A reanalysis of the luminosities of clusters of galaxies in the EMSS sample with 0.3 < z < 0.6

The X-ray luminosities of the Einstein Extended Medium Sensitivity Survey (EMSS) clusters of galaxies with redshifts 0.3<z<0.6 are remeasured using ROSAT PSPC data. It is found that the new luminosities are on average 1.18 +/- 0.08 times higher than previously measured but that this ratio depends strongly on the X-ray core radii we measure. For the clusters with small core radii, in general we confirm the EMSS luminosities, but for clusters with core radii >250 kpc (the constant value assumed in the EMSS), the new luminosities are 2.2 +/- 0.15 times the previous measurements. The X-ray luminosity function (XLF) at 0.3<z<0.6 is recalculated and is found to be consistent with the local XLF. The constraints on the updated properties of the 0.3<z<0.6 EMSS sample, including a comparison with the number of clusters predicted from local XLFs, indicate that the space density of luminous, massive clusters has either not evolved or has increased by a small factor ~2 since z=0.4. The implications of this result are discussed in terms of constraints on the cosmological parameter Omega_0.Comment: 12 pages, 7 figures. Accepted for publication in MNRA

Examining the reliability and validity of the Clinical Assessment Interview for Negative Symptoms within the Management of Schizophrenia in Clinical Practice (MOSAIC) multisite national study

The current study sought to expand on prior reports of the validity and reliability of the CAINS (CAINS) by examining its performance across diverse non-academic clinical settings as employed by raters not affiliated with the scale's developers and across a longer test-retest follow-up period. The properties of the CAINS were examined within the Management of Schizophrenia in Clinical Practice (MOSAIC) schizophrenia registry. A total of 501 participants with a schizophrenia spectrum diagnosis who were receiving usual care were recruited across 15 national Patient Assessment Centers and evaluated with the CAINS, other negative symptom measures, and assessments of functioning, quality of life and cognition. Temporal stability of negative symptoms was assessed across a 3-month follow-up. Results replicated the two-factor structure of the CAINS reflecting Motivation and Pleasure and expression symptoms. The CAINS scales exhibited high internal consistency and temporal stability. Convergent validity was supported by significant correlations between the CAINS subscales with other negative symptom measures. Additionally, the CAINS was significantly correlated with functioning and quality of life. Discriminant validity was demonstrated by small to moderate associations between the CAINS and positive symptoms, depression, and cognition (and these associations were comparable to those found with other negative symptom scales). Findings suggest that the CAINS is a reliable and valid tool for measuring negative symptoms in schizophrenia across diverse clinical samples and settings

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype