New class of compounds have very low vapor pressures

Magnesium hexahydrate tetrachlorometallates are 50-volume-percent water, have a high melting point and possess a low vapor pressure. These new compounds are relatively noncorrosive, thermally stable, and water soluble but not hygroscopic. They may have potential applications as cooling fluids

Cosmic variance of the galaxy cluster weak lensing signal

Intrinsic variations of the projected density profiles of clusters of galaxies at fixed mass are a source of uncertainty for cluster weak lensing. We present a semi-analytical model to account for this effect, based on a combination of variations in halo concentration, ellipticity and orientation, and the presence of correlated haloes. We calibrate the parameters of our model at the 10 per cent level to match the empirical cosmic variance of cluster profiles at M_200m=10^14...10^15 h^-1 M_sol, z=0.25...0.5 in a cosmological simulation. We show that weak lensing measurements of clusters significantly underestimate mass uncertainties if intrinsic profile variations are ignored, and that our model can be used to provide correct mass likelihoods. Effects on the achievable accuracy of weak lensing cluster mass measurements are particularly strong for the most massive clusters and deep observations (with ~20 per cent uncertainty from cosmic variance alone at M_200m=10^15 h^-1 M_sol and z=0.25), but significant also under typical ground-based conditions. We show that neglecting intrinsic profile variations leads to biases in the mass-observable relation constrained with weak lensing, both for intrinsic scatter and overall scale (the latter at the 15 per cent level). These biases are in excess of the statistical errors of upcoming surveys and can be avoided if the cosmic variance of cluster profiles is accounted for.Comment: 14 pages, 6 figures; submitted to MNRA

Bias-Free Shear Estimation using Artificial Neural Networks

Bias due to imperfect shear calibration is the biggest obstacle when constraints on cosmological parameters are to be extracted from large area weak lensing surveys such as Pan-STARRS-3pi, DES or future satellite missions like Euclid. We demonstrate that bias present in existing shear measurement pipelines (e.g. KSB) can be almost entirely removed by means of neural networks. In this way, bias correction can depend on the properties of the individual galaxy instead on being a single global value. We present a procedure to train neural networks for shear estimation and apply this to subsets of simulated GREAT08 RealNoise data. We also show that circularization of the PSF before measuring the shear reduces the scatter related to the PSF anisotropy correction and thus leads to improved measurements, particularly on low and medium signal-to-noise data. Our results are competitive with the best performers in the GREAT08 competition, especially for the medium and higher signal-to-noise sets. Expressed in terms of the quality parameter defined by GREAT08 we achieve a Q = 40, 140 and 1300 without and 50, 200 and 1300 with circularization for low, medium and high signal-to-noise data sets, respectively.Comment: 19 pages, 8 figures; accepted for publication in Ap

Photometric Redshifts for Next-Generation Surveys

Photometric redshifts are essential in studies of both galaxy evolution and cosmology, as they enable analyses of objects too numerous or faint for spectroscopy. The Rubin Observatory, Euclid, and Roman Space Telescope will soon provide a new generation of imaging surveys with unprecedented area coverage, wavelength range, and depth. To take full advantage of these datasets, further progress in photometric redshift methods is needed. In this review, we focus on the greatest common challenges and prospects for improvement in applications of photo-$z$'s to the next generation of surveys: - Gains in $performance$ -- i.e., the precision of redshift estimates for individual galaxies -- could greatly enhance studies of galaxy evolution and some probes of cosmology. - Improvements in $characterization$ -- i.e., the accurate recovery of redshift $distributions$ of galaxies in the presence of uncertainty on individual redshifts -- are urgently needed for cosmological measurements with next-generation surveys. - To achieve both of these goals, improvements in the scope and treatment of the samples of spectroscopic redshifts which make high-fidelity photo-$z$'s possible will also be needed. For the full potential of the next generation of surveys to be reached, the characterization of redshift distributions will need to improve by roughly an order of magnitude compared to the current state of the art, requiring progress on a wide variety of fronts. We conclude by presenting a speculative evaluation of how photometric redshift methods and the collection of the necessary spectroscopic samples may improve by the time near-future surveys are completed.Comment: Posted with permission from the Annual Review of Astronomy and Astrophysics, Volume 60, copyright 2022 Annual Reviews, http://www.annualreviews.org

Collisional and dynamic evolution of dust from the asteroid belt

The size and spatial distribution of collisional debris from main belt asteroids is modeled over a 10 million year period. The model dust and meteoroid particles spiral toward the Sun under the action of Poynting-Robertson drag and grind down as they collide with a static background of field particles

Characterization and correction of charge-induced pixel shifts in DECam

Interaction of charges in CCDs with the already accumulated charge distribution causes both a flux dependence of the point-spread function (an increase of observed size with flux, also known as the brighter/fatter effect) and pixel-to-pixel correlations of the Poissonian noise in flat fields. We describe these effects in the Dark Energy Camera (DECam) with charge dependent shifts of effective pixel borders, i.e. the Antilogus et al. (2014) model, which we fit to measurements of flat-field Poissonian noise correlations. The latter fall off approximately as a power-law r^-2.5 with pixel separation r, are isotropic except for an asymmetry in the direct neighbors along rows and columns, are stable in time, and are weakly dependent on wavelength. They show variations from chip to chip at the 20% level that correlate with the silicon resistivity. The charge shifts predicted by the model cause biased shape measurements, primarily due to their effect on bright stars, at levels exceeding weak lensing science requirements. We measure the flux dependence of star images and show that the effect can be mitigated by applying the reverse charge shifts at the pixel level during image processing. Differences in stellar size, however, remain significant due to residuals at larger distance from the centroid.Comment: typo and formatting fixes, matches version published in JINS

Geographic Variation in Informed Consent Law: Two Standards for Disclosure of Treatment Risks

We analyzed 714 jury verdicts in informed consent cases tried in 25 states in 1985–2002 to determine whether the applicable standard of care (“patient” vs. “professional” standard) affected the outcome. Verdicts for plaintiffs were significantly more frequent in states with a patient standard than in states with a professional standard (27 percent vs. 17 percent, P = 0.02). This difference in outcomes did not hold for other types of medical malpractice litigation (36 percent vs. 37 percent, P = 0.8). The multivariate odds of a plaintiff’s verdict were more than twice as high in states with a patient standard than in states with a professional standard (odds ratio = 2.15, 95% confidence interval = 1.32–3.50). The law’s expectations of clinicians with respect to risk disclosure appear to vary geographically