Overcoming real-world obstacles in 21 cm power spectrum estimation: A method demonstration and results from early Murchison Widefield Array data

By J. Dillon, Adrian Liu, Christopher L. Williams, Jacqueline N. Hewitt, Max Tegmark, E. Morgan, A. Levine, Miguel F. Morales, Steven J. Tingay, G. Bernardi and 9 more. 2013

145 citations recorded by the source corpus.

We present techniques for bridging the gap between idealized inverse covariance weighted quadratic estimation of 21 cm power spectra and the real-world challenges presented universally by interferometric observation. By carefully evaluating various estimators and adapting our techniques for large but incomplete data sets, we develop a robust power spectrum estimation framework that preserves the so-called \EoR window" and keeps track of estimator errors and covariances. We apply our method to observations from the 32-tile prototype of the Murchinson Wideeld Array to demonstrate the importance of a judicious analysis technique. Lastly, we apply our method to investigate the dependence of the clean EoR window on frequency|especially the frequency dependence of the so-called \wedge" feature|and establish upper limits on the power spectrum from z = 6:2 to z = 11:7. Our lowest limit is

Subfields: Aerospace Engineering, Astronomy and Astrophysics, Media Technology

View Paper: https://www.semanticscholar.org/paper/8236f8e52150968f1d27a5ba2e04c2242c3029fb

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In Aerospace Engineering

  1. A. Mesinger
  2. B. Greig
  3. Jonathan C. Pober
  4. Randall B. Wayth
  5. Cathryn M. Trott
  6. Steven J. Tingay
  7. Bryna J. Hazelton
  8. J. Aguirre

In Astronomy and Astrophysics

  1. A. Mesinger
  2. B. Greig
  3. C. Carilli
  4. S. Furlanetto
  5. Miguel F. Morales
  6. M. McQuinn
  7. Judd D. Bowman
  8. Jonathan C. Pober

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