TDCOSMO V: strategies for precise and accurate measurements of the Hubble constant with strong lensing

  title={TDCOSMO V: strategies for precise and accurate measurements of the Hubble constant with strong lensing},
  author={Simon Birrer and Tommaso Treu},
  journal={arXiv: Cosmology and Nongalactic Astrophysics},
  • S. Birrer, T. Treu
  • Published 2020
  • Physics
  • arXiv: Cosmology and Nongalactic Astrophysics
Strong lensing time delays can measure the Hubble constant H$_0$ independent of any other probe. Assuming commonly used forms for the radial mass density profile of the lenses, a 2\% precision has been achieved with 7 Time-Delay Cosmography (TDCOSMO) lenses, in tension with the H$_0$ from the cosmic microwave background. However, without assumptions on the radial mass density profile -- and relying exclusively on stellar kinematics to break the mass-sheet degeneracy -- the precision drops to 8… Expand

Figures and Tables from this paper

Model-independent Estimation of H 0 and Ω K from Strongly Lensed Fast Radio Bursts
  • Shaoxin Zhao, Bin Liu, Zhengxiang Li, He Gao
  • Physics
  • 2021
Model-independent estimation of H 0 and Ω K can provide clues about the origin of the intractable Hubble constant tension and the current cosmic-curvature crisis. Strongly lensed fast radio burstsExpand
Cosmology Intertwined II: The Hubble Constant Tension
The current cosmological probes have provided a fantastic confirmation of the standard $\Lambda$ Cold Dark Matter cosmological model, that has been constrained with unprecedented accuracy. However,Expand
lenstronomy II: A gravitational lensing software ecosystem
Through community engagement and involvement, lenstronomy has become a foundation of an ecosystem of affiliated packages extending the original scope of the software and proving its robustness and applicability at the forefront of the strong gravitational lensing community in an open source and reproducible manner. Expand
Оптические осцилляции активных ядер и сверхвысокое угловое разрешение гравитационно-линзированных квазаров SDSS J1721+8842, SDSS J1433+6007 и SDSS J2145+6345
В работе представлены результаты обнаружения активной переменности и оптических осцилляций общих кривых блеска гравитационно-линзиpованных квазаров SDSS J1721+8842, SDSS J1433+6007 и SDSS J2145+6345Expand
Large-scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant
Being fully automated and efficient, this pipeline is a promising tool for exploring ensemble-level systematics in lens modeling for H 0 inference, and can accurately characterize the posterior probability density functions of model parameters governing the elliptical power-law mass profile in an external shear field. Expand
Improved time-delay lens modelling and H0 inference with transient sources
Strongly lensed explosive transients such as supernovae, gamma-ray bursts, fast radio bursts, and gravitational waves are very promising tools to determine the Hubble constant (H0) in the near futureExpand
In the realm of the Hubble tension—a review of solutions * * In honor of the seminal work by E Hubble [1]
 The simplest ΛCDM model provides a good fit to a large span of cosmological data but harbors large areas of phenomenology and ignorance. With the improvement of the number and the accuracy ofExpand
Line-of-sight effects in strong gravitational lensing
While most strong-gravitational-lensing systems may be roughly modelled by a single massive object between the source and the observer, in the details all the structures near the light pathExpand
Cosmology Intertwined I: Perspectives for the Next Decade
The standard $\Lambda$ Cold Dark Matter cosmological model provides an amazing description of a wide range of astrophysical and astronomical data. However, there are a few big open questions, thatExpand
Hierarchical Inference with Bayesian Neural Networks: An Application to Strong Gravitational Lensing
This work incorporates BNNs with flexible posterior parameterizations into a hierarchical inference framework that allows for the reconstruction of population hyperparameters and removes the bias introduced by the training distribution. Expand