: 4 pages, 3 figure

Josephson dynamics of a spin-orbit coupled Bose-Einstein condensate in a double well potential

We investigate the quantum dynamics of an experimentally realized spin-orbit coupled Bose-Einstein condensate in a double well potential. The spin-orbit coupling can significantly enhance the atomic inter-well tunneling. We find the coexistence of internal and external Josephson effects in the system, which are moreover inherently coupled in a complicated form even in the absence of interatomic interactions. Moreover, we show that the spin-dependent tunneling between two wells can induce a net atomic spin current referred as spin Josephson effects. Such novel spin Josephson effects can be observable for realistically experimental conditions.Comment: 8 page

Harper operators, Fermi curves, and Picard-Fuchs equations

This paper is a continuation of the work on the spectral problem of Harper operator using algebraic geometry. We continue to discuss the local monodromy of algebraic Fermi curves based on Picard-Lefschetz formula. The density of states over approximating components of Fermi curves satisfies a Picard-Fuchs equation. By the property of Landen transformation, the density of states has a Lambert series as the quarter period. A $q$-expansion of the energy level can be derived from a mirror map as in the B-model.Comment: v2, 13 pages, minor changes have been mad

Quantum kernels with squeezed-state encoding for machine learning

Kernel methods are powerful for machine learning, as they can represent data in feature spaces that similarities between samples may be faithfully captured. Recently, it is realized that machine learning enhanced by quantum computing is closely related to kernel methods, where the exponentially large Hilbert space turns to be a feature space more expressive than classical ones. In this paper, we generalize quantum kernel methods by encoding data into continuous-variable quantum states, which can benefit from the infinite-dimensional Hilbert space of continuous variables. Specially, we propose squeezed-state encoding, in which data is encoded as either in the amplitude or the phase. The kernels can be calculated on a quantum computer and then are combined with classical machine learning, e.g. support vector machine, for training and predicting tasks. Their comparisons with other classical kernels are also addressed. Lastly, we discuss physical implementations of squeezed-state encoding for machine learning in quantum platforms such as trapped ions.Comment: 5 pages, 4 figure

Flexible semiparametric joint modeling: an application to estimate individual lung function decline and risk of pulmonary exacerbations in cystic fibrosis.

BACKGROUND: Epidemiologic surveillance of lung function is key to clinical care of individuals with cystic fibrosis, but lung function decline is nonlinear and often impacted by acute respiratory events known as pulmonary exacerbations. Statistical models are needed to simultaneously estimate lung function decline while providing risk estimates for the onset of pulmonary exacerbations, in order to identify relevant predictors of declining lung function and understand how these associations could be used to predict the onset of pulmonary exacerbations. METHODS: Using longitudinal lung function (FEV1) measurements and time-to-event data on pulmonary exacerbations from individuals in the United States Cystic Fibrosis Registry, we implemented a flexible semiparametric joint model consisting of a mixed-effects submodel with regression splines to fit repeated FEV1 measurements and a time-to-event submodel for possibly censored data on pulmonary exacerbations. We contrasted this approach with methods currently used in epidemiological studies and highlight clinical implications. RESULTS: The semiparametric joint model had the best fit of all models examined based on deviance information criterion. Higher starting FEV1 implied more rapid lung function decline in both separate and joint models; however, individualized risk estimates for pulmonary exacerbation differed depending upon model type. Based on shared parameter estimates from the joint model, which accounts for the nonlinear FEV1 trajectory, patients with more positive rates of change were less likely to experience a pulmonary exacerbation (HR per one standard deviation increase in FEV1 rate of change = 0.566, 95% CI 0.516-0.619), and having higher absolute FEV1 also corresponded to lower risk of having a pulmonary exacerbation (HR per one standard deviation increase in FEV1 = 0.856, 95% CI 0.781-0.937). At the population level, both submodels indicated significant effects of birth cohort, socioeconomic status and respiratory infections on FEV1 decline, as well as significant effects of gender, socioeconomic status and birth cohort on pulmonary exacerbation risk. CONCLUSIONS: Through a flexible joint-modeling approach, we provide a means to simultaneously estimate lung function trajectories and the risk of pulmonary exacerbations for individual patients; we demonstrate how this approach offers additional insights into the clinical course of cystic fibrosis that were not possible using conventional approaches

Paleoproterozoic S-type granites in the Helanshan Complex, Khondalite Belt, North China Craton: Implications for rapid sediment recycling during slab break-off

S-type granites, typically derived from the rapid recycling of sedimentary rocks, are sometimes accompanied by contemporary mafic magmatism and granulite metamorphism. However, the geodynamic context for such rock suites is often highly disputed, with various model proposed, including back-arc basin opening, lithospheric delamination, mantle plume and continental rifting. The Paleoproterozoic Khondalite Belt in the North China Craton provides an example of synchronous mafic and felsic magmatism that was accompanied by granulite-facies metamorphic events for which the tectonic affinities of these rocks remains unclear. This study integrates in situ zircon Hf–O isotope analyses, whole-rock geochemistry and Nd isotope results for the earliest two-mica granites (ca. 1.95 Ga) in order to provide constraints on the above issues. The granites are strongly peraluminous (A/CNK value >1.1), and characterized by high zircon δ18O values of 7.3–10.6‰, corresponding to calculated magmatic δ18O values of 9.1–12.3‰, similar to those of typical S-type granites. They have relatively high and homogeneous ɛNd(t) values of −1.1 to +0.9 and highly variable zircon ɛHf(t) values ranging from −1.0 to +8.3. In situ zircon Hf–O isotopic compositions indicate that the S-type granites may contain some mantle or juvenile crustal components in addition to a sediment component. Based on the new results and published data, a slab break-off model is proposed to explain the rapid recycling of sedimentary precursors and the generation of the ca. 1.95 Ga S-type granites