Drift scan observations provide the broad sky coverage and instrumental stability needed to measure the Epoch of Reionization (EoR) 21-cm signal. In such observations, the telescope’s pointing centre (PC) moves continuously on the sky. The Tracking Tapered Gridded Estimator (TTGE) combines observations from different PC to estimate $P(k_{\perp}, k_{\parallel})$ the 21-cm power spectrum, centred on a tracking centre (TC) which remains fixed on the sky. The tapering further restricts the sky response to a small angular region around TC, thereby mitigating wide-field foregrounds. Here we consider $154.2\,\mathrm{MHz}$ ($z = 8.2$) Murchison Widefield Array (MWA) drift scan observations. The periodic pattern of flagged channels, present in MWA data, is known to introduce artefacts which pose a challenge for estimating $P(k_{\perp}, k_{\parallel})$. Here we have validated the TTGE using simulated MWA drift scan observations which incorporate the flagged channels same as the data. We demonstrate that the TTGE is able to recover $P(k_{\perp}, k_{\parallel})$ without any artefacts and estimate $P(k)$ within $5 \%$ accuracy over a large $k$-range. We also present preliminary results for a single PC, combining 9 nights of observation $(17 \, \mathrm{min}$ total). We find that $P(k_{\perp}, k_{\parallel})$ exhibits streaks at a fixed interval of $k_{\parallel}=0.29 \, \mathrm{Mpc}^{-1}$, which matches $\Delta \nu_\mathrm{per}=1.28 \, \mathrm{MHz}$ that is the period of the flagged channels. Since the simulations demonstrate that the TTGE is impervious to the flagged channels, the streaks seen for the actual data are possibly caused by some systematic that has the same period as the flagged channels. These streaks are more than 3–4 orders of magnitude smaller than the peak foreground power $\mid P(k_{\perp}, k_{\parallel}) \mid \approx 10^{16} \, \mathrm{mK^2}\, \mathrm{Mpc^3}$ at $k_{\parallel}=0$. The streaks are not as pronounced at larger $k_{\parallel}$, and in some cases they do not appear to extend across the entire $k_{\perp}$ range. The rectangular region $0.05 \leq k_{\perp} \leq 0.16 \, \mathrm{Mpc^{-1}}$ and $0.9 \leq k_{\parallel}\leq 4.6 \, \mathrm{Mpc^{-1}}$ is found to be relatively free of foreground contamination and artefacts, and we have used this to place the $2\unicode{x03C3}$ upper limit $\Delta^2(k) < (1.85\times10^4)^2\, \mathrm{mK^2}$ on the EoR 21-cm mean squared brightness temperature fluctuations at $k=1 \,\mathrm{Mpc}^{-1}$.

Detection of the 21 cm signal from the Epoch of Reionisation (EoR) ($z \sim 6 - 10$) amidst the dominant foregrounds, which are 3–4 orders of magnitude greater than the weak cosmological signal, is a challenging task for the existing 21 cm experiments. The detection is further challenged by the large Field of View (FoV) of the instrument used for observation, as it becomes necessary to excise foregrounds present within the FoV to make a successful detection. In response to the challenges faced, in our previous work, we developed and installed a new instrument – the Central Redundant Array Mega-tile (CRAM) – and integrated it within the MWA Phase II configuration. It is a larger antenna tile configuration ($8\times 8$ dipoles) with a smaller FoV at every frequency under consideration and has multiple sidelobes of reduced response when compared with the existing Murchison Widefield Array (MWA) tiles. In this paper, we aim to demonstrate through power spectrum simulations that using the larger tile, such as the CRAM, can reduce the impact of bright radio foregrounds near the field edge. For the pedagogical approach aimed with this work, we developed a power spectrum pipeline to estimate the cylindrically averaged power spectrum. The power spectrum is estimated for MWA-MWA baselines and CRAM-MWA baselines using analytical beams, simulated diffuse sky maps and a semi-numerical 21 cm signal. Employing a drift scanning strategy, we estimate 1D and 2D power spectra for a series of two-minute observations spanning 24 hrs using the diffuse sky maps. Our simulations predict a power reduction at the edge of the EoR wedge. The reduction in foreground power is confirmed with the Fisher analysis of the expected signal-to-noise ratio (SNR) improvement, which reports a higher SNR with the power estimations from CRAM baselines when compared with the regular MWA baselines. The reduced power obtained with the CRAM baselines is consistent with the fact that the larger tile configuration has reduced the impact of foregrounds from near the horizon.

