We present a mass map reconstructed from weak gravitational lensing shear measurements over 139 sq. deg from the Dark Energy Survey (DES) Science Verification data. The mass map probes both luminous and dark matter, thus providing a tool for studying
cosmology. We find good agreement between the mass map and the distribution of massive galaxy clusters identified using a red-sequence cluster finder. Potential candidates for super-clusters and voids are identified using these maps. We measure the cross-correlation between the mass map and a magnitude-limited foreground galaxy sample and find a detection at the 5-7 sigma level on a large range of scales. These measurements are consistent with simulated galaxy catalogs based on LCDM N-body simulations, suggesting low systematics uncertainties in the map. We summarize our key findings in this letter; the detailed methodology and tests for systematics are presented in a companion paper.
Weak gravitational lensing allows one to reconstruct the spatial distribution of the projected mass density across the sky. These mass maps provide a powerful tool for studying cosmology as they probe both luminous and dark matter. In this paper, we
present a weak lensing mass map reconstructed from shear measurements in a 139 sq. deg area from the Dark Energy Survey (DES) Science Verification (SV) data. We compare the distribution of mass with that of the foreground distribution of galaxies and clusters. The overdensities in the reconstructed map correlate well with the distribution of optically detected clusters. We demonstrate that candidate superclusters and voids along the line of sight can be identified, exploiting the tight scatter of the cluster photometric redshifts. We cross-correlate the mass map with a foreground magnitude-limited galaxy sample from the same data. Our measurement gives results consistent with mock catalogs from N-body simulations that include the primary sources of statistical uncertainties in the galaxy, lensing, and photo-z catalogs. The statistical significance of the cross-correlation is at the 6.8-sigma level with 20 arcminute smoothing. A major goal of this study is to investigate systematic effects arising from a variety of sources, including PSF and photo-z uncertainties. We make maps derived from twenty variables that may characterize systematics and find the principal components. We find that the contribution of systematics to the lensing mass maps is generally within measurement uncertainties. In this work, we analyze less than 3% of the final area that will be mapped by the DES; the tools and analysis techniques developed in this paper can be applied to forthcoming larger datasets from the survey.
We present a forward-modelling simulation framework designed to model the data products from the Dark Energy Survey (DES). This forward-model process can be thought of as a transfer function -- a mapping from cosmological and astronomical signals to
the final data products used by the scientists. Using output from the cosmological simulations (the Blind Cosmology Challenge), we generate simulated images (the Ultra Fast Image Simulator, Berge et al. 2013) and catalogs representative of the DES data. In this work we simulate the 244 sq. deg coadd images and catalogs in 5 bands for the DES Science Verification (SV) data. The simulation output is compared with the corresponding data to show that major characteristics of the images and catalogs can be captured. We also point out several directions of future improvements. Two practical examples, star/galaxy classification and proximity effects on object detection, are then used to demonstrate how one can use the simulations to address systematics issues in data analysis. With clear understanding of the simplifications in our model, we show that one can use the simulations side-by-side with data products to interpret the measurements. This forward modelling approach is generally applicable for other upcoming and future surveys. It provides a powerful tool for systematics studies which is sufficiently realistic and highly controllable.
We report the pressure dependence of the superconducting transition temperature, $T_c$, in TlNi$_2$Se$_{2-x}$S$_x$ detected via the AC susceptibility method. The pressure-temperature phase diagram constructed for TlNi$_{2}$Se$_{2}$, TlNi$_{2}$S$_{2}$
and TlNi$_{2}$SeS exhibits two unexpected features: (a) a sudden collapse of the superconducting state at moderate pressure for all three compositions and (b) a dome-shaped pressure dependence of $T_c$ for TlNi$_{2}$SeS. These results point to the nontrivial role of S substitution and its subtle interplay with applied pressure, as well as novel superconducting properties of the TlNi$_2$Se$_{2-x}$S$_x$ system.
Future weak lensing surveys potentially hold the highest statistical power for constraining cosmological parameters compared to other cosmological probes. The statistical power of a weak lensing survey is determined by the sky coverage, the inverse o
f the noise in shear measurements, and the galaxy number density. The combination of the latter two factors is often expressed in terms of $n_{rm eff}$ -- the effective number density of galaxies used for weak lensing measurements. In this work, we estimate $n_{rm eff}$ for the Large Synoptic Survey Telescope (LSST) project, the most powerful ground-based lensing survey planned for the next two decades. We investigate how the following factors affect the resulting $n_{rm eff}$ of the survey with detailed simulations: (1) survey time, (2) shear measurement algorithm, (3) algorithm for combining multiple exposures, (4) inclusion of data from multiple filter bands, (5) redshift distribution of the galaxies, and (6) masking and blending. For the first time, we quantify in a general weak lensing analysis pipeline the sensitivity of $n_{rm eff}$ to the above factors. We find that with current weak lensing algorithms, expected distributions of observing parameters, and all lensing data ($r$- and $i$-band, covering 18,000 degree$^{2}$ of sky) for LSST, $n_{rm eff} approx37$ arcmin$^{-2}$ before considering blending and masking, $n_{rm eff} approx31$ arcmin$^{-2}$ when rejecting seriously blended galaxies and $n_{rm eff} approx26$ arcmin$^{-2}$ when considering an additional 15% loss of galaxies due to masking. With future improvements in weak lensing algorithms, these values could be expected to increase by up to 20%. Throughout the paper, we also stress the ways in which $n_{rm eff}$ depends on our ability to understand and control systematic effects in the measurements.
