Two-Loop Self-Energy and Multiple Scattering at Finite Temperature

One and two loop self-energies are worked out explicitly for a heavy scalar field interacting weakly with a light self-interacting scalar field at finite temperature. The ring/daisy diagrams and a set of necklace diagrams can be summed simultaneously. This simple model serves to illustrate the connection between multi-loop self-energy diagrams and multiple scattering in a medium.Comment: 15 pages including 7 figures; v2. with appendix added, accepted by PR

Oscillatory Spin Polarization and Magneto-Optic Kerr Effect in Fe3O4 Thin Films on GaAs(001)

The spin dependent properties of epitaxial Fe3O4 thin films on GaAs(001) are studied by the ferromagnetic proximity polarization (FPP) effect and magneto-optic Kerr effect (MOKE). Both FPP and MOKE show oscillations with respect to Fe3O4 film thickness, and the oscillations are large enough to induce repeated sign reversals. We attribute the oscillatory behavior to spin-polarized quantum well states forming in the Fe3O4 film. Quantum confinement of the t2g states near the Fermi level provides an explanation for the similar thickness dependences of the FPP and MOKE oscillations.Comment: to appear in Phys. Rev. Let

A Spectroscopic Survey of the Fields of 28 Strong Gravitational Lenses: Implications for H0H_0

Strong gravitational lensing provides an independent measurement of the Hubble parameter ($H_0$). One remaining systematic is a bias from the additional mass due to a galaxy group at the lens redshift or along the sightline. We quantify this bias for more than 20 strong lenses that have well-sampled sightline mass distributions, focusing on the convergence $\kappa$ and shear $\gamma$. In 23% of these fields, a lens group contributes a $\ge$1% convergence bias; in 57%, there is a similarly significant line-of-sight group. For the nine time delay lens systems, $H_0$ is overestimated by 11$^{+3}_{-2}$% on average when groups are ignored. In 67% of fields with total $\kappa \ge$ 0.01, line-of-sight groups contribute $\gtrsim 2\times$ more convergence than do lens groups, indicating that the lens group is not the only important mass. Lens environment affects the ratio of four (quad) to two (double) image systems; all seven quads have lens groups while only three of 10 doubles do, and the highest convergences due to lens groups are in quads. We calibrate the $\gamma$-$\kappa$ relation: $\log(\kappa_{\rm{tot}}) = (1.94 \pm 0.34) \log(\gamma_{\rm{tot}}) + (1.31 \pm 0.49)$ with a rms scatter of 0.34 dex. Shear, which, unlike convergence, can be measured directly from lensed images, can be a poor predictor of $\kappa$; for 19% of our fields, $\kappa$ is $\gtrsim 2\gamma$. Thus, accurate cosmology using strong gravitational lenses requires precise measurement and correction for all significant structures in each lens field.Comment: 34 pages, 11 figures, accepted for publication in Ap

Utilization of Mental Health Services by Low-Income Pregnant and Postpartum Women on Medical Assistance

This paper examines mental health service use among publicly insured white and African-American pregnant and postpartum women who live in a metropolitan area. The study examines the extent to which ethnicity, physical health problems, and behavioral health risk factors are associated with the probability of service use during the prenatal- postpartum period. It also analyzes the patterns of service utilization for those women who used mental health services. Medicaid claims and eligibility data, County Reporting System claims and admissions data, and Pennsylvania State Vital Birth Records were integrated using a unique algorithm. Logistic regression was employed to estimate the probability of mental health service use among 3,841 low-income women residing in Philadelphia who were continuously enrolled in Medicaid for 9 months preceding delivery and 6 months postpartum. Analyses were also conducted on the intensity and location of service use, as well as psychiatric diagnosis, during pregnancy and the postpartum period. About 10% of the women used mental health services during the study period. Women were more likely to use services if they were Caucasian, had a number of chronic diseases, had a number of pregnancy complications, and smoked. Among users, the same proportion (ca. 6%) used services during pregnancy and postpartum, with the average number of outpatient visits slightly higher during pregnancy than during the postpartum period. Most outpatient services (86%) were delivered in the specialty sector. Most women who used mental health services (84%) were diagnosed with minor psychiatric disorders including minor depression and anxiety disorders. Women who used services during the postpartum only were more likely to be diagnosed with major depression, whereas women who used services throughout the perinatal period were more likely to be diagnosed with severe mental disorders. Health providers can use information generated in this study to identify women who are likely to have a need for mental health services

