arXiv subjects

Andrei Mesinger

Publications and source records attributed to Andrei Mesinger.

At least 37 records · Page 2Linked to original sources

arXiv2025

The Impact of Cosmic Variance on Inferences of Global Neutral Fraction Derived from Ly$α$ Luminosity Functions During Reionization

We investigate the impact of field-to-field variation, deriving from cosmic variance, in measured Lyman-$α$ emitter (LAE) luminosity functions (LFs) and this variation's impact on inferences of the neutral fraction of the intergalactic medium (IGM) during reionization. We post-process a z=7 IGM simulation to populate the dark matter halos with LAEs. These LAEs have realistic UV magnitudes, Ly$α$ fluxes, and Ly$α$ line profiles. We calculate the attenuation of Ly$α$ emission in universes with varying IGM neutral fraction, $\bar{\rm{x}}_{\rm{HI}}$. In a $\bar{\rm{x}}_{\rm{HI}}=0.3$ simulation, we perform 100 realizations of a mock 2 square degree survey with a redshift window $Δz = 0.5$ and flux limit $\rm{f}_{Lyα}>1\times10^{-17}\:\rm{ergs}\:\: \rm{s}^{-1} \: \rm{cm}^{-2}$; such a survey is typical in depth and volume of the largest LAE surveys conducted today. For each realization, we compute the LAE LF and use it to recover the input $\bar{\rm{x}}_{\rm{HI}}$. Comparing the inferred values of $\bar{\rm{x}}_{\rm{HI}}$ across the ensemble of the surveys, we find that cosmic variance, deriving from large-scale structure and variation in the neutral gas along the sightline, imposes a floor in the uncertainty of $Δ\bar{\rm{x}}_{\rm{HI}} \sim 0.2$ when $\bar{\rm{x}}_{\rm{HI}}$ $=0.3$. We explore mitigation strategies to decrease this uncertainty, such as increasing the volume, decreasing the flux limit, or probing the volume with many independent fields. Increasing the area and/or depth of the survey does not mitigate the uncertainty, but composing a survey with many independent fields is effective. This finding highlights the best strategy for LAE surveys aiming at constraining $\bar{\rm{x}}_{\rm{HI}}$ of the universe during reionization.

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arXiv2025

Bayesian estimation of cross-coupling and reflection systematics in 21cm array visibility data

Observations with radio arrays that target the 21-cm signal originating from the early Universe suffer from a variety of systematic effects. An important class of these are reflections and spurious couplings between antennas. We apply a Hamiltonian Monte Carlo sampler to the modelling and mitigation of these systematics in simulated Hydrogen Epoch of Reionisation Array (HERA) data. This method allows us to form statistical uncertainty estimates for both our models and the recovered visibilities, which is an important ingredient in establishing robust upper limits on the Epoch of Reionisation (EoR) power spectrum. In cases where the noise is large compared to the EoR signal, this approach can constrain the systematics well enough to mitigate them down to the noise level for both systematics studied. Incoherently averaging the recovered power spectra can further reduce the noise and improve recovery. Where the noise level is lower than the EoR, our modelling can mitigate the majority of the reflections and coupling with there being only a minor level of residual systematics. Our approach performs similarly to existing filtering/fitting techniques used in the HERA pipeline, but with the added benefit of rigorously propagating uncertainties. In all cases it does not significantly attenuate the underlying signal.

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arXiv2025

SKA-ESO Synergies for the Epoch of Reionization and Cosmic Dawn

Mapping out the first billion years using the 21-cm line with the Square Kilometer Array (SKA) will revolutionize our understanding of the cosmic dawn, reionization and the galaxies that drove these milestones. However, synergies with other telescopes in the form of cross correlations will be fundamental in making and confirming initial, low signal-to-noise claims of a detection. Participants of the 2023 European Southern Observatory (ESO) - SKA Observatory workshop discussed such synergies for Epoch of Reionization (EoR) and Cosmic Dawn (CD) science. Here we highlight some of the most promising candidates for cross-correlating SKA EoR/CD observations with ESO instruments such as the Multi-Object Optical and Near-infrared Spectrograph (MOONS), the MOSAIC multi-object spectrograph, and the ArmazoNes high Dispersion Echelle Spectrograph (ANDES).

