2012.02777
Cosmic shear cosmology beyond 2-point statistics: A combined peak count and correlation function analysis of DES-Y1
Harnois-Déraps, et al
We constrain cosmological parameters from a joint cosmic shear analysis of peak-counts and the two-point shear correlation function, as measured from the Dark Energy Survey (DES-Y1). We find the structure growth parameter $S_8\equiv \sigma_8\sqrt{\Omega_{\rm m}/0.3} = 0.766^{+0.033}_{-0.038}$, which at 4.8% precision, provides one of the tightest constraints on $S_8$ from the DES-Y1 weak lensing data. In our simulation-based method we determine the expected DES-Y1 peak-count signal for a range of cosmologies sampled in four $w$CDM parameters ($\Omega_{\rm m}$, $\sigma_8$, $h$, $w_0$). We also determine the joint peak-correlation function covariance matrix with over 1000 realisations at our fiducial cosmology. With mock DES-Y1 data we calibrate the impact of photometric redshift and shear calibration uncertainty on the peak-count, marginalising over these uncertainties in our cosmological analysis. Using dedicated training samples we show that our measurements are unaffected by mass resolution limits in the simulation, and that our constraints are robust against uncertainty in the effect of baryon feedback. Accurate modelling for the impact of intrinsic alignments on the tomographic peak-count remains a challenge, currently limiting our exploitation of cross-correlated peak counts between high and low redshift bins. We demonstrate that once calibrated, a fully tomographic joint peak-count and correlation function analysis has the potential to reach a 3% precision on $S_8$ for DES-Y1. Our methodology can be adopted to model any statistic that is sensitive to the non-Gaussian information encoded in the shear field. In order to accelerate the development of these beyond-two-point cosmic shear studies, our simulations are made available to the community, on request.
2012.04006
Identifying candidate optical variables using Gaia Data Release 2
Andrew, et al
Gaia is undertaking a deep synoptic survey of the Galaxy, but photometry from individual epochs has, as of yet, only been released for a minimal number of sources. We show that it is possible to identify variable stars in Gaia Data Release 2 by selecting stars with unexpectedly large photometric uncertainties given their brightness and number of observations. By comparing our results to existing catalogs of variables, we show that information on the amplitude of variability is also implicitly present in the Gaia photometric uncertainties. We present a catalog of about 9.3 million candidate variable stars, and discuss its limitations and prospects for future tests and extensions.
2012.04100
On the effect of magnetospheric shielding on the lunar hydrogen cycle
Tucker, et al
We examine how water is produced globally over the lunar surface as it orbits in/out of the magnetotail. Due to the interaction of the solar wind (SW) with Earth's magnetic field, upstream the magnetic field is compressed down to ~10 Earth radii. However, the diverted stream of SW around Earth's magnetic field results in an extended depleted region of SW protons (positively charged hydrogen) out to 1000's of Earth radii, referred to as the magnetotail. The Moon orbits at a distance of ~40 Earth radii; therefore, upstream it is within the SW, but downstream it is partially shielded while in the magnetotail during full Moon. SW protons penetrate lunar soil particles and some H atoms can chemical react with oxygen to form water-like molecules such as OH/H2O. Most of the H atoms bounce around within grains until finding another hydrogen atom, chemically combine, and then escape the grain as H2 into the thin atmosphere. We developed a model to calculate the global distribution of OH produced in the lunar surface and H2 released to the atmosphere as the Moon orbits in/out of Earth's magnetotail. The model results are in good agreement with available observations.
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