arXiv subjects

Harry T. J. Bevins

Publications and source records attributed to Harry T. J. Bevins.

15 recordsLinked to original sources

arXiv2026

hyprfine: simulating the 21-cm signal from the Dark Ages through to the Epoch of Reionization on a GPU

hyprfine is an analytic simulation of the sky-averaged 21-cm signal from $z=1100 - 6$ written using JAX and Python for native GPU capabilities. It models the average temperature of the 21-cm signal over cosmic time as a function of the $Λ$-CDM cosmology parameters and the astrophysics of the first stars and galaxies. As far as we are aware, the code is the first analytic GPU native simulation of the 21-cm signal. It runs in a fraction of a second, parallelises efficiently across a GPU and is differentiable through the Dark Ages ($z \geq 35$). The code is publicly available at https://www.github.com/htjb/hyprfine.

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arXiv2026

Quantifying Sky Map Resolution Requirements for Beam Chromaticity Correction in Sky-Averaged 21 cm Experiments

The 21 cm hyperfine transition of neutral hydrogen provides one of the few direct probes of the early cosmic history. High-redshift detections of this signal could shine light on the poorly understood epochs of the Dark Ages and Cosmic Dawn, periods that remain among the least understood in the Universe's history. However, this signal is masked by bright foregrounds and is distorted by the chromaticity of the antenna used to detect it. Correcting for the chromaticity requires an accurate representation of the radio sky across relevant frequencies. However, base sky maps used for this correction, such as instances of the Global Sky Model (GSM), are limited by resolution, calibration and extrapolation uncertainties, especially when scaled to lower frequencies relevant for Cosmic Dawn studies. This work quantifies how accurately the base map must represent the true sky to produce a reliable beam correction. Using simulated sky data, we generate beam chromaticity corrections generated from progressively degraded versions of the base map, and compare how well they do in comparison to a correction based on the full-resolution map. We find that degradation in map resolution of $\sim 1^\circ$ does not introduce measurable increases in the amplitude of the residuals when correcting for the chromaticity and subtracting three different foreground models (two polynomials and a power law expansion). These results provide practical constraints on the required resolution and accuracy of sky models used in beam correction pipelines, informing future design and calibration strategies for global 21 cm experiments, and future efforts to map the low frequency sky.

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arXiv2026

Towards end-to-end Bayesian forward models in global 21-cm cosmology: surrogate modelling and marginalisation of beam uncertainty

Robust statistical inference in global 21-cm cosmology requires end-to-end uncertainty quantification that jointly handles the highly degenerate cosmological signal, foreground emission, and instrumental response. Although electromagnetic simulations capture physical antenna properties in a parametrised way, multi-hour runtimes make their integration within likelihood-based sampling frameworks infeasible. Most existing approaches therefore assume a single precomputed beam, a fragile assumption given our demonstration that realistic mismatches can severely bias the recovered cosmological and foreground parameters. To address this, we present an accelerated and differentiable Bayesian framework that incorporates an informed surrogate representation of chromatic beam uncertainty directly into a forward-modelling pipeline. Treating the physical antenna properties as nuisance quantities, we apply a two-stage decomposition directly to simulated directivity patterns, reducing the instrumental parameterisation by two orders of magnitude while retaining the angular and spectral structure required for accurate beam reconstruction. Exploiting the linearity of the resulting surrogate, we use analytical marginalisation to allow the continuous instrumental uncertainty to be propagated into the final posteriors and Bayesian evidence without directly sampling the beam space. Testing the framework against a suite of unseen beams and cosmological signals, we recover the true inputs at approximately the instrumental-noise level. We further show that, for the uncertainty considered here, as few as 100 electromagnetic simulations are sufficient to construct an effective surrogate, substantially reducing the simulation burden for future analyses. This framework provides a scalable, statistically rigorous route towards hardware-accelerated uncertainty quantification in global 21-cm cosmology.

