Pith. sign in

REVIEW 1 cited by

The Tip of the Red Giant Branch Distance Ladder and the Hubble Constant

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2403.17048 v2 pith:2KZB3WVE submitted 2024-03-25 astro-ph.CO

The Tip of the Red Giant Branch Distance Ladder and the Hubble Constant

classification astro-ph.CO
keywords constanthubbletrgbdistancebranchdevelopmentsgiantgiven
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

While the tip of the red giant branch (TRGB) has been used as a distance indicator since the early 1990's, its application to measure the Hubble Constant as a primary distance indicator occurred only recently. The TRGB is also currently at an interesting crossroads as results from the James Webb Space Telescope (JWST) are beginning to emerge. In this chapter, we provide a review of the TRGB as it is used to measure the Hubble constant. First, we provide an essential review of the physical and observational basis of the TRGB as well as providing a summary for its use for measuring the Hubble Constant. More attention is then given is then given to recent, but still pre-JWST, developments, including new calibrations and developments with algorithms. We also address challenges that arise while measuring a TRGB-based Hubble Constant. We close by looking forward to the exciting prospects from telescopes such as JWST and Gaia.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. A Simulation Based Inference Approach to Modelling of Type Ia Supernova Populations

    astro-ph.CO 2026-07 conditional novelty 6.0

    A simulation-based inference pipeline (Stjörnumál) fits SN Ia dust and intrinsic scatter models to DES 5-year data, enabling fast Bayesian model comparison across seven SN Ia population models.