Fully-guided polarization-correlated photon pairs at 1560 nm from a type-II SPDC-based source.

The study, reliable generation, and application of spectral and polarization-correlated biphotons is a widely researched area in the field of quantum technology. In this Letter, we report a bright narrowband source of spectral and polarization-correlated orthogonal photon-pairs around the telecom wavelength of 1560 nm from a fiber-pigtailed, type-II quasi-phase-matched, MgO-doped periodically poled lithium niobate (MgO:ppLN) ridge waveguide. We achieved a high spectral brightness of ∼5×10 photon pairs/s/mW/nm with a coincidence-to-accidental ratio (CAR) value of ∼427 and an emission bandwidth of ∼2.

Bright source of narrowband polarization-entangled photons from a thick type-II ppKTP crystal.

We demonstrate a high brightness (∼2.36 × 10 pairs/s/mW) polarization-entangled photon-pair source at 800-nm via spontaneous parametric down-conversion (SPDC) in a 3-cm long type-II ppKTP crystal pumped unidirectionally in a single-pass geometry. A high coincidences-to-accidentals ratio (CAR ∼ 1200) depicted by our source indicates a strong temporal correlation between the generated photon pairs.

Broadband telecom photon pairs from a fiber-integrated PPLN ridge waveguide.

We demonstrate a spectrally correlated photon-pair source at telecom wavelengths (spanning across the S-, C-, and L-bands), based on type-0 spontaneous parametric downconversion (SPDC) in a fiber-coupled Zn-indiffused MgO doped periodically poled lithium niobate (PPLN) ridge waveguide. Modal analysis of the waveguide performed through numerical finite element method (FEM) simulation indicates that device temperature can be used to dramatically vary and control the emission spectrum. Efficient photon-pair generation is measured over a broad wavelength range from ∼1520 - 1580 nm [full width at half maximum (FWHM) > 45 nm] with a coincidence-to-accidental ratio (CAR) as high as ∼668 and spectral brightness ∼2.

Bayesian negative binomial regression model with unobserved covariates for predicting the frequency of north atlantic tropical storms.

Predicting the annual frequency of tropical storms is of interest because it can provide basic information towards improved preparation against these storms. Sea surface temperatures (SSTs) averaged over the hurricane season can predict annual tropical cyclone activity well. But predictions need to be made before the hurricane season when the predictors are not yet observed.

Bayesian variable selection for latent class models.

In this article, we develop a latent class model with class probabilities that depend on subject-specific covariates. One of our major goals is to identify important predictors of latent classes. We consider methodology that allows estimation of latent classes while allowing for variable selection uncertainty.

Obesity and diabetes genetic variants associated with gestational weight gain.

Objective: We sought to determine whether genetic variants associated with diabetes and obesity predict gestational weight gain.

Study Design: A total of 960 participants in the Pregnancy, Infection, and Nutrition cohorts were genotyped for 27 single-nucleotide polymorphisms (SNPs) associated with diabetes and obesity.

Results: Among Caucasian and African American women (n = 960), KCNQ1 risk allele carriage was directly associated with weight gain (P < .

Default Prior Distributions and Efficient Posterior Computation in Bayesian Factor Analysis.

Factor analytic models are widely used in social sciences. These models have also proven useful for sparse modeling of the covariance structure in multidimensional data. Normal prior distributions for factor loadings and inverse gamma prior distributions for residual variances are a popular choice because of their conditionally conjugate form.