Evolution of entanglement within classical light states

We investigate the evolution of quantum correlations over the lifetime of a multi-photon state. Measurements reveal time-dependent oscillations of the entanglement fidelity for photon pairs created by a single semiconductor quantum dot. The oscillations are attributed to the phase acquired in the intermediate, non-degenerate, exciton-photon state and are consistent with simulations. We conclude that emission of photon pairs by a typical quantum dot with finite polarisation splitting is in fact entangled in a time-evolving state, and not classically correlated as previously regarded

EVA Glove Research Team

The goal of the basic research portion of the extravehicular activity (EVA) glove research program is to gain a greater understanding of the kinematics of the hand, the characteristics of the pressurized EVA glove, and the interaction of the two. Examination of the literature showed that there existed no acceptable, non-invasive method of obtaining accurate biomechanical data on the hand. For this reason a project was initiated to develop magnetic resonance imaging as a tool for biomechanical data acquisition and visualization. Literature reviews also revealed a lack of practical modeling methods for fabric structures, so a basic science research program was also initiated in this area

Giant Stark effect in the emission of single semiconductor quantum dots

We study the quantum-confined Stark effect in single InAs/GaAs quantum dots embedded within a AlGaAs/GaAs/AlGaAs quantum well. By significantly increasing the barrier height we can observe emission from a dot at electric fields of -500 kV/cm, leading to Stark shifts of up to 25 meV. Our results suggest this technique may enable future applications that require self-assembled dots with transitions at the same energy

Climate simulation of the latest Permian: Implications for mass extinction

This report presents the results of climate modeling research which indicates that elevated levels of carbon dioxide in the atmosphere at the end of the Permian period led to climatic conditions inhospitable to both marine and terrestrial life. The Permian-Triassic boundary (about 251 million years ago) was the time of the largest known mass extinction in Earth's history, when greater than ninety percent of all marine species, and approximately seventy percent of all terrestrial species, died out. The model, which used paleogeography and paleotopography correct for the time period, indicated that warm high-latitude surface air temperatures and elevated carbon dioxide levels may have resulted in slowed circulation and stagnant, anoxic conditions in Earth's oceans. The report also suggests that the excess carbon dioxide (and sulfur dioxide) may have originated from volcanic activity associated with eruption of the Siberian Trap flood basalts, which took place at the same time. Educational levels: Undergraduate lower division, Undergraduate upper division, Graduate or professional

Cavity-enhanced radiative emission rate in a single-photon-emitting diode operating at 0.5 GHz

We report the observation of a Purcell enhancement in the electroluminescence decay rate of a single quantum dot, embedded in a microcavity light-emitting-diode structure. Lateral confinement of the optical mode was achieved using an annulus of low-refractive-index aluminium oxide, formed by wet oxidation. The same layer acts as a current aperture, reducing the active area of the device without impeding the electrical properties of the p-i-n diode. This allowed single photon electroluminescence to be demonstrated at repetition rates up to 0.5 GHz.Comment: 11 pages, 4 Figures. To be published in New Journal of Physic

Mortality Rate in Veterans with Multiple Chronic Conditions

Background: Among patients with multiple chronic conditions, there is increasing appreciation of the complex interrelatedness of diseases. Previous studies have focused on the prevalence and economic burden associated with multiple chronic conditions, much less is known about the mortality rate associated with specific combinations of multiple diseases. Objective: Measure the mortality rate in combinations of 11 chronic conditions. Design: Cohort study of veteran health care users. Participants Veterans between 55 and 64 years that used Veterans Health Administration health care services between October 1999 and September 2000. Measurements: Patients were identified as having one or more of the following: COPD, diabetes, hypertension, rheumatoid arthritis, osteoarthritis, asthma, depression, ischemic heart disease, dementia, stroke, and cancer. Mutually exclusive combinations of disease based on these conditions were created, and 5-year mortality rates were determined. Results: There were 741,847 persons included. The number in each group by a count of conditions was: none = 217,944 (29.34%); 1 = 221,111 (29.8%); 2 = 175,228 (23.6%); 3 = 86,447 (11.7%); and 4+ = 41,117 (5.5%). The 5-year mortality rate by the number of conditions was: none = 4.1%; 1 = 6.0%; 2 = 7.8%; 3 = 11.2%; 4+ = 16.7%. Among combinations with the same number of conditions, there was significant variability in mortality rates. Conclusions: Patients with multiple chronic conditions have higher mortality rates. Because there was significant variation in mortality across clusters with the same number of conditions, when studying patients with multiple coexisting illnesses, it is important to understand not only that several conditions may be present but that specific conditions can differentially impact the risk of mortality

