分类： 天文学 >> 天文学 提交时间： 2023-02-19
Yao-Yuan Mao
Annika H. G. Peter
Susmita Adhikari
Keith Bechtol
Simeon Bird
Simon Birrer
Jonathan Blazek
Jeffrey L. Carlin
Nushkia Chamba
Johann Cohen-Tanugi
Francis-Yan Cyr-Racine
Tansu Daylan
Birendra Dhanasingham
Alex Drlica-Wagner
Cora Dvorkin
Christopher Fassnacht
Eric Gawiser
Maurizio Giannotti
Vera Gluscevic
Alma Gonzalez-Morales
摘要： Establishing that Vera C. Rubin Observatory is a flagship dark matter experiment is an essential pathway toward understanding the physical nature of dark matter. In the past two decades, wide-field astronomical surveys and terrestrial laboratories have jointly created a phase transition in the ecosystem of dark matter models and probes. Going forward, any robust understanding of dark matter requires astronomical observations, which still provide the only empirical evidence for dark matter to date. We have a unique opportunity right now to create a dark matter experiment with Rubin Observatory Legacy Survey of Space and Time (LSST). This experiment will be a coordinated effort to perform dark matter research, and provide a large collaborative team of scientists with the necessary organizational and funding supports. This approach leverages existing investments in Rubin. Studies of dark matter with Rubin LSST will also guide the design of, and confirm the results from, other dark matter experiments. Supporting a collaborative team to carry out a dark matter experiment with Rubin LSST is the key to achieving the dark matter science goals that have already been identified as high priority by the high-energy physics and astronomy communities.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： With the advent of a new generation of cosmological experiments that will provide high-precision measurements of the cosmic microwave background (CMB) and galaxies in the large-scale structure, it is pertinent to examine the potential of performing a joint analysis of multiple cosmological probes. In this paper, we study the cosmological information content contained in the one-loop power spectra and tree bispectra of galaxies cross-correlated with CMB lensing. We use the FFTLog method to compute angular correlations in spherical harmonic space, applicable for wide angles that can be accessed by forthcoming galaxy surveys. We find that adding the bispectra and cross-correlations with CMB lensing offers a significant improvement in parameter constraints, including those on the total neutrino mass, $M_\nu$, and local non-Gaussianity amplitude, $f_{\rm NL}$. In particular, our results suggest that the combination of the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) and CMB-S4 will be able to achieve $\sigma(M_\nu)=42$ meV from galaxy and CMB lensing correlations, and $\sigma(M_\nu)=12$ meV when further combined with the CMB temperature and polarization data, without any prior on the optical depth.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Alex Drlica-Wagner
Chanda Prescod-Weinstein
Hai-Bo Yu
Andrea Albert
Mustafa Amin
Arka Banerjee
Masha Baryakhtar
Keith Bechtol
Simeon Bird
Simon Birrer
Torsten Bringmann
Regina Caputo
Sukanya Chakrabarti
Thomas Y. Chen
Djuna Croon
Francis-Yan Cyr-Racine
William A. Dawson
Cora Dvorkin
Vera Gluscevic
Daniel Gilman
摘要： Cosmological and astrophysical observations currently provide the only robust, positive evidence for dark matter. Cosmic probes of dark matter, which seek to determine the fundamental properties of dark matter through observations of the cosmos, have emerged as a promising means to reveal the nature of dark matter. This report summarizes the current status and future potential of cosmic probes to inform our understanding of the fundamental nature of dark matter in the coming decade.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： Strong gravitational lensing has emerged as a promising approach for probing dark matter models on sub-galactic scales. Recent work has proposed the subhalo effective density slope as a more reliable observable than the commonly used subhalo mass function. The subhalo effective density slope is a measurement independent of assumptions about the underlying density profile and can be inferred for individual subhalos through traditional sampling methods. To go beyond individual subhalo measurements, we leverage recent advances in machine learning and introduce a neural likelihood-ratio estimator to infer an effective density slope for populations of subhalos. We demonstrate that our method is capable of harnessing the statistical power of multiple subhalos (within and across multiple images) to distinguish between characteristics of different subhalo populations. The computational efficiency warranted by the neural likelihood-ratio estimator over traditional sampling enables statistical studies of dark matter perturbers and is particularly useful as we expect an influx of strong lensing systems from upcoming surveys.
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