The detection of the sky-averaged 21-cm signal from the Cosmic Dawn requires antennas whose beam pattern varies minimally with frequency, since beam chromaticity couples the bright, spatially structured Galactic foreground into spurious spectral structure that can obscure the faint cosmological signal. We present a Particle Swarm Optimization (PSO) framework that optimizes a double-ridged transverse-electromagnetic mode (TEM) horn antenna operating from 60 to 85 MHz against a cost function targeting beam chromaticity directly, and benchmark it against both an unoptimized baseline and an established directivity-based cost function [Restrepo, O. A., Lucero, F. I., Chaparro, G. et al. [2023] J. Astron. Instrum. 12, 2350005]. The designs are evaluated by convolving CST-simulated beam patterns with the Global Sky Model to produce antenna-temperature spectra over Local Sidereal Time, and assessed through a mock signal-injection test and a spectral-index analysis. The proposed cost function reduces the directivity smoothness metric by 97% and the beam-solid-angle variation by 52%, and yields the lowest beam-induced foreground residual of the three designs at every foreground order, falling below the depth of an injected 500[Formula: see text]mK signal already at fourth order. In the cold-sky window used for a global-signal integration it is also the least chromatic ([Formula: see text]). We show that the single-power-law spectral index is an incomplete chromaticity metric — its full-day scatter is dominated by Galactic-transit hours excluded from the science integration — and that the foreground-fit residual is the more direct measure of recoverability. These results demonstrate that targeting beam chromaticity directly produces a TEM horn better suited to foreground subtraction than either the baseline or a directivity-based optimization, and provide an observation-driven framework for antenna design in global 21-cm experiments.
Radio and mm-wavelength astronomical instrumentation systems require anti-aliasing and band-defining filters with sharp band edges, high reproducibility, low thermal variability, and low susceptibility to radiofrequency (RF) interference. As large-scale deployments involving thousands of RF channels become more common, there is an increasing need for filter solutions that balance technical performance, scalability, and cost-efficiency. In this work, we present a practical framework for the design and implementation of high order stripline filters tailored for wideband digital readout systems. Emphasis is placed on achieving low unit-to-unit variation ([Formula: see text] on frequency response metrics), steep roll-off ([Formula: see text] [Formula: see text]dB/GHz), high stopband isolation ([Formula: see text] [Formula: see text]dB), minimal in-band ripple ([Formula: see text] [Formula: see text]dB), and environmental stability (thermal drift [Formula: see text]% across 0–115 ∘ C). These performance targets are realized specifically in stripline filters, which rely on an embedded layout structure, material selection, and electromagnetic shielding. While these filters are complex to design, for low production runs, their precision and process uniformity make them ideal for scalable batch fabrication. Case studies from radio astronomy applications validate the proposed approach against demanding real-world requirements, demonstrating that the combination of careful material stack-up and repeatable design methodology support scalable deployment of high-order filters for next-generation radio telescopes.
Instruments targeting 21 cm emission at high redshifts need a spectral dynamic range of better than ten thousand to distinguish the 21 cm background against bright foregrounds. Systematics arising from the antenna pattern are a leading limitation for current instruments and must be addressed in future experiments. Antenna pattern measurements could help reach this precision. Pattern measurements are complicated by the large scale of the instruments and interaction with the local environment. In-situ beam mapping methods have been investigated but the required accuracy remains ill defined. One consideration is whether the calibration source is in the far field. Near field measurements require more elaborate measurement and such an expense must be well motivated. The far field distance is set by the effective size of the antenna. Reflections and interactions with surroundings extend the effective size of the antenna to scales well beyond the physical aperture. Here we give a new, instrument-agnostic method for calculating beam calibration requirements. Using 21cm models and instrument noise we prescribe bounds on the geometric reflection size scales. These scales must be shown via measurement to be below noise. This prescription depends weakly on instrument-specific noise and for interferometers, on the characteristic baseline length, but is otherwise independent of any detailed simulation of antenna or analysis pipeline. Example calculations for HERA-like and EDGES-like instruments find cosmological structures map to reflection scales of 100 m. This far field distance puts ground-based transmitters close to the horizon and drone sources well above typical or legal operating heights. A near-field measurement approach is necessary. Phase-locked systems have been demonstrated with promising results but more work is necessary to validate an antenna pattern at the necessary dynamic range.
The Radio wave Observations at the Lunar Surface of the photoElectron Sheath (ROLSES) instrument is a radio telescope system designed to characterize the radio and plasma wave environment of the nearside lunar surface at frequencies between 2 kHz and 30 MHz. The ROLSES sensor consists of a set of four 2.5 meter radio monopole antennas onboard the Intuitive Machines (IM 1) lander, Odysseus. The antennas were stowed during launch and deployed after landing on the lunar surface using a frangibolt mechanism. The frequency range is well suited to observing radio waves at frequencies below 15 MHz that cannot be observed from Earth due to the ionospheric cutoff. Radio waves from the Sun, the Milky Way galaxy, Jupiter, Earth's auroral region, and ground-based radio transmitters were expected to be present on the lunar surface. Radio data from each of the 4 antennas, after passing through an isolating pre-amp and signal conditioning analog electronics, were digitized to 14 bits at 120 mega samples per second and then digitally processed by a Field Programmable Gate Array (FPGA) that performs onboard spectral analysis via a Fast Fourier Transform (FFT). Time averaged spectral values are then stored and returned. Also telemetered to Earth are raw waveforms (unprocessed time sequence data) that are useful in studying dust impact on ROLSES antennas. ROLSES data are sent to the lander and subsequently downlinked for further processing. ROLSES is part of NASA's Commercial Lunar Payload Services (CLPS) program. Odysseus landed close to the south pole at Malapert A (80 S). This paper describes the design and operations of the ROLSES instrument and presents initial observations made during transit and surface operations in February 2024. We also describe next version of this instrument (ROLSES 2) currently under development.
Recent experiments in cosmology, particularly those aimed at detecting the faint, redshifted, global 21 cm hydrogen line (depth < ~200 mK, z > 7.5), have imposed stringent new requirements on radiometer calibration. In this work, we present a framework for circuit modeling and parameter inference to strengthen these calibration pipelines. This new approach enables in situ characterization of otherwise immeasurable systematics using physically motivated models. A combination of frequentist and Bayesian techniques are employed in a pipeline that supports iterative modeling, robust parameter estimation, and detailed uncertainty quantification. The framework is applied to the REACH telescope, where the precise correction of variations in the radio signal paths arising from component aging or environmental effects is critical. Circuit models of REACH's calibration sources are developed, with the goal of predicting source temperature corrections that are conventionally obtained from laboratory measurements. By fitting the models to measured data using a convolutional cost function, a strong agreement with RMS residuals no worse than -37 dB is obtained. However, Bayesian inference reveals that the resulting temperature corrections can have uncertainties on the order of 1 to 2 K, caused by reflection coefficient degeneracies, measurement noise, and errors in the models. To combat this, posteriors obtained from laboratory measurements are employed as updated priors, reducing correction uncertainties down to 75 mK. Ultimately, the framework provides a means of dynamically accounting for drift in system non-idealities over time, addressing the increasing precision demands of global 21 cm radio astronomy.