Tunable Indistinguishable Photons From Remote Quantum Dots

Single semiconductor quantum dots have been widely studied within devices that can apply an electric field. In the most common system, the low energy offset between the InGaAs quantum dot and the surrounding GaAs material limits the magnitude of field that can be applied to tens of kVcm^-1, before carriers tunnel out of the dot. The Stark shift experienced by the emission line is typically 1 meV. We report that by embedding the quantum dots in a quantum well heterostructure the vertical field that can be applied is increased by over an order of magnitude whilst preserving the narrow linewidths, high internal quantum efficiencies and familiar emission spectra. Individual dots can then be continuously tuned to the same energy allowing for two-photon interference between remote, independent, quantum dots

Histological validation of a type 1 diabetes clinical diagnostic model for classification of diabetes

Aims: Misclassification of diabetes is common due to an overlap in the clinical features of type 1 and type 2 diabetes. Combined diagnostic models incorporating clinical and biomarker information have recently been developed that can aid classification, but they have not been validated using pancreatic pathology. We evaluated a clinical diagnostic model against histologically defined type 1 diabetes. Methods: We classified cases from the Network for Pancreatic Organ donors with Diabetes (nPOD) biobank as type 1 (n = 111) or non-type 1 (n = 42) diabetes using histopathology. Type 1 diabetes was defined by lobular loss of insulin-containing islets along with multiple insulin-deficient islets. We assessed the discriminative performance of previously described type 1 diabetes diagnostic models, based on clinical features (age at diagnosis, BMI) and biomarker data [autoantibodies, type 1 diabetes genetic risk score (T1D-GRS)], and singular features for identifying type 1 diabetes by the area under the curve of the receiver operator characteristic (AUC-ROC). Results: Diagnostic models validated well against histologically defined type 1 diabetes. The model combining clinical features, islet autoantibodies and T1D-GRS was strongly discriminative of type 1 diabetes, and performed better than clinical features alone (AUC-ROC 0.97 vs. 0.95; P = 0.03). Histological classification of type 1 diabetes was concordant with serum C-peptide [median < 17 pmol/l (limit of detection) vs. 1037 pmol/l in non-type 1 diabetes; P < 0.0001]. Conclusions: Our study provides robust histological evidence that a clinical diagnostic model, combining clinical features and biomarkers, could improve diabetes classification. Our study also provides reassurance that a C-peptide-based definition of type 1 diabetes is an appropriate surrogate outcome that can be used in large clinical studies where histological definition is impossible. Parts of this study were presented in abstract form at the Network for Pancreatic Organ Donors Conference, Florida, USA, 19-22 February 2019 and Diabetes UK Professional Conference, Liverpool, UK, 6-8 March 2019.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.Diabetes UK. Grant Number: 16/0005529 NIH. Grant Number: AI‐422388 NIHR. Grant Number: 17/0005624 Diabetes UK. Grant Number: 16/0005480 JDRF Career Development. Grant Number: 5‐CDA‐2014‐221‐A‐N Helmsley Charitable Trust. Grant Number: #2018PG‐T1D053published version, accepted version (12 month embargo), submitted versio

Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High‐Resolution Global Warming Experiment

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection