MEDEA: A New Model for Emulating Radio Antenna Beam Patterns for 21-cm Cosmology and Antenna Design Studies2024/08/28 by Joshua J. Hibbard, Bang D. Nhan, Hibbard, Joshua J. +5 · 1 citation
Engineering · Physics and Astronomy · #Antenna Design and Optimization #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Physical sciences #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Radio Astronomy Observations and Technology
paper · pdf · doi:10.48550/arxiv.2408.16135
openalex publication_date 2024/08/28 · openalex created_date 2024/09/22 · openalex updated_date 2026/07/28
In 21-cm experimental cosmology, accurate characterization of a radio telescope's antenna beam response is essential to measure the 21-cm signal. Computational electromagnetic (CEM) simulations estimate the antenna beam pattern and frequency response by subjecting the EM model to different dependencies, or beam hyper-parameters, such as soil dielectric constant or orientation with the environment. However, it is computationally expensive to search all possible parameter spaces to optimize the antenna design or accurately represent the beam to the level required for use as a systematic model in 21-cm cosmology. We therefore present MEDEA, an emulator which rapidly and accurately generates farfield radiation patterns over a large hyper-parameter space. MEDEA takes a subset of beams simulated by CEM software, spatially decomposes them into coefficients in a complete, linear basis, and then interpolates them to form new beams at arbitrary hyper-parameters. We test MEDEA on an analytical dipole and two numerical beams motivated by upcoming lunar lander missions, and then employ MEDEA as a model to fit mock radio spectrometer data to extract covariances on the input beam hyper-parameters. We find that the interpolated beams have RMS relative errors of at most 10-2 using 20 input beams or less, and that fits to mock data are able to recover the input beam hyper-parameters when the model and mock derive from the same set of beams. When a systematic bias is introduced into the mock data, extracted beam hyper-parameters exhibit bias, as expected. We propose several future extensions to MEDEA to potentially account for such bias.