Strong gravitational lens systems with time delays between the multiple
images allow measurements of time-delay distances, which are primarily
sensitive to the Hubble constant that is key to probing dark energy, neutrino
physics, and the spatial curvature of the Universe, as well as discovering new
physics. We present H0LiCOW ($H_0$ Lenses in COSMOGRAIL's Wellspring), a
program that aims to measure $H_0$ with $<3.5\%$ uncertainty from five lens
systems (B1608+656, RXJ1131-1231, HE0435-1223, WFI2033-4723 and HE1104-1805).
We have been acquiring (1) time delays through COSMOGRAIL and Very Large Array
monitoring, (2) high-resolution Hubble Space Telescope imaging for the lens
mass modeling, (3) wide-field imaging and spectroscopy to characterize the lens
environment, and (4) moderate-resolution spectroscopy to obtain the stellar
velocity dispersion of the lenses for mass modeling. In cosmological models
with one-parameter extension to flat $\Lambda$CDM, we expect to measure $H_0$
to $<3.5\%$ in most models, spatial curvature $\Omega_{\rm k}$ to 0.004, $w$ to
0.14, and the effective number of neutrino species to 0.2 (1$\sigma$
uncertainties) when combined with current CMB experiments. These are,
respectively, a factor of $\sim15$, $\sim2$, and $\sim1.5$ tighter than CMB
alone. Our data set will further enable us to study the stellar initial mass
function of the lens galaxies, and the co-evolution of supermassive black holes
and their host galaxies. This program will provide a foundation for extracting
cosmological distances from the hundreds of time-delay lenses that are expected
to be discovered in current and future surveys.

H0LiCOW 计划通过研究重力透镜中的时间延迟，测量哈勃常数以探索暗能量、中微子物理、宇宙空间曲率和发现新的物理现象，并确定宇宙距离，从而提供宇宙模型的众多参数的测量值。

H0LiCOW I. COSMOGRAIL 之泉中的 $H_0$ 透镜：项目概述

H0LiCOW I. $H_0$ Lenses in COSMOGRAIL's Wellspring: Program Overview

We present the results of a search for galaxy substructures in a sample of 11
gravitational lens galaxies from the Sloan Lens ACS Survey. We find no
significant detection of mass clumps, except for a luminous satellite in the
system SDSS J0956+5110. We use these non-detections, in combination with a
previous detection in the system SDSS J0946+1006, to derive constraints on the
substructure mass function in massive early-type host galaxies with an average
redshift z ~ 0.2 and an average velocity dispersion of 270 km/s. We perform a
Bayesian inference on the substructure mass function, within a median region of
about 32 kpc squared around the Einstein radius (~4.2 kpc). We infer a mean
projected substructure mass fraction $f = 0.0076^{+0.0208}_{-0.0052}$ at the 68
percent confidence level and a substructure mass function slope $\alpha$ < 2.93
at the 95 percent confidence level for a uniform prior probability density on
alpha. For a Gaussian prior based on Cold Dark Matter (CDM) simulations, we
infer $f = 0 .0064^{+0.0080}_{-0.0042}$ and a slope of $\alpha$ =
1.90$^{+0.098}_{-0.098}$ at the 68 percent confidence level. Since only one
substructure was detected in the full sample, we have little information on the
mass function slope, which is therefore poorly constrained (i.e. the Bayes
factor shows no positive preference for any of the two models).The inferred
fraction is consistent with the expectations from CDM simulations and with
inference from flux ratio anomalies at the 68 percent confidence level.

研究了 11 个引力透镜星系中的星系亚结构，发现除了系统 SDSS J0956 + 5110 中的一个亮卫星外，没有发现质量块。通过这些非检测结果，结合先前在 SDSS J0946 + 1006 中的检测结果，我们得出了大质量类星体寄主星系的亚结构质量函数的约束条件，并进行贝叶斯推断得出其坡度和平均投影亚结构质量分数。其中，推断出的亚结构分数与 CDM 模拟的期望值相一致。

使用强引力透镜推断 z=0.2 处冷暗物质亚结构质量函数

Inference of the Cold Dark Matter substructure mass function at z=0.2  using strong gravitational lenses

We describe a new method for analyzing gravitational lens images, for the
case where the source light distribution is pixelized. The method is suitable
for high resolution, high S/N data of a multiply-imaged extended source. For a
given mass distribution, we show that the step of inverting the image to obtain
the deconvolved pixelized source light distribution, and the uncertainties, is
a linear one. This means that the only parameters of the non-linear problem are
those required to model the mass distribution. This greatly simplifies the
search for a min.-chi^2 fit to the data and speeds up the inversion. The method
is extended in a straightforward way to include linear regularization. We apply
the method to simulated Einstein ring images and demonstrate the effectiveness
of the inversion for both the unregularized and regularized cases.

本文提出了一种针对像素化光源的引力透镜图像分析新方法，并表明仅需建模质量分布所需的参数即可实现去卷积像素化源光分布的计算，这大大简化了寻找数据最小卡方拟合和加速反演的步骤，并将该方法应用于模拟爱因斯坦环图像中，证明了其在无正则化和有正则化两种情况下的有效性。