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arXiv2025

matvis: A matrix-based visibility simulator for fast forward modelling of many-element 21 cm arrays

Detection of the faint 21 cm line emission from the Cosmic Dawn and Epoch of Reionisation will require not only exquisite control over instrumental calibration and systematics to achieve the necessary dynamic range of observations but also validation of analysis techniques to demonstrate their statistical properties and signal loss characteristics. A key ingredient in achieving this is the ability to perform high-fidelity simulations of the kinds of data that are produced by the large, many-element, radio interferometric arrays that have been purpose-built for these studies. The large scale of these arrays presents a computational challenge, as one must simulate a detailed sky and instrumental model across many hundreds of frequency channels, thousands of time samples, and tens of thousands of baselines for arrays with hundreds of antennas. In this paper, we present a fast matrix-based method for simulating radio interferometric measurements (visibilities) at the necessary scale. We achieve this through judicious use of primary beam interpolation, fast approximations for coordinate transforms, and a vectorised outer product to expand per-antenna quantities to per-baseline visibilities, coupled with standard parallelisation techniques. We validate the results of this method, implemented in the publicly-available matvis code, against a high-precision reference simulator, and explore its computational scaling on a variety of problems.

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arXiv2024

Impacts and Statistical Mitigation of Missing Data on the 21cm Power Spectrum: A Case Study with the Hydrogen Epoch of Reionization Array

The precise characterization and mitigation of systematic effects is one of the biggest roadblocks impeding the detection of the fluctuations of cosmological 21cm signals. Missing data in radio cosmological experiments, often due to radio frequency interference (RFI), poses a particular challenge to power spectrum analysis as it could lead to the ringing of bright foreground modes in Fourier space, heavily contaminating the cosmological signals. Here we show that the problem of missing data becomes even more arduous in the presence of systematic effects. Using a realistic numerical simulation, we demonstrate that partially flagged data combined with systematic effects can introduce significant foreground ringing. We show that such an effect can be mitigated through inpainting the missing data. We present a rigorous statistical framework that incorporates the process of inpainting missing data into a quadratic estimator of the 21cm power spectrum. Under this framework, the uncertainties associated with our inpainting method and its impact on power spectrum statistics can be understood. These results are applied to the latest Phase II observations taken by the Hydrogen Epoch of Reionization Array, forming a crucial component in power spectrum analyses as we move toward detecting 21cm signals in the ever more noisy RFI environment.

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arXiv2024

Percent-level timing of reionization: self-consistent, implicit-likelihood inference from XQR-30+ Ly$α$ forest data

The Lyman alpha (Lya) forest in the spectra of z>5 quasars provides a powerful probe of the late stages of the Epoch of Reionization (EoR). With the recent advent of exquisite datasets such as XQR-30, many models have struggled to reproduce the observed large-scale fluctuations in the Lya opacity. Here we introduce a Bayesian analysis framework that forward-models large-scale lightcones of IGM properties, and accounts for unresolved sub-structure in the Lya opacity by calibrating to higher-resolution hydrodynamic simulations. Our models directly connect physically-intuitive galaxy properties with the corresponding IGM evolution, without having to tune "effective" parameters or calibrate out the mean transmission. The forest data, in combination with UV luminosity functions and the CMB optical depth, are able to constrain global IGM properties at percent level precision in our fiducial model. Unlike many other works, we recover the forest observations without evoking a rapid drop in the ionizing emissivity from z~7 to 5.5, which we attribute to our sub-grid model for recombinations. In this fiducial model, reionization ends at $z=5.44\pm0.02$ and the EoR mid-point is at $z=7.7\pm0.1$. The ionizing escape fraction increases towards faint galaxies, showing a mild redshift evolution at fixed UV magnitude, Muv. Half of the ionizing photons are provided by galaxies fainter than Muv~-12, well below direct detection limits of optical/NIR instruments including JWST. We also show results from an alternative galaxy model that does not allow for a redshift evolution in the ionizing escape fraction. Despite being decisively disfavored by the Bayesian evidence, the posterior of this model is in qualitative agreement with that from our fiducial model. We caution however that our conclusions regarding the early stages of the EoR and which sources reionized the Universe are more model-dependent.

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arXiv2024

The EDGES measurement disfavors an excess radio background during the cosmic dawn

In 2018 the EDGES experiment claimed the first detection of the global cosmic 21cm signal, which featured an absorption trough centered around $z \sim 17$ with a depth of approximately -500mK. This amplitude is deeper than the standard prediction (in which the radio background is determined by the cosmic microwave background) by a factor of two and potentially hints at the existence of a radio background excess. While this result was obtained by fitting the data with a phenomenological flattened-Gaussian shape for the cosmological signal, here we develop a physical model for the inhomogeneous radio background sourced by the first galaxies hosting population III stars. Star formation in these galaxies is quenched at lower redshifts due to various feedback mechanisms, so they serve as a natural candidate for the excess radio background hinted by EDGES, without violating present day measurements by ARCADE2. We forward-model the EDGES sky temperature data, jointly sampling our physical model for the cosmic signal, a foreground model, and residual calibration errors. We compare the Bayesian evidences obtained by varying the complexity and prior ranges for the systematics. We find that the data is best explained by a model with seven log-polynomial foreground terms, and that it requires calibration residuals. Interestingly, the presence of a cosmic 21cm signal with a non-standard depth is decisively disfavored. This is contrary to previous EDGES analysis in the context of extra radio background models, serving as a caution against using a ''pseudo-likelihood'' built on a model (flattened Gaussian) that is different from the one being used for inference. We make our simulation code and associated emulator publicly-available.

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arXiv2024

Inferring reionization and galaxy properties from the patchy kinetic Sunyaev-Zel'dovich signal

The patchy kinetic Sunyaev-Zel'dovich (kSZ) signal is an integral probe of the timing and morphology of the epoch of reionization (EoR). Recent observations have claimed a low signal-to-noise (S/N) measurement, with a dramatic increase in S/N expected in the near future. In this work, we quantify what we can learn about the EoR from the kSZ signal. We perform Bayesian inference by sampling galaxy properties and using forward-models of the kSZ as well as other EoR and galaxy observations in the likelihood. Including the recent kSZ measurement obtained by the South Pole Telescope ($\mathcal{D}_{3000}^{\rm{pkSZ}} = 1.1_{-0.7}^{+1.1} μ$K$^2$) shifts the posterior distribution in favor of faster and later reionization models, resulting in lower values of the optical depth to the CMB: $τ_e = 0.052_{-0.008}^{+0.009}$ with a 68$\%$ confidence interval (C.I.). The combined EoR and UV luminosity function observations also imply a typical ionizing escape fraction of $0.04_{-0.03}^{+0.05}$ (95$\%$ C.I.), without a strong dependence on halo mass. We show how the patchy kSZ power from our posterior depends on the commonly-used parameters of reionization. For a given midpoint and duration, the EoR morphology only has a few percent impact on the patchy kSZ power in our posterior. However, a physical model is needed to obtain tight constraints from the current low S/N patchy kSZ measurement, as it allows us to take advantage of complimentary high-$z$ observations. Future high S/N detections of the patchy kSZ should decrease the current uncertainties on the timing of the EoR by factors of $\sim$2 - 3.

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arXiv2024

Mapping reionization bubbles in the JWST era I: empirical edge detection with Lyman alpha emission from galaxies

Ionized bubble sizes during reionization trace physical properties of the first galaxies. JWST's ability to spectroscopically confirm and measure Lyman-alpha (Ly$α$) emission in sub-L* galaxies opens the door to mapping ionized bubbles in 3D. However, existing Lya-based bubble measurement strategies rely on constraints from single galaxies, which are limited by the large variability in intrinsic Ly$α$ emission. As a first step, we present two bubble size estimation methods using Lya spectroscopy of ensembles of galaxies, enabling us to map ionized structures and marginalize over Ly$α$ emission variability. We test our methods using Gpc-scale reionization simulations of the intergalactic medium (IGM). To map bubbles in the plane of the sky, we develop an edge detection method based on the asymmetry of Ly$α$ transmission as a function of spatial position. To map bubbles along the line-of-sight, we develop an algorithm using the tight relation between Ly$α$ transmission and the line-of-sight distance from galaxies to the nearest neutral IGM patch. Both methods can robustly recover bubbles with radius $\gtrsim$10 comoving Mpc, sufficient for mapping bubbles even in the early phases of reionization, when the IGM is $\sim70-90\%$ neutral. These methods require $\gtrsim$0.002-0.004 galaxies/cMpc$^3$, a $5σ$ Ly$α$ equivalent width upper limit of $\lesssim$30Å for the faintest targets, and redshift precision $Δz \lesssim 0.015$, feasible with JWST spectroscopy. Shallower observations will provide robust lower limits on bubble sizes. Additional constraints on IGM transmission from Ly$α$ escape fractions and line profiles will further refine these methods, paving the way to our first direct understanding of ionized bubble growth.

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arXiv2024

The importance of stochasticity in determining galaxy emissivities and UV LFs during cosmic dawn and reionization

The stochastic nature of star formation and photon propagation in high-redshift galaxies can result in sizable galaxy-to-galaxy scatter in their properties. Ignoring this scatter by assuming mean quantities can bias estimates of their emissivity and corresponding observables. We construct a flexible, semi-empirical model, sampling scatter around the following mean relations: (i) the conditional halo mass function (CHMF); (ii) the stellar-to-halo mass relation (SHMR); (iii) galaxy star formation main sequence (SFMS); (iv) fundamental metallicity relation (FMR); (v) conditional intrinsic luminosity; and (vi) photon escape fraction. In our fiducial model, ignoring scatter in these galaxy properties overestimates the duration of the EoR, delaying its completion by up to $Δz$ ~ 2. We quantify the relative importance of each of the above sources of scatter in determining the ionizing, soft-band X-ray and Lyman Werner (LW) emissivities as a function of scale and redshift. We find that scatter around the SFMS is important for all bands, especially at the highest redshifts where the emissivity is dominated by the faintest, most "bursty" galaxies. Ignoring this scatter would underestimate the mean emissivity and its standard deviation computed over 5 cMpc regions by factors of up to $\sim$2-10 at $5< z < 15$. Scatter around the X-ray luminosity to star formation rate relation is important for determining X-ray emissivity, accounting for roughly half of its mean and standard deviation. The importance of scatter in the ionizing escape fraction depends on its functional form, while scatter around the SHMR contributes at the level of ~10-20%. Although scatter does flatten the UV luminosity functions, shifting the bright end by 1-2 magnitudes, the level of scatter in our fiducial model is insufficient to fully explain recent estimates from JWST photometry (consistent with previous studies).

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arXiv2024

How informative are summaries of the cosmic 21-cm signal?

The cosmic 21-cm signal will bring data-driven advances to studies of the Cosmic Dawn (CD) and Epoch of Reionization (EoR). Radio telescopes such as the SKA will eventually map the HI fluctuations over the first billion years - the majority of our observable Universe. With such large data volumes, it becomes increasingly important to develop "optimal" summary statistics, allowing us to learn as much as possible about the CD and EoR. In this work we compare the constraining power of several 21-cm summary statistics, using the determinant of the Fisher information matrix, $\det F$. Since we do not have an established "fiducial" model for the astrophysics of the first galaxies, we compute the distribution of $\det F$ across the prior volume. Using a large database of cosmic 21-cm lightcones that include realizations of telescope noise, we compare the following summaries: (i) the spherically-averaged power spectrum (1DPS), (ii) the cylindrically-averaged power spectrum (2DPS), (iii) the 2D Wavelet scattering transform (WST), (iv) a recurrent neural network (RNN), (v) an information-maximizing neural network (IMNN), and (vi) the combination of 2DPS and IMNN. Our best performing individual summary is the 2DPS, having relatively high Fisher information throughout parameter space. Although capable of achieving the highest Fisher information for some parameter choices, the IMNN does not generalize well, resulting in a broad distribution. Our best results are achieved with the concatenation of the 2DPS and IMNN. The combination of only these two complimentary summaries reduces the recovered parameter variances on average by factors of $\sim$6.5 - 9.5, compared with using each summary independently. Finally, we point out that that the common assumption of a constant covariance matrix when doing Fisher forecasts using 21-cm summaries can significantly underestimate parameter constraints.

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arXiv2024

21cm signal sensitivity to dark matter decay

The redshifted 21cm signal from the Cosmic Dawn is expected to provide unprecedented insights into early Universe astrophysics and cosmology. Here we explore how dark matter can heat the intergalactic medium before the first galaxies, leaving a distinctive imprint in the 21cm power spectrum. We provide the first dedicated Fisher matrix forecasts on the sensitivity of the Hydrogen Epoch of Reionization Array (HERA) telescope to dark matter decays. We show that with 1000 hours of observation, HERA has the potential to improve current cosmological constraints on the dark matter decay lifetime by up to three orders of magnitude. Even in extreme scenarios with strong X-ray emission from early-forming, metal-free galaxies, the bounds on the decay lifetime would be improved by up to two orders of magnitude. Overall, HERA shall improve on existing limits for dark matter masses below $2$ GeV$/c^2$ for decays into $e^+e^-$ and below few MeV$/c^2$ for decays into photons.

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arXiv2024

21cmEMU: an emulator of 21cmFAST summary observables

Recent years have witnessed rapid progress in observations of the Epoch of Reionization (EoR). These have enabled high-dimensional inference of galaxy and intergalactic medium (IGM) properties during the first billion years of our Universe. However, even using efficient, semi-numerical simulations, traditional inference approaches that compute 3D lightcones on-the-fly can take $10^5$ core hours. Here we present 21cmEMU: an emulator of several summary observables from the popular 21cmFAST simulation code. 21cmEMU takes as input nine parameters characterizing EoR galaxies, and outputs the following summary statistics: (i) the IGM mean neutral fraction; (ii) the 21-cm power spectrum; (iii) the mean 21-cm spin temperature; (iv) the sky-averaged (global) 21-cm signal; (v) the ultraviolet (UV) luminosity functions (LFs); and (vi) the Thomson scattering optical depth to the cosmic microwave background (CMB). All observables are predicted with sub-percent median accuracy, with a reduction of the computational cost by a factor of over 10$^4$. After validating inference results, we showcase a few applications, including: (i) quantifying the relative constraining power of different observational datasets; (ii) seeing how recent claims of a late EoR impact previous inferences; and (iii) forecasting upcoming constraints from the sixth observing season of the Hydrogen Epoch of Reionization Array (HERA) telescope. 21cmEMU is publicly-available, and is included as an alternative simulator in the public 21CMMC sampler.

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arXiv2024

Direct Optimal Mapping Image Power Spectrum and its Window Functions

The key to detecting neutral hydrogen during the epoch of reionization (EoR) is to separate the cosmological signal from the dominating foreground radiation. We developed direct optimal mapping (DOM) to map interferometric visibilities; it contains only linear operations, with full knowledge of point spread functions from visibilities to images. Here, we demonstrate a fast Fourier transform-based image power spectrum and its window functions computed from the DOM images. We use noiseless simulation, based on the Hydrogen Epoch of Reionization Array Phase I configuration, to study the image power spectrum properties. The window functions show $<10^{-11}$ of the integrated power leaks from the foreground-dominated region into the EoR window; the 2D and 1D power spectra also verify the separation between the foregrounds and the EoR.

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arXiv2024

IGM damping wing constraints on the tail end of reionisation from the enlarged XQR-30 sample

The attenuation of Ly$α$ photons by neutral hydrogen in the intergalactic medium (IGM) at $z\gtrsim5$ continues to be a powerful probe for studying the epoch of reionisation. Given a framework to estimate the intrinsic (true) Ly$α$ emission of high-$z$ sources, one can infer the ionisation state of the IGM during reionisation. In this work, we use the enlarged XQR-30 sample of 42 high-resolution and high-SNR QSO spectra between $5.8\lesssim\,z\lesssim\,6.6$ obtained with VLT/X-Shooter to place constraints on the IGM neutral fraction. This is achieved using our existing Bayesian QSO reconstruction framework which accounts for uncertainties such as the: (i) posterior distribution of predicted intrinsic Ly$α$ emission profiles (obtained via covariance matrix reconstruction of the Ly$α$ and N V emission lines from unattenuated high-ionisation emission line profiles; C IV, Si IV + O IV] and C III]) and (ii) distribution of ionised regions within the IGM using synthetic damping wing profiles drawn from a $1.6^3$ Gpc$^3$ reionisation simulation. Following careful quality control, we used 23 of the 42 available QSOs to obtain constraints/limits on the IGM neutral fraction during the tail-end of reionisation. Our median and 68th percentile constraints on the IGM neutral fraction are: $0.20\substack{+0.14\\-0.12}$ and $0.29\substack{+0.14\\-0.13}$ at $z = 6.15$~and 6.35. Further, we also report 68th percentile upper-limits of $\bar{x}_{\mathrm{H\,{\scriptscriptstyle I}}} < 0.21$, 0.20, 0.21 and 0.18 at $z = 5.8, 5.95, 6.05$~and 6.55. These results imply reionisation is still ongoing at $5.8\lesssim\,z\lesssim\,6.55$, consistent with previous results from XQR-30 (dark fraction and Ly$α$ forest) along with other observational probes considered in the literature.

