English

Methods of Error Estimation for Delay Power Spectra in $21\,\textrm{cm}$ Cosmology

Instrumentation and Methods for Astrophysics 2021-08-11 v2 Cosmology and Nongalactic Astrophysics

Abstract

Precise measurements of the 21 cm power spectrum are crucial for understanding the physical processes of hydrogen reionization. Currently, this probe is being pursued by low-frequency radio interferometer arrays. As these experiments come closer to making a first detection of the signal, error estimation will play an increasingly important role in setting robust measurements. Using the delay power spectrum approach, we have produced a critical examination of different ways that one can estimate error bars on the power spectrum. We do this through a synthesis of analytic work, simulations of toy models, and tests on small amounts of real data. We find that, although computed independently, the different error bar methodologies are in good agreement with each other in the noise-dominated regime of the power spectrum. For our preferred methodology, the predicted probability distribution function is consistent with the empirical noise power distributions from both simulated and real data. This diagnosis is mainly in support of the forthcoming HERA upper limit, and also is expected to be more generally applicable.

Keywords

Cite

@article{arxiv.2103.09941,
  title  = {Methods of Error Estimation for Delay Power Spectra in $21\,\textrm{cm}$ Cosmology},
  author = {Jianrong Tan and Adrian Liu and Nicholas S. Kern and Zara Abdurashidova and James E. Aguirre and Paul Alexander and Zaki S. Ali and Yanga Balfour and Adam P. Beardsley and Gianni Bernardi and Tashalee S. Billings and Judd D. Bowman and Richard F. Bradley and Philip Bull and Jacob Burba and Steven Carey and Christopher L. Carilli and Carina Cheng and David R. DeBoer and Matt Dexter and Eloy de Lera Acedo and Joshua S. Dillon and John Ely and Aaron Ewall-Wice and Nicolas Fagnoni and Randall Fritz and Steve R. Furlanetto and Kingsley Gale-Sides and Brian Glendenning and Deepthi Gorthi and Bradley Greig and Jasper Grobbelaar and Ziyaad Halday and Bryna J. Hazelton and Jacqueline N. Hewitt and Jack Hickish and Daniel C. Jacobs and Austin Julius and Joshua Kerrigan and Piyanat Kittiwisit and Saul A. Kohn and Matthew Kolopanis and Adam Lanman and Paul La Plante and Telalo Lekalake and David MacMahon and Lourence Malan and Cresshim Malgas and Matthys Maree and Zachary E. Martinot and Eunice Matsetela and Andrei Mesinger and Mathakane Molewa and Miguel F. Morales and Tshegofalang Mosiane and Steven G. Murray and Abraham R. Neben and Bojan Nikolic and Chuneeta D. Nunhokee and Aaron R. Parsons and Nipanjana Patra and Samantha Pieterse and Jonathan C. Pober and Nima Razavi-Ghods and Jon Ringuette and James Robnett and Kathryn Rosie and Peter Sims and Saurabh Singh and Craig Smith and Angelo Syce and Nithyanandan Thyagarajan and Peter K. G. Williams and Haoxuan Zheng},
  journal= {arXiv preprint arXiv:2103.09941},
  year   = {2021}
}

Comments

35 Pages, 9 Figures, 4 Tables. Replaced with accepted ApJ version; some clarifying text added in response to referee comments with no changes to results

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