The baryon mass content (i.e. stellar and gas mass) of dark matter halos in the early Universe depends on both global factors – for example, ionising ultraviolet (UV) radiation background – and local factors – for example, star formation efficiency and assembly history. We use a lightweight semi-analytical model to investigate how both local and global factors impact the halo baryon mass content at redshifts of $z\geq 5$. Our model incorporates a time delay between when stars form and when they produce feedback of $0\leq t^d/\mathrm{Myr} \leq 30$, which can drive bursts of star formation, and a mass and redshift-dependent UV background, which captures the influence of cosmological reionisation on gas accretion onto halos. We use statistically representative halo assembly histories and assume that the cosmological gas accretion rate is proportional to the halo mass accretion rate. Delayed ($t^d$>0) feedback leads to oscillations in gas mass with cosmic time, behaviour that cannot be captured with instantaneous feedback ($t^d$=0). Highly efficient star formation drives stronger oscillations, while strong feedback impacts when oscillations occur; in contrast, inefficient star formation and weak feedback produce similar long-term behaviour to that observed in instantaneous feedback models. If the delayed feedback timescale is too long, a halo retains its gas reservoir but the feedback suppresses star formation. Our model predicts that lower mass systems (halo masses $m_\mathrm{h} \leq 10^7 \mathrm{M}_\odot$) at $z \leq 10$ should be strongly gas deficient ($m_\mathrm{g}\rightarrow 0$), whereas higher mass systems retain their gas reservoirs because they are sufficiently massive to continue accreting gas through cosmological reionisation. Interestingly, in higher mass halos, the median $m_\star/(m_\star+m_\mathrm{g}) \simeq 0.01-0.05$, but is a factor of 3–5 smaller when feedback is delayed. Our model does not include seed supermassive black hole feedback, which is necessary to explain massive quenched galaxies in the early Universe.

Radio interferometers can potentially detect the sky-averaged signal from the Cosmic Dawn (CD) and the Epoch of Reionisation (EoR) by studying the Moon as a thermal block to the foreground sky. The first step is to mitigate the Earth-based radio frequency interference (RFI) reflections (Earthshine) from the Moon, which significantly contaminate the FM band $\approx 88-110$ MHz, crucial to CD-EoR science. We analysed Murchison Widefield Array (MWA) phase I data from 72 to 180 MHz at 40 kHz resolution to understand the nature of Earthshine over three observing nights. We took two approaches to correct the Earthshine component from the Moon. In the first method, we mitigated the Earthshine using the flux density of the two components from the data, while in the second method, we used simulated flux density based on an FM catalogue to mitigate the Earthshine. Using these methods, we were able to recover the expected Galactic foreground temperature of the patch of sky obscured by the Moon. We performed a joint analysis of the Galactic foregrounds and the Moon’s intrinsic temperature $(T_{\mathrm{Moon}})$ while assuming that the Moon has a constant thermal temperature throughout three epochs. We found $T_{\mathrm{Moon}}$ to be at $184.4\pm{2.6}\,\mathrm{K}$ and $173.8\pm{2.5}\,\mathrm{K}$ using the first and the second methods, respectively, and the best-fit values of the Galactic spectral index $(\alpha)$ to be within the 5% uncertainty level when compared with the global sky models. Compared with our previous work, these results improved constraints on the Galactic spectral index and the Moon’s intrinsic temperature. We also simulated the Earthshine at MWA between November and December 2023 to find suitable observing times less affected by the Earthshine. Such observing windows act as Earthshine avoidance and can be used to perform future global CD-EoR experiments using the Moon with the MWA.

We demonstrate that the Bayesian evidence can be used to find a good approximation of the ground truth likelihood function of a dataset, a goal of the likelihood-free inference (LFI) paradigm. As a concrete example, we use forward modelled sky-averaged 21-cm signal antenna temperature datasets where we artificially inject noise structures of various physically motivated forms. We find that the Gaussian likelihood performs poorly when the noise distribution deviates from the Gaussian case, for example, heteroscedastic radiometric or heavy-tailed noise. For these non-Gaussian noise structures, we show that the generalised normal likelihood is on a similar Bayesian evidence scale with comparable sky-averaged 21-cm signal recovery as the ground truth likelihood function of our injected noise. We therefore propose the generalised normal likelihood function as a good approximation of the true likelihood function if the noise structure is a priori unknown.

We demonstrate the effectiveness of a Bayesian evidence -based analysis for diagnosing and disentangling the sky-averaged 21-cm signal from instrumental systematic effects. As a case study, we consider a simulated REACH pipeline with an injected systematic. We demonstrate that very poor performance or erroneous signal recovery is achieved if the systematic remains unmodelled. These effects include sky-averaged 21-cm posterior estimates resembling a very deep or wide signal. However, when including parameterised models of the systematic, the signal recovery is dramatically improved in performance. Most importantly, a Bayesian evidence-based model comparison is capable of determining whether or not such a systematic model is needed as the true underlying generative model of an experimental dataset is in principle unknown. We, therefore, advocate a pipeline capable of testing a variety of potential systematic errors with the Bayesian evidence acting as the mechanism for detecting their presence.

Global 21-cm experiments require exquisitely precise calibration of the measurement systems in order to separate the weak 21-cm signal from Galactic and extragalactic foregrounds as well as instrumental systematics. Hitherto, experiments aiming to make this measurement have concentrated on measuring this signal using the single element approach. However, an alternative approach based on interferometers with short baselines is expected to alleviate some of the difficulties associated with a single element approach such as precision modelling of the receiver noise spectrum. Short spacing Interferometer Telescope probing cosmic dAwn and epoch of ReionisAtion (SITARA) is a short spacing interferometer deployed at the Murchison Radio-astronomy Observatory (MRO). It is intended to be a prototype or a test-bed to gain a better understanding of interferometry at short baselines, and develop tools to perform observations and data calibration. In this paper, we provide a description of the SITARA system and its deployment at the MRO, and discuss strategies developed to calibrate SITARA. We touch upon certain systematics seen in SITARA data and their modelling. We find that SITARA has sensitivity to all sky signals as well as non-negligible noise coupling between the antennas. It is seen that the coupled receiver noise has a spectral shape that broadly matches the theoretical calculations reported in prior works. We also find that when appropriately modified antenna radiation patterns taking into account the effects of mutual coupling are used, the measured data are well modelled by the standard visibility equation.

Precise instrumental calibration is of crucial importance to 21-cm cosmology experiments. The Murchison Widefield Array’s (MWA) Phase II compact configuration offers us opportunities for both redundant calibration and sky-based calibration algorithms; using the two in tandem is a potential approach to mitigate calibration errors caused by inaccurate sky models. The MWA Epoch of Reionization (EoR) experiment targets three patches of the sky (dubbed EoR0, EoR1, and EoR2) with deep observations. Previous work in Li et al. (2018) and (2019) studied the effect of tandem calibration on the EoR0 field and found that it yielded no significant improvement in the power spectrum (PS) over sky-based calibration alone. In this work, we apply similar techniques to the EoR1 field and find a distinct result: the improvements in the PS from tandem calibration are significant. To understand this result, we analyse both the calibration solutions themselves and the effects on the PS over three nights of EoR1 observations. We conclude that the presence of the bright radio galaxy Fornax A in EoR1 degrades the performance of sky-based calibration, which in turn enables redundant calibration to have a larger impact. These results suggest that redundant calibration can indeed mitigate some level of model incompleteness error.

Direct detection of the Epoch of Reionization (EoR) via redshifted 21 cm line of H i will reveal the nature of the first stars and galaxies as well as revolutionize our understanding of a poorly explored evolutionary phase of the Universe. Projects such as the MWA, LOFAR, and PAPER commenced in the last decade with the promise of high significance statistical detection of the EoR, but have so far only weakly constrained models owing to unforeseen challenges from bright foreground sources and instrument systematics. It is essential for next generation instruments like the HERA and SKA to have these challenges addressed. I present an analysis of these challenges – wide-field measurements, antenna beam chromaticity, reflections in the instrument, and antenna position errors – along with performance specifications and design solutions that will be critical to designing successful next-generation instruments in enabling the first detection and also in placing meaningful constraints on reionization models.

We present new software to cross-match low-frequency radio catalogues: the Positional Update and Matching Algorithm. The Positional Update and Matching Algorithm combines a positional Bayesian probabilistic approach with spectral matching criteria, allowing for confusing sources in the matching process. We go on to create a radio sky model using Positional Update and Matching Algorithm based on the Murchison Widefield Array Commissioning Survey, and are able to automatically cross-match ~ 98.5% of sources. Using the characteristics of this sky model, we create simple simulated mock catalogues on which to test the Positional Update and Matching Algorithm, and find that Positional Update and Matching Algorithm can reliably find the correct spectral indices of sources, along with being able to recover ionospheric offsets. Finally, we use this sky model to calibrate and remove foreground sources from simulated interferometric data, generated using OSKAR (the Oxford University visibility generator). We demonstrate that there is a substantial improvement in foreground source removal when using higher frequency and higher resolution source positions, even when correcting positions by an average of 0.3 arcmin given a synthesised beam-width of ~ 2.3 arcmin.

Cosmological simulations predict that dark matter halos with circular velocities lower than 30 km/s should have lost most of their neutral gas by heating of the ultra-violet background. This is in stark contrast with gas-rich galaxies such as e.g. Leo T, Leo P and Pisces A, which all have circular velocities of ~15 km/s (Ryan-Weber et al. 2008, Bernstein-Cooper et al. 2014, Tollerud et al. 2015). We show that when we include feedback from the first stars into our models, simulated dwarfs have very different properties at redshift 0 than when this form of feedback is not included. Including this Population-III feedback leads to galaxies that lie on the baryonic Tully-Fisher relation over the entire mass range of star forming dwarf galaxies, as well as reproducing a broad range of other observational properties.

In the redshift range 100≲(1+z)≲137, the cosmic microwave background (CMB) had a temperature of 273–373 K (0–100°C), allowing early rocky planets (if any existed) to have liquid water chemistry on their surface and be habitable, irrespective of their distance from a star. In the standard ΛCDM cosmology, the first star-forming halos within our Hubble volume started collapsing at these redshifts, allowing the chemistry of life to possibly begin when the Universe was merely 10–17 million years old. The possibility of life starting when the average matter density was a million times bigger than it is today is not in agreement with the anthropic explanation for the low value of the cosmological constant.

We present the results from our cosmological simulations of the first stages of galaxy formation. We use Gadget-2 (Springel 2005), modified to include detailed cooling, chemistry, and radiative transfer of primordial gas to study the impact of the first stars on galaxy formation. In contrast to previous work, we apply a realistic treatment of stellar feedback by using updated stellar models for the first stars. In this proceeding, we briefly summarize how stellar feedback from the first stars affects the primordial IGM inside the first galaxies.