Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userTesting PSF Interpolation In Weak Lensing With Real Data
105
0
0.0
(
0
)
Authors
Tianhuan Lu
Ask ChatGPT about the research
No Arabic abstract
Reconstruction of the point spread function (PSF) is a critical process in weak lensing measurement. We develop a real-data based and galaxy-oriented pipeline to compare the performances of various PSF reconstruction schemes. Making use of a large amount of the CFHTLenS data, the performances of three classes of interpolating schemes - polynomial, Kriging, and Shepard - are evaluated. We find that polynomial interpolations with optimal orders and domains perform the best. We quantify the effect of the residual PSF reconstruction error on shear recovery in terms of the multiplicative and additive biases, and their spatial correlations using the shear measurement method of Zhang et al. (2015). We find that the impact of PSF reconstruction uncertainty on the shear-shear correlation can be significantly reduced by cross correlating the shear estimators from different exposures. It takes only 0.2 stars (SNR > 100) per square arcmin on each exposure to reach the best performance of PSF interpolation, a requirement that is generally satisfied in the CFHTlenS data.
rate research
Read More
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 variation 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.
Accurate reconstruction of the spatial distributions of the Point Spread Function (PSF) is crucial for high precision cosmic shear measurements. Nevertheless, current methods are not good at recovering the PSF fluctuations of high spatial frequencies. In general, the residual PSF fluctuations are spatially correlated, therefore can significantly contaminate the correlation functions of the weak lensing signals. We propose a method to correct for this contamination statistically, without any assumptions on the PSF and galaxy morphologies or their spatial distribution. We demonstrate our idea with the data from the W2 field of CFHTLenS.
Weak lensing surveys are emerging as an important tool for the construction of mass selected clusters of galaxies. We evaluate both the efficiency and completeness of a weak lensing selection by combining a dense, complete redshift survey, the Smithsonian Hectospec Lensing Survey (SHELS), with a weak lensing map from the Deep Lens Survey (DLS). SHELS includes 11,692 redshifts for galaxies with R < 20.6 in the four square degree DLS field; the survey is a solid basis for identifying massive clusters of galaxies with redshift z < 0.55. The range of sensitivity of the redshift survey is similar to the range for the DLS convergence map. Only four the twelve convergence peaks with signal-to-noise > 3.5 correspond to clusters of galaxies with M > 1.7 x 10^14 solar masses. Four of the eight massive clusters in SHELS are detected in the weak lensing map yielding a completeness of roughly 50%. We examine the seven known extended cluster x-ray sources in the DLS field: three can be detected in the weak lensing map, three should not be detected without boosting from superposed large-scale structure, and one is mysteriously undetected even though its optical properties suggest that it should produce a detectable lensing signal. Taken together, these results underscore the need for more extensive comparisons among different methods of massive cluster identification.
We generalize ERA method of PSF correction for more realistic situations. The method re-smears the observed galaxy image(galaxy image smeared by PSF) and PSF image by an appropriate function called Re-Smearing Function(RSF) to make new images which have the same ellipticity with the lensed (before smeared by PSF) galaxy image. It has been shown that the method avoids a systematic error arising from an approximation in the usual PSF correction in moment method such as KSB for simple PSF shape. By adopting an idealized PSF we generalize ERA method applicable for arbitrary PSF. This is confirmed with simulated complex PSF shapes. We also consider the effect of pixel noise and found that the effect causes systematic overestimation.
We use a dense redshift survey in the foreground of the Subaru GTO2deg^2 weak lensing field (centered at $alpha_{2000}$ = 16$^h04^m44^s$;$delta_{2000}$ =43^circ11^{prime}24^{primeprime}$) to assess the completeness and comment on the purity of massive halo identification in the weak lensing map. The redshift survey (published here) includes 4541 galaxies; 4405 are new redshifts measured with the Hectospec on the MMT. Among the weak lensing peaks with a signal-to-noise greater that 4.25, 2/3 correspond to individual massive systems; this result is essentially identical to the Geller et al. (2010) test of the Deep Lens Survey field F2. The Subaru map, based on images in substantially better seeing than the DLS, enables detection of less massive halos at fixed redshift as expected. We demonstrate that the procedure adopted by Miyazaki et al. (2007) for removing some contaminated peaks from the weak lensing map improves agreement between the lensing map and the redshift survey in the identification of candidate massive systems.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
