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Type 2 diabetes (T2D) in youth is a growing healthcare and public health concern. It is costly, and youth suffer from disabling and deadly comorbid conditions at a faster pace than adult onset. However, T2D is preventable. The population of obese youth at greatest risk for T2D is of minority race/ethnicity and socioeconomically disadvantaged background, which creates barriers to health promoting lifestyles. Despite being the first line of prevention efforts for T2D, efficacious behavioral lifestyle interventions are still lacking at the community level. During the summers of 2016 and 2017, a study integrated obesity and diabetes prevention health education into TeenWorks summer employment program at Indy Urban Acres in Indianapolis, Indiana. Results were analyzed using paired sample t-tests. Participants (N = 168) had a mean age of 15.8 ± 0.7 years, 61% female, 13% Hispanic, 80% Black. By the end of the intervention, physical activity (p = 0.000) and prevention knowledge (p = 0.000) were significantly higher. Dietary intake (p = 0.204), self-efficacy (p = 0.58), food insecurity (p = 0.058) and depression screening scores (p = 0.809) were not significantly different. In light of the continuing childhood obesity epidemic and increasing prevalence of prediabetes and T2D in youth, there is a pressing need to understand and reduce barriers to obesity and diabetes prevention in high-risk populations. This study demonstrated the feasibility of integrating obesity and T2D prevention health education into a teen summer employment program.

We present a Verilog-A model accounting for the temporal avalanche buildup and its statistics in Single-Photon Avalanche Diodes (SPADs). This physics-based approach is compared to TCAD mixed-mode analyzing predictions, as well as measurements. The buildup that can be in the order of hundreds picoseconds, affects the statistical pulse width distribution, which is experimentally verified. Furthermore, we address in detail the voltage swing across the device during avalanche and its quenching, studying its impact on power consumption. This model can help a chip designer to optimize circuits for quenching the SPAD photodiode.

We report an algorithm for reconstructing images when the average number of photons recorded per pixel is of order unity, i.e. photon-sparse data. The image optimisation algorithm minimises a cost function incorporating both a Poissonian log-likelihood term based on the deviation of the reconstructed image from the measured data and a regularization-term based upon the sum of the moduli of the second spatial derivatives of the reconstructed image pixel intensities. The balance between these two terms is set by a bootstrapping technique where the target value of the log-likelihood term is deduced from a smoothed version of the original data. When compared to the original data, the processed images exhibit lower residuals with respect to the true object. We use photon-sparse data from two different experimental systems, one system based on a single-photon, avalanche photo-diode array and the other system on a time-gated, intensified camera. However, this same processing technique could most likely be applied to any low photon-number image irrespective of how the data is collected.

We implement Poisson denoising algorithms that are fast enough to allow real-time processing of images produced by a single photon avalanche detector (SPAD) camera. This work has applications in low-light-level surveillance and medical imaging.

We present an image reconstruction algorithm for producing grey-scale images derived from binary photon-sparse data. The algorithm is based upon a likelihood of Poissonian distribution combined with a measure of image smoothness.

Time-bin encoding is a robust form of optical quantum information, especially for transmission in optical fibers. To read out the information, the separation of the time bins must be larger than the detector time resolution, typically on the order of nanoseconds for photon counters. In the present work, we demonstrate a technique using a nonlinear interaction between chirped entangled time-bin photons and shaped laser pulses to perform projective measurements on arbitrary time-bin states with picosecond-scale separations. We demonstrate a tomographically-complete set of time-bin qubit projective measurements and show the fidelity of operations is sufficiently high to violate the CHSH-Bell inequality by more than 6 standard deviations., Comment: 5 pages main article, 5 pages supplementary, 5 main figures, 2 supplementary figures

Using shaped pulses and nonlinear optics, we have experimentally demonstrated coherent measurement of time-bin encoded photons with temporal separations two orders of magnitude smaller than detector resolution by converting timing information to frequency.

Nonlinear optical processes such as parametric down conversion and squeezed light generation are key elements of most quantum protocols, leading to crucial applications such as quantum imaging, sub-shot-noise metrology, and secure communication.

Using an electron multiplying CCD camera we observe both image plane (position) and far field (momentum) correlations between photon pairs produced from spontaneous parametric down-conversion when using a 201 x 201 bi-dimensional array of pixels and a flux of around 0.02 photons/pixel. After background subtraction we characterize the strength of signal and idler correlations in both transverse dimensions by applying entanglement and EPR criteria, showing good agreement with the theoretical predictions. The application of such devices in quantum optics could have a wide range, including quantum computation with spatial degrees of freedom of single photons.

The methods of nonlinear optics lead to important capabilities within the field of quantum information science. Applications such as high-capacity quantum key distribution and enhanced measurement sensitivity are described.