The statistics of peak counts in reconstructed shear maps contain information beyond the power spectrum, and can improve cosmological constraints from measurements of the power spectrum alone if systematic errors can be controlled. We study the effec
t of galaxy shape measurement errors on predicted cosmological constraints from the statistics of shear peak counts with the Large Synoptic Survey Telescope (LSST). We use the LSST image simulator in combination with cosmological N-body simulations to model realistic shear maps for different cosmological models. We include both galaxy shape noise and, for the first time, measurement errors on galaxy shapes. We find that the measurement errors considered have relatively little impact on the constraining power of shear peak counts for LSST.
A main science goal for the Large Synoptic Survey Telescope (LSST) is to measure the cosmic shear signal from weak lensing to extreme accuracy. One difficulty, however, is that with the short exposure time ($simeq$15 seconds) proposed, the spatial va
riation of the Point Spread Function (PSF) shapes may be dominated by the atmosphere, in addition to optics errors. While optics errors mainly cause the PSF to vary on angular scales similar or larger than a single CCD sensor, the atmosphere generates stochastic structures on a wide range of angular scales. It thus becomes a challenge to infer the multi-scale, complex atmospheric PSF patterns by interpolating the sparsely sampled stars in the field. In this paper we present a new method, PSFent, for interpolating the PSF shape parameters, based on reconstructing underlying shape parameter maps with a multi-scale maximum entropy algorithm. We demonstrate, using images from the LSST Photon Simulator, the performance of our approach relative to a 5th-order polynomial fit (representing the current standard) and a simple boxcar smoothing technique. Quantitatively, PSFent predicts more accurate PSF models in all scenarios and the residual PSF errors are spatially less correlated. This improvement in PSF interpolation leads to a factor of 3.5 lower systematic errors in the shear power spectrum on scales smaller than $sim13$, compared to polynomial fitting. We estimate that with PSFent and for stellar densities greater than $simeq1/{rm arcmin}^{2}$, the spurious shear correlation from PSF interpolation, after combining a complete 10-year dataset from LSST, is lower than the corresponding statistical uncertainties on the cosmic shear power spectrum, even under a conservative scenario.
The complete 10-year survey from the Large Synoptic Survey Telescope (LSST) will image $sim$ 20,000 square degrees of sky in six filter bands every few nights, bringing the final survey depth to $rsim27.5$, with over 4 billion well measured galaxies.
To take full advantage of this unprecedented statistical power, the systematic errors associated with weak lensing measurements need to be controlled to a level similar to the statistical errors. This work is the first attempt to quantitatively estimate the absolute level and statistical properties of the systematic errors on weak lensing shear measurements due to the most important physical effects in the LSST system via high fidelity ray-tracing simulations. We identify and isolate the different sources of algorithm-independent, textit{additive} systematic errors on shear measurements for LSST and predict their impact on the final cosmic shear measurements using conventional weak lensing analysis techniques. We find that the main source of the errors comes from an inability to adequately characterise the atmospheric point spread function (PSF) due to its high frequency spatial variation on angular scales smaller than $sim10$ in the single short exposures, which propagates into a spurious shear correlation function at the $10^{-4}$--$10^{-3}$ level on these scales. With the large multi-epoch dataset that will be acquired by LSST, the stochastic errors average out, bringing the final spurious shear correlation function to a level very close to the statistical errors. Our results imply that the cosmological constraints from LSST will not be severely limited by these algorithm-independent, additive systematic effects.
We measure the branching fractions of $B^{0} to J/psi eta^{(}{}{}^{)}$ decays with the complete Belle data sample of $772 times 10^{6}$ $Bbar{B}$ events collected at the $Upsilon(4S)$ resonance with the Belle detector at the KEKB asymmetric-energy $e
^+ e^-$ collider. The results for the branching fractions are: ${cal B}(B^{0} to J/psi eta)=(12.3 pm ^{1.8}_{1.7} pm 0.7) times 10^{-6}$ and ${cal B}(B^{0} to J/psieta) < 7.4 times 10^{-6}$ at 90% confidence level. The $eta-eta$ mixing angle is constrained to be less than $ 42.2^{circ}$ at 90% confidence level.
Photoproduction of $Lambda$(1520) with liquid hydrogen and deuterium targets was examined at photon energies below 2.4 GeV in the SPring-8 LEPS experiment. For the first time, the differential cross sections were measured at low energies and with a d
euterium target. A large asymmetry of the production cross sections from protons and neutrons was observed at backward K$^{+/0}$ angles. This suggests the importance of the contact term, which coexists with t-channel K exchange under gauge invariance. This interpretation was compatible with the differential cross sections, decay asymmetry, and photon beam asymmetry measured in the production from protons at forward K$^+$ angles.
