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Register a new userA Comparison of Cosmological Models Using Time Delay Lenses
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The use of time-delay gravitational lenses to examine the cosmological expansion introduces a new standard ruler with which to test theoretical models. The sample suitable for this kind of work now includes 12 lens systems, which have thus far been used solely for optimizing the parameters of $Lambda$CDM. In this paper, we broaden the base of support for this new, important cosmic probe by using these observations to carry out a one-on-one comparison between {it competing} models. The currently available sample indicates a likelihood of $sim 70-80%$ that the $R_{rm h}=ct$ Universe is the correct cosmology versus $sim 20-30%$ for the standard model. This possibly interesting result reinforces the need to greatly expand the sample of time-delay lenses, e.g., with the successful implementation of the Dark Energy Survey, the VST ATLAS survey, and the Large Synoptic Survey Telescope. In anticipation of a greatly expanded catalog of time-delay lenses identified with these surveys, we have produced synthetic samples to estimate how large they would have to be in order to rule out either model at a $sim 99.7%$ confidence level. We find that if the real cosmology is $Lambda$CDM, a sample of $sim 150$ time-delay lenses would be sufficient to rule out $R_{rm h}=ct$ at this level of accuracy, while $sim 1,000$ time-delay lenses would be required to rule out $Lambda$CDM if the real Universe is instead $R_{rm h}=ct$. This difference in required sample size reflects the greater number of free parameters available to fit the data with $Lambda$CDM.
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The construction of the cosmic distance-duality relation (CDDR) has been widely studied. However, its consistency with various new observables remains a topic of interest. We present a new way to constrain the CDDR $eta(z)$ using different dynamic and geometric properties of strong gravitational lenses (SGL) along with SNe Ia observations. We use a sample of $102$ SGL with the measurement of corresponding velocity dispersion $sigma_0$ and Einstein radius $theta_E$. In addition, we also use a dataset of $12$ two image lensing systems containing the measure of time delay $Delta t$ between source images. Jointly these two datasets give us the angular diameter distance $D_{A_{ol}}$ of the lens. Further, for luminosity distance, we use the $740$ observations from JLA compilation of SNe Ia. To study the combined behavior of these datasets we use a model independent method, Gaussian Process (GP). We also check the efficiency of GP by applying it on simulated datasets, which are generated in a phenomenological way by using realistic cosmological error bars. Finally, we conclude that the combined bounds from the SGL and SNe Ia observation do not favor any deviation of CDDR and are in concordance with the standard value ($eta=1$) within $2sigma$ confidence region, which further strengthens the theoretical acceptance of CDDR.
In this work, we present a homogeneous curve-shifting analysis using the difference-smoothing technique of the publicly available light curves of 24 gravitationally lensed quasars, for which time delays have been reported in the literature. The uncertainty of each measured time delay was estimated using realistic simulated light curves. The recipe for generating such simulated light curves with known time delays in a plausible range around the measured time delay is introduced here. We identified 14 gravitationally lensed quasars that have light curves of sufficiently good quality to enable the measurement of at least one time delay between the images, adjacent to each other in terms of arrival-time order, to a precision of better than 20% (including systematic errors). We modeled the mass distribution of ten of those systems that have known lens redshifts, accurate astrometric data, and sufficiently simple mass distribution, using the publicly available PixeLens code to infer a value of $H_0$ of 68.1 $pm$ 5.9 km s$^{-1}$ Mpc$^{-1}$ (1$sigma$ uncertainty, 8.7% precision) for a spatially flat universe having $Omega_m$ = 0.3 and $Omega_Lambda$ = 0.7. We note here that the lens modeling approach followed in this work is a relatively simple one and does not account for subtle systematics such as those resulting from line-of-sight effects and hence our $H_0$ estimate should be considered as indicative.
This paper presents optical R-band light curves and the time delay of the doubly imaged gravitationally lensed quasar SDSS J1001+5027 at a redshift of 1.838. We have observed this target for more than six years, between March 2005 and July 2011, using the 1.2-m Mercator Telescope, the 1.5-m telescope of the Maidanak Observatory, and the 2-m Himalayan Chandra Telescope. Our resulting light curves are composed of 443 independent epochs, and show strong intrinsic quasar variability, with an amplitude of the order of 0.2 magnitudes. From this data, we measure the time delay using five different methods, all relying on distinct approaches. One of these techniques is a new development presented in this paper. All our time-delay measurements are perfectly compatible. By combining them, we conclude that image A is leading B by 119.3 +/- 3.3 days (1 sigma, 2.8% uncertainty), including systematic errors. It has been shown recently that such accurate time-delay measurements offer a highly complementary probe of dark energy and spatial curvature, as they independently constrain the Hubble constant. The next mandatory step towards using SDSS J1001+5027 in this context will be the measurement of the velocity dispersion of the lensing galaxy, in combination with deep Hubble Space Telescope imaging.
The two properties of the radial mass distribution of a gravitational lens that are well-constrained by Einstein rings are the Einstein radius R_E and xi2 = R_E alpha(R_E)/(1-kappa_E), where alpha(R_E) and kappa_E are the second derivative of the deflection profile and the convergence at R_E. However, if there is a tight mathematical relationship between the radial mass profile and the angular structure, as is true of ellipsoids, an Einstein ring can appear to strongly distinguish radial mass distributions with the same xi2. This problem is beautifully illustrated by the ellipsoidal models in Millon et al. (2019). When using Einstein rings to constrain the radial mass distribution, the angular structure of the models must contain all the degrees of freedom expected in nature (e.g., external shear, different ellipticities for the stars and the dark matter, modest deviations from elliptical structure, modest twists of the axes, modest ellipticity gradients, etc.) that work to decouple the radial and angular structure of the gravity. Models of Einstein rings with too few angular degrees of freedom will lead to strongly biased likelihood distinctions between radial mass distributions and very precise but inaccurate estimates of H0 based on gravitational lens time delays.
COSMOGRAIL is a long-term photometric monitoring of gravitationally lensed QSOs aimed at implementing Refsdals time-delay method to measure cosmological parameters, in particular H0. Given long and well sampled light curves of strongly lensed QSOs, time-delay measurements require numerical techniques whose quality must be assessed. To this end, and also in view of future monitoring programs or surveys such as the LSST, a blind signal processing competition named Time Delay Challenge 1 (TDC1) was held in 2014. The aim of the present paper, which is based on the simulated light curves from the TDC1, is double. First, we test the performance of the time-delay measurement techniques currently used in COSMOGRAIL. Second, we analyse the quantity and quality of the harvest of time delays obtained from the TDC1 simulations. To achieve these goals, we first discover time delays through a careful inspection of the light curves via a dedicated visual interface. Our measurement algorithms can then be applied to the data in an automated way. We show that our techniques have no significant biases, and yield adequate uncertainty estimates resulting in reduced chi2 values between 0.5 and 1.0. We provide estimates for the number and precision of time-delay measurements that can be expected from future time-delay monitoring campaigns as a function of the photometric signal-to-noise ratio and of the true time delay. We make our blind measurements on the TDC1 data publicly available
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