Type Ia supernova parameter estimation: a comparison of two approaches using current datasets

By using the Sloan Digital Sky Survey (SDSS) first year type Ia supernova (SN Ia) compilation, we compare two different approaches (traditional \chi^2 and complete likelihood) to determine parameter constraints when the magnitude dispersion is to be estimated as well. We consider cosmological constant + Cold Dark Matter (\Lambda CDM) and spatially flat, constant w Dark Energy + Cold Dark Matter (FwCDM) cosmological models and show that, for current data, there is a small difference in the best fit values and $\sim$ 30% difference in confidence contour areas in case the MLCS2k2 light-curve fitter is adopted. For the SALT2 light-curve fitter the differences are less significant ($\lesssim$ 13% difference in areas). In both cases the likelihood approach gives more restrictive constraints. We argue for the importance of using the complete likelihood instead of the \chi^2 approach when dealing with parameters in the expression for the variance.Comment: 16 pages, 5 figures. More complete analysis by including peculiar velocities and correlations among SALT2 parameters. Use of 2D contours instead of 1D intervals for comparison. There can be now a significant difference between the approaches, around 30% in contour area for MLCS2k2 and up to 13% for SALT2. Generic streamlining of text and suppression of section on model selectio

The logic of tact:How decisions happen in situations of crisis

The mass-migration of refugees in the fall 2015 posed an immense humanitarian and logistical challenge: exhausted from their week-long journeys, refugees arrived in Vienna in need of care, shelter, food, medical aid, and onward transport. The refugee crisis was managed by an emerging polycentric and inter-sectoral collective of organizations. In this paper, we investigate how, during such a situation, leaders of these organizations made decisions in concert with each other and hence sustained the collective's capacity to act collectively. We ask: what was the logic of decision-making that orchestrated collective action during the crisis? In answering this question, we make the following contribution: departing from March's logics of consequences and appropriateness as well as Weick's work on sensemaking during crisis, we introduce an alternative logic that informed decision-making: the logic of tact. With this concept we (a) offer a better understanding of how managers make decisions under the condition of bounded rationality and the simultaneous transgression of their institutional identity in situations of crisis; and we (b) show that in decision-making under duress cognition is neither ahead of action, nor is action ahead of cognition; rather, tact explicates the rapid switching between cognition and action, orchestrating decision-making through this interplay

Closing in on Asymmetric Dark Matter I: Model independent limits for interactions with quarks

It is argued that experimental constraints on theories of asymmetric dark matter (ADM) almost certainly require that the DM be part of a richer hidden sector of interacting states of comparable mass or lighter. A general requisite of models of ADM is that the vast majority of the symmetric component of the DM number density must be removed in order to explain the observed relationship $\Omega_B\sim\Omega_{DM}$ via the DM asymmetry. Demanding the efficient annihilation of the symmetric component leads to a tension with experimental limits if the annihilation is directly to Standard Model (SM) degrees of freedom. A comprehensive effective operator analysis of the model independent constraints on ADM from direct detection experiments and LHC monojet searches is presented. Notably, the limits obtained essentially exclude models of ADM with mass 1GeV$\lesssim m_{DM} \lesssim$ 100GeV annihilating to SM quarks via heavy mediator states. This motivates the study of portal interactions between the dark and SM sectors mediated by light states. Resonances and threshold effects involving the new light states are shown to be important for determining the exclusion limits.Comment: 18+6 pages, 18 figures. v2: version accepted for publicatio

Thermal Relic Abundances of Particles with Velocity-Dependent Interactions

We reexamine the evolution of thermal relic particle abundances for the case where the interaction rate depends on the particle velocities. For the case of Sommerfeld enhancement, we show that the standard analytic approximation, modified in a straightforward way, provides an estimate of the relic particle abundance that is accurate to within 10% (in comparison to less than 1% error for the non-Sommerfeld-enhanced case). We examine the effect of kinetic decoupling on relic particle abundances when the interaction rate depends on the velocity. For the case of pure p-wave annihilation, the effect of kinetic decoupling is an increase in the relic abundance, but the effect is negligible when the kinetic decoupling temperature is much less than the chemical decoupling temperature. For the case of Sommerfeld-enhanced s-wave annihilations, after kinetic decoupling occurs, annihilations continue to change the particle abundance down to arbitrarily low temperatures, until either matter domination begins or the Sommerfeld effect cuts off. We derive analytic approximations to give the final relic particle abundances for both of these cases.Comment: 6 pages, 5 figures. Discussion and clarification added. To appear in Phys. Lett. B