A neural circuit model of decision uncertainty and change-of-mind

Decision-making is often accompanied by a degree of confidence on whether a choice is correct. Decision uncertainty, or lack in confidence, may lead to change-of-mind. Studies have identified the behavioural characteristics associated with decision confidence or change-of-mind, and their neural correlates. Although several theoretical accounts have been proposed, there is no neural model that can compute decision uncertainty and explain its effects on change-of-mind. We propose a neuronal circuit model that computes decision uncertainty while accounting for a variety of behavioural and neural data of decision confidence and change-of-mind, including testable model predictions. Our theoretical analysis suggests that change-of-mind occurs due to the presence of a transient uncertainty-induced choice-neutral stable steady state and noisy fluctuation within the neuronal network. Our distributed network model indicates that the neural basis of change-of-mind is more distinctively identified in motor-based neurons. Overall, our model provides a framework that unifies decision confidence and change-of-mind

Novel Mode Selection Schemes for Buffer-Aided Cooperative NOMA System

This paper investigates a cooperative non-orthogonal multiple access (C-NOMA) system, where the NOMA and buffer-aided cooperative transmission modes between the users are integrated. Two novel mode selection schemes are proposed, which adaptively select the NOMA and cooperative modes according to different buffer states and communication environments. These two proposed schemes are termed single-core state (SCS) and dual-core state (DCS) schemes since they correspond to single and dual-core buffer states. These core states are carefully chosen, which ensure not only a sufficient amount of available transmission modes or links but also a small number of stored packets at each buffer. The closed-form expressions of the outage probabilities and average delays of the proposed schemes are derived and verified by simulation results. Asymptotic performance analysis is also performed, revealing that both proposed schemes achieve the full diversity within the minimum required buffer size of two. Analytical and simulation results show that the proposed SCS and DCS schemes ensure favourable outage performance and the lowest delay, respectively

Radio Galaxy Zoo: Cosmological Alignment of Radio Sources

We study the mutual alignment of radio sources within two surveys, FIRST and TGSS. This is done by producing two position angle catalogues containing the preferential directions of respectively $30\,059$ and $11\,674$ extended sources distributed over more than $7\,000$ and $17\,000$ square degrees. The identification of the sources in the FIRST sample was performed in advance by volunteers of the Radio Galaxy Zoo project, while for the TGSS sample it is the result of an automated process presented here. After taking into account systematic effects, marginal evidence of a local alignment on scales smaller than $2.5\deg$ is found in the FIRST sample. The probability of this happening by chance is found to be less than $2$ per cent. Further study suggests that on scales up to $1.5\deg$ the alignment is maximal. For one third of the sources, the Radio Galaxy Zoo volunteers identified an optical counterpart. Assuming a flat $\Lambda$CDM cosmology with $\Omega_m = 0.31, \Omega_\Lambda = 0.69$, we convert the maximum angular scale on which alignment is seen into a physical scale in the range $[19, 38]$ Mpc $h_{70}^{-1}$. This result supports recent evidence reported by Taylor and Jagannathan of radio jet alignment in the $1.4$ deg$^2$ ELAIS N1 field observed with the Giant Metrewave Radio Telescope. The TGSS sample is found to be too sparsely populated to manifest a similar signal

Fast Meta Learning for Adaptive Beamforming

This paper studies the deep learning based adaptive downlink beamforming solution for the signal-to-interference-plus-noise ratio balancing problem. Adaptive beamforming is an important approach to enhance the performance in dynamic wireless environments in which testing channels have different distributions from training channels. We propose an adaptive method to achieve fast adaptation of beamforming based on the principle of meta learning. Specifically, our method first learns an embedding model by training a deep neural network as a transferable feature extractor. In the adaptation stage, it fits a support vector regression model using the extracted features and testing data of the new environment. Simulation results demonstrate that compared to the state of the art meta learning method, our proposed algorithm reduces the complexities in both training and adaptation processes by more than an order of magnitude, while achieving better adaptation performance