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arXiv2024

Blind QSO reconstruction challenge: Exploring methods to reconstruct the Ly$α$ emission line of QSOs

Reconstructing the intrinsic Ly$α$ line flux from high-$z$ QSOs can place constraints on the neutral hydrogen content of the intergalactic medium during reionisation. There are now $\gtrsim10$ different Ly$α$ reconstruction pipelines using different methodologies to predict the Ly$α$ line flux from correlations with the spectral information redward of Ly$α$. However, there have been few attempts to directly compare the performance of these pipelines. Therefore, we devised a blind QSO challenge to compare these reconstruction pipelines on a uniform set of objects. Each author was provided de-identified, observed rest-frame QSO spectra with spectral information only redward of 1260Å rest-frame to ensure unbiased reconstruction. We constructed two samples of 30 QSOs, from X-Shooter and SDSS both spanning $3.5<z<4.5$. Importantly, the purpose of this comparison study was not to champion a single, best performing reconstruction pipeline but rather to explore the relative performance of these pipelines over a range of QSOs with broad observational characteristics to infer general trends. In summary, we find machine learning approaches in general provide the strongest ``best guesses" but underestimate the accompanying statistical uncertainty, although these can be recalibrated, whilst pipelines that decompose the spectral information, for example principal component or factor analysis generally perform better at predicting the Ly$α$ profile. Further, we found that reconstruction pipelines trained on SDSS QSOs performed similarly on average for both the X-Shooter and SDSS samples indicating no discernible biases owing to differences in the observational characteristics of the training set or QSO being reconstructed, although the recovered distributions of reconstructions for X-Shooter were broader likely due to an increased fraction of outliers.

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arXiv2024

Inferring astrophysical parameters using the 2D cylindrical power spectrum from reionisation

Enlightening our understanding of the first galaxies responsible for driving reionisation requires detecting the 21-cm signal from neutral hydrogen. Interpreting the wealth of information embedded in this signal requires Bayesian inference. Parameter inference from the 21-cm signal is primarily restricted to the spherically averaged power spectrum (1D PS) owing to its relatively straightforward derivation of an analytic likelihood function enabling traditional Monte-Carlo Markov-Chain (MCMC) approaches. However, in recent years, simulation-based inference (SBI) has become feasible which removes the necessity of having an analytic likelihood, enabling more complex summary statistics of the 21-cm signal to be used for Bayesian inference. In this work, we use SBI, specifically marginal neural ratio estimation to learn the likelihood-to-evidence ratio with Swyft, to explore parameter inference using the cylindrically averaged 2D PS. Since the 21-cm signal is anisotropic, the 2D PS should yield more constraining information compared to the 1D PS which isotropically averages the signal. For this, we consider a mock 1000 hr observation of the 21-cm signal using the SKA and compare the performance of the 2D PS relative to the 1D PS. Additionally, we explore two separate foreground mitigation strategies, perfect foreground removal and wedge avoidance. We find the 2D PS outperforms the 1D PS by improving the marginalised uncertainties on individual astrophysical parameters by up to $\sim30-40$ per cent irrespective of the foreground mitigation strategy. Primarily, these improvements stem from how the 2D PS distinguishes between the transverse, $k_{\perp}$, and redshift dependent, $k_{\parallel}$ information which enables greater sensitivity to the complex reionisation morphology.

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arXiv2024

Exploring the role of the halo mass function for inferring astrophysical parameters during reionisation

The detection of the 21-cm signal at $z\gtrsim6$ will reveal insights into the properties of the first galaxies responsible for driving reionisation. To extract this information, we perform parameter inference which requires embedding 3D simulations of the 21-cm signal within a Bayesian inference pipeline. Presently, when performing inference we must choose which sources of uncertainty to sample and which to hold fixed. Since the astrophysics of galaxies are much more uncertain than those of the underlying halo-mass function (HMF), we usually parameterise and model the former while fixing the latter. However, in doing so we may bias our inference of the properties of these first galaxies. In this work, we explore the consequences of assuming an incorrect choice of HMF and quantify the relative biases in our inferred astrophysical model parameters when considering the wrong HMF. We then relax this assumption by constructing a generalised five parameter model for the HMF and simultaneously recover these parameters along with our underlying astrophysical model. For this analysis, we use 21cmFAST and perform Simulation-Based Inference by applying marginal neural ratio estimation to learn the likelihood-to-evidence ratio using Swyft. Using a mock 1000 hour observation of the 21-cm power spectrum from the forthcoming Square Kilometre Array, conservatively assuming foreground wedge avoidance, we find assuming the incorrect HMF can bias the recovered astrophysical parameters by up to $\sim3-4σ$ even when including independent information from observed luminosity functions. When considering our generalised HMF model, we recover constraints on our astrophysical parameters with a factor of $\sim2-4$ larger marginalised uncertainties. Importantly, these constraints are unbiased, agnostic to the underlying HMF and therefore more conservative.

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