Child/Adolescent Anxiety Multimodal Study (CAMS): rationale, design, and methods

<p>Abstract</p> <p>Objective</p> <p>To present the design, methods, and rationale of the Child/Adolescent Anxiety Multimodal Study (CAMS), a recently completed federally-funded, multi-site, randomized placebo-controlled trial that examined the relative efficacy of cognitive-behavior therapy (CBT), sertraline (SRT), and their combination (COMB) against pill placebo (PBO) for the treatment of separation anxiety disorder (SAD), generalized anxiety disorder (GAD) and social phobia (SoP) in children and adolescents.</p> <p>Methods</p> <p>Following a brief review of the acute outcomes of the CAMS trial, as well as the psychosocial and pharmacologic treatment literature for pediatric anxiety disorders, the design and methods of the CAMS trial are described.</p> <p>Results</p> <p>CAMS was a six-year, six-site, randomized controlled trial. Four hundred eighty-eight (N = 488) children and adolescents (ages 7-17 years) with DSM-IV-TR diagnoses of SAD, GAD, or SoP were randomly assigned to one of four treatment conditions: CBT, SRT, COMB, or PBO. Assessments of anxiety symptoms, safety, and functional outcomes, as well as putative mediators and moderators of treatment response were completed in a multi-measure, multi-informant fashion. Manual-based therapies, trained clinicians and independent evaluators were used to ensure treatment and assessment fidelity. A multi-layered administrative structure with representation from all sites facilitated cross-site coordination of the entire trial, study protocols and quality assurance.</p> <p>Conclusions</p> <p>CAMS offers a model for clinical trials methods applicable to psychosocial and psychopharmacological comparative treatment trials by using state-of-the-art methods and rigorous cross-site quality controls. CAMS also provided a large-scale examination of the relative and combined efficacy and safety of the best evidenced-based psychosocial (CBT) and pharmacologic (SSRI) treatments to date for the most commonly occurring pediatric anxiety disorders. Primary and secondary results of CAMS will hold important implications for informing practice-relevant decisions regarding the initial treatment of youth with anxiety disorders.</p> <p>Trial registration</p> <p>ClinicalTrials.gov NCT00052078.</p

Native T1 mapping: inter-study, inter-observer and inter-center reproducibility in hemodialysis patients

Background Native T1 mapping is a cardiovascular magnetic resonance (CMR) technique that associates with markers of fibrosis and strain in hemodialysis patients. The reproducibility of T1 mapping in hemodialysis patients, prone to changes in fluid status, is unknown. Accurate quantification of myocardial fibrosis in this population has prognostic potential. Methods Using 3 Tesla CMR, we report the results of 1) the inter-study, inter-observer and intra-observer reproducibility of native T1 mapping in 10 hemodialysis patients; 2) inter-study reproducibility of left ventricular (LV) structure and function in 10 hemodialysis patients; 3) the agreement of native T1 map and native T1 phantom analyses between two centres in 20 hemodialysis patients; 4) the effect of changes in markers of fluid status on native T1 values in 10 hemodialysis patients. Results Inter-study, inter-observer and intra-observer variability of native T1 mapping were excellent with co-efficients of variation (CoV) of 0.7, 0.3 and 0.4% respectively. Inter-study CoV for LV structure and function were: LV mass = 1%; ejection fraction = 1.1%; LV end-diastolic volume = 5.2%; LV end-systolic volume = 5.6%. Inter-centre variability of analysis techniques were excellent with CoV for basal and mid-native T1 slices between 0.8–1.2%. Phantom analyses showed comparable native T1 times between centres, despite different scanners and acquisition sequences (centre 1: 1192.7 ± 7.5 ms, centre 2: 1205.5 ± 5 ms). For the 10 patients who underwent inter-study testing, change in body weight (Δweight) between scans correlated with change in LV end-diastolic volume (ΔLVEDV) (r = 0.682;P = 0.03) representing altered fluid status between scans. There were no correlations between change in native T1 between scans (ΔT1) and ΔLVEDV or Δweight (P > 0.6). Linear regression confirmed ΔT1 was unaffected by ΔLVEDV or Δweight (P > 0.59). Conclusions Myocardial native T1 is reproducible in HD patients and unaffected by changes in fluid status at the levels we observed. Native T1 mapping is a potential imaging biomarker for myocardial fibrosis in patients with end-stage renal disease

Photometric redshifts and clustering of emission line galaxies selected jointly by DES and eBOSS

We present the results of the first test plates of the extended Baryon Oscillation Spectroscopic Survey. This paper focuses on the emission line galaxies (ELG) population targetted from the Dark Energy Survey (DES) photometry. We analyse the success rate, efficiency, redshift distribution, and clustering properties of the targets. From the 9000 spectroscopic redshifts targetted, 4600 have been selected from the DES photometry. The total success rate for redshifts between 0.6 and 1.2 is 71\% and 68\% respectively for a bright and faint, on average more distant, samples including redshifts measured from a single strong emission line. We find a mean redshift of 0.8 and 0.87, with 15 and 13\% of unknown redshifts respectively for the bright and faint samples. In the redshift range 0.6<z<1.2, for the most secure spectroscopic redshifts, the mean redshift for the bright and faint sample is 0.85 and 0.9 respectively. Star contamination is lower than 2\%. We measure a galaxy bias averaged on scales of 1 and 10~Mpc/h of 1.72 \pm 0.1 for the bright sample and of 1.78 \pm 0.12 for the faint sample. The error on the galaxy bias have been obtained propagating the errors in the correlation function to the fitted parameters. This redshift evolution for the galaxy bias is in agreement with theoretical expectations for a galaxy population with MB-5\log h < -21.0. We note that biasing is derived from the galaxy clustering relative to a model for the mass fluctuations. We investigate the quality of the DES photometric redshifts and find that the outlier fraction can be reduced using a comparison between template fitting and neural network, or using a random forest algorithm

Transfer learning for galaxy morphology from one survey to another

© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio