Cosmology from HSC Y1 Weak Lensing with Combined Higher-Order Statistics and Simulation-based Inference
Camila P. Novaes, Leander Thiele, Joaquin Armijo, Sihao Cheng, Jessica A. Cowell, Gabriela A. Marques, Elisa G. M. Ferreira, Masato Shirasaki, Ken Osato, Jia Liu
We present cosmological constraints from weak lensing with the Subaru Hyper Suprime-Cam (HSC) first-year (Y1) data, using a simulation-based inference (SBI) method. % We explore the performance of a set of higher-order statistics (HOS) including the Minkowski functionals, counts of peaks and minima, and the probability distribution function and compare them to the traditional two-point statistics. The HOS, also known as non-Gaussian statistics, can extract additional non-Gaussian information that is inaccessible to the two-point statistics. We use a neural network to compress the summary statistics, followed by an SBI approach to infer the posterior distribution of the cosmological parameters. We apply cuts on angular scales and redshift bins to mitigate the impact of systematic effects. Combining two-point and non-Gaussian statistics, we obtain $S_8 \equiv σ_8 \sqrt{Ω_m/0.3} = 0.804_{-0.040}^{+0.041}$ and $Ω_m = 0.344_{-0.090}^{+0.083}$, similar to that from non-Gaussian statistics alone. These results are consistent with previous HSC analyses and Planck 2018 cosmology. Our constraints from non-Gaussian statistics are $\sim 25\%$ tighter in $S_8$ than two-point statistics, where the main improvement lies in $Ω_m$, with $\sim 40$\% tighter error bar compared to using the angular power spectrum alone ($S_8 = 0.766_{-0.056}^{+0.054}$ and $Ω_m = 0.365_{-0.141}^{+0.148}$). We find that, among the non-Gaussian statistics we studied, the Minkowski functionals are the primary driver for this improvement. Our analyses confirm the SBI as a powerful approach for cosmological constraints, avoiding any assumptions about the functional form of the data's likelihood.
Galaxy-Galaxy Lensing in HSC: Validation Tests and the Impact of Heterogeneous Spectroscopic Training Sets
虽然测光红移（photo-z's）是当前和即将到来的大规模调查的关键成分，高质量的光谱红移目前可用于训练，验证和测试他们是基本上不代表的幅度和颜色。我们通过跟踪来自异质训练样本的对象如何作为幅度和颜色的函数对photo-z预测做出贡献来研究这种偏差的性质和结构，并说明固定颜色下的潜在红移分布可以作为幅度的函数强烈演变。然后，我们测试的鲁棒性的星系-星系透镜信号在120度$^2$的HSC-SSP DR 1数据光谱的完整性和photo-z偏差，并发现它们的影响是次主导的当前的统计不确定性。我们的方法提供了一个框架，以调查光谱的不完整性如何影响在未来的调查，如LSST和WFIRST的照片Z为基础的弱透镜的预测。
Cosmology and Source Redshift Constraints from Galaxy Clustering and Tomographic Weak Lensing with HSC Y3 and SDSS using the Point-Mass Correction Model
RedMaPPer Cluster Properties from Two-Dimensional Lensing Shear Maps in the HSC-SSP Survey
South-Western Institute for Astronomy Research (SWIFAR), Yunnan University（西南天体物理研究所，云南大学）；Yunnan Key Laboratory of Survey Science, Yunnan University（云南省测绘科学重点实验室，云南大学）；Shanghai Astronomical Observatory (SHAO)（上海天文台）；University of Chinese Academy of Sciences（中国科学院大学）
Weak-lensing mass calibration of \emph{Planck} Sunyaev--Zel'dovich clusters with HSC-SSP Year~3
Stanford University（斯坦福大学）；Kavli Institute for Particle Astrophysics and Cosmology, Stanford University（斯坦福大学卡弗里粒子天体物理与宇宙学研究所）；SLAC National Accelerator Laboratory（SLAC国家加速器实验室）；Princeton University（普林斯顿大学）；Nagoya University（名古屋大学）；The Inter-University Centre for Astronomy and Astrophysics（大学间天文与天体物理中心）；The University of Tokyo（东京大学）；Cornell University（康奈尔大学）；University of Pennsylvania（宾夕法尼亚大学）
First application of weak lensing peak steepness statistics to HSC Y1 data: effectively probing halo density profiles
South-Western Institute for Astronomy Research, Yunnan University（云南大学西南天文研究所）；Yunnan Key Laboratory of Survey Science, Yunnan University（云南大学云南省测绘科学重点实验室）；School of Physics and Astronomy, Beijing Normal University（北京师范大学物理与天文学院）；Department of Astronomy, School of Physics, Peking University（北京大学物理学院天文学系）；National Astronomical Observatories, Chinese Academy of Sciences（中国科学院国家天文台）；School of Astronomy and Space Science, University of Chinese Academy of Sciences（中国科学院大学天文学与空间科学学院）；Southwest United Graduate School（西南联合研究生院）
Modelling Galaxy Clustering and Tomographic Galaxy-Galaxy Lensing with HSC Y3 and SDSS using the Point-Mass Correction Model and Redshift Self-Calibration
Simulation-Based Cosmological Mass Calibration of XXL Galaxy Clusters using HSC Weak Lensing
National Yang Ming Chiao Tung University（国立阳明交通大学）；Academia Sinica Institute of Astronomy and Astrophysics (ASIAA)（中央研究院天文及天文物理研究所）；University of Surrey（萨里大学）；University of Geneva（日内瓦大学）；École Polytechnique Fédérale de Lausanne (EPFL)（洛桑联邦理工学院）；National Cheng Kung University（国立成功大学）；INAF - Osservatorio di Astrofisica e Scienza dello Spazio di Bologna（意大利国家天体物理研究所博洛尼亚天文与空间科学观测站）；INFN, Sezione di Bologna（意大利国家核物理研究所博洛尼亚分部）；Universität Bonn（波恩大学）
Environmental dependence on galaxy-halo connections for satellites using HSC weak lensing
Inter-University Centre for Astronomy and Astrophysics（大学间天文学与天体物理中心）；Kavli Institute for the Physics and Mathematics of the Universe (WPI)（宇宙物理学与数学 Kavli 研究所（WPI））
The SRG/eROSITA All-Sky Survey. The Weak-Lensing Mass Calibration and the Stellar Mass-to-Halo Mass Relation from the Hyper Suprime-Cam Subaru Strategic Program
National Cheng Kung University（国立成功大学）；Max Planck Institute for Extraterrestrial Physics（马克斯·普朗克地外物理研究所）；INAF, Osservatorio di Astrofisica e Scienza dello Spazio（意大利国家天体物理研究所空间科学天文台）；Hiroshima University（广岛大学）；Academia Sinica（中央研究院）；Chiba University（千叶大学）；National Yang Ming Chiao Tung University（国立阳明交通大学）
Cosmic Shear constraints from HSC Year 3 with clustering calibration of the tomographic redshift distributions from DESI
Lawrence Berkeley National Laboratory（劳伦斯伯克利国家实验室）；University of California, Berkeley（加州大学伯克利分校）；Institute for Advanced Study（普林斯顿高等研究院）；University of Virginia（弗吉尼亚大学）；University of Pittsburgh（匹兹堡大学）
