Building Confidence in Next-Generation 21cm Cosmology: A Forward-Model Approach
Wednesday 05 May 2021 @ 12:00 p.m., David Caro building, Level 2, Hercus Theatre (+Zoom)
Dr Steven Murray, Arizona State University; Email: steven.g.murray[at]asu.edu
21cm cosmology is growing in momentum. New low-frequency radio telescopes able to probe the neutral hydrogen in the high-redshift Universe (z~6-30) come in two flavours: single-antennas that probe the average thermal history of the Universe (such as EDGES, SARAS and REACH), and interferometers that measure the spatial fluctuations of 21cm emission (such as HERA, MWA and SKA).
Both come with an extraordinary challenge: bright foregrounds amplify small spectral “features” in the instrument, obscuring the background signal unless calibrated to one part in 10^5. Accounting for these effects is susceptible to inadvertant removal of part of the signal, which has led to several retractions of published upper-limits over the past decade. Add to this the extremely surprising results from EDGES in 2018, and we must ask: how much can we trust the results of 21cm experiments, and how can we build confidence amongst the community?
In this talk, I will discuss my role in answering
these questions with two current 21cm experiments — EDGES and HERA.
EDGES is working to verify its result from 2018 using new and improved data and improved analysis techniques. I will describe our new effort to forward-model systematics, starting with receiver calibration and simple models for the antenna reflection coefficients, showing the effects of propagating their full correlated uncertainties on the cosmological estimates.
Concerning HERA, I will report on the work of the Validation team (Aguirre et al., 2021), in support of our recent first upper limit (Kern et al., 2021). We produced a sophisticated end-to-end simulation of the full observation, including thermal noise, realistic foregrounds and many instrumental systematics. This simulation was processed with the exact analysis pipeline used for the data. I will discuss our philosophy and findings, with special regards for future improvements.