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arXiv2026

Impact of numerical stability in Bayesian noise wave calibration on global 21-cm experiments

Detecting the global 21-cm signal from the Cosmic Dawn and Epoch of Reionization requires calibration accuracy far below the level of astrophysical foregrounds. REACH models its receiver using the noise wave formalism, with five frequency-dependent low-noise amplifier parameters fitted jointly to multiple calibration sources. We identify a numerical instability in this Bayesian calibration pipeline: the condition number of the posterior covariance matrix reaches $κ(\mathbf{V}^*) \sim 10^{9}$--$10^{11}$, making solutions non-reproducible across computing environments. Singular value decomposition shows that the instability is driven by near-collinearity between the design-matrix columns associated with the excess noise source temperature, $X_\mathrm{NS}$, and the load temperature, $X_\mathrm{L}$. Using a Chebyshev basis, we develop a two-step mitigation. First, fixing $T_\mathrm{NS}$ to a scalar removes the degeneracy and reduces $κ(\mathbf{V}^*)$ to $\sim 60$. Second, to retain frequency dependence, we recover $T_\mathrm{NS}(ν)$ directly from the hot-load calibration measurement. On mock data, this method preserves the stability of the reduced model while achieving comparable calibration accuracy. Masking narrow channels around cable standing-wave degeneracies further removes local artefacts in the design matrix. These steps provide a stable, reproducible, and data-driven calibration procedure. Because the $X_\mathrm{NS}$--$X_\mathrm{L}$ degeneracy is inherent to the noise wave formalism, the method is relevant to other global 21-cm experiments.

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arXiv2026

Simulation-based tension quantification of the cosmic dipole

The cosmic dipole measured in surveys of cosmologically distant sources consistently exceeds the expectation derived from the cosmic microwave background, posing a significant challenge to the standard $Λ$CDM cosmology. In the era of precision cosmology, quantifying robust tensions is constrained by our ability to model complex, non-linear effects that often result in intractable likelihood functions. In this paper, we present a flexible simulation-based inference (SBI) architecture for measuring the cosmic dipole tension using Neural Ratio Estimators (NREs). We design and train an ensemble of NREs to evaluate the log Bayesian evidence ratio and measure $Nσ$ tension. We validate our approach against nested sampling, demonstrating that it accurately recovers the ground-truth. Under the kinematic interpretation of the dipole, we apply our approach to Planck, the NRAO VLA Sky Survey (NVSS), the Rapid ASKAP Continuum Survey (RACS), and the Wide-field Infrared Survey Explorer catalogue (CatWISE). Here, leveraging SBI, we measure a $\approx5.7σ$ tension between CatWISE and Planck. We demonstrate the extensibility of our approach by applying it to forward-modelled simulations of the CatWISE Eddington bias, revealing a $\approx6.7σ$ tension. The methodology proposed here enables robust tension quantification as we enter the era of LSST, Euclid, and the SKA.

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arXiv2026

Optimisation of calibration sources for global 21-cm experiments: the REACH case

The spin-flip 21-cm signal from the Cosmic Dawn and the Epoch of Reionization is an essential probe of the conditions that led to the formation of the first luminous objects in the early Universe. However, its detection remains a major challenge owing to its low strength compared to the bright foregrounds and the requirement of precise calibration of the instrument to prevent systematics that could hinder a detection or lead to false inferences. REACH (Radio Experiment for the Analysis of Cosmic Hydrogen) is a radiometer experiment designed to detect this sky-averaged signal in the frequency range of 50--130~MHz. Using a wide-beam antenna, REACH calibration relies on internal reference sources, covering a broad range of temperatures and reflection coefficients. The choice of type and number of calibrators used significantly influences the quality of the calibration. This work investigates these effects and introduces a novel method for selecting an optimal set of calibration sources. With an optimised set, we aim to reduce calibration time, thereby increasing sky integration time while preserving calibration accuracy. We explore two optimisation strategies: one applied across the full receiver band and another performed on a frequency-by-frequency basis. Finally, we demonstrate that, with a total calibration time comparable to the conventional full-calibrator set, an optimised set with fewer calibrators achieves approximately a $15~\%$ reduction in calibrated temperature noise and improved absolute calibration of the instrument. This has implications for better calibration strategies in similar radiometer experiments.

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arXiv2026

Calibrating Bayesian Tension Statistics using Neural Ratio Estimation

When fits of the same physical model to two different datasets disagree, we call this tension. Several apparent tensions in cosmology have occupied researchers in recent years, and a number of different metrics have been proposed to quantify tension. Many of these metrics suffer from limiting assumptions, and correctly calibrating these is essential if we want to successfully determine whether discrepancies are significant. A commonly used metric of tension is the evidence ratio R. The statistic has been widely adopted by the community as a Bayesian way of quantifying tensions, however, it has a non-trivial dependence on the prior that is not always accounted for properly. We show that this can be calibrated out effectively with Neural Ratio Estimation. We demonstrate our proposed calibration technique with an analytic example, a toy example inspired by 21-cm cosmology, and with observations of the Baryon Acoustic Oscillations from the Dark Energy Spectroscopic Instrument (DESI) and the Sloan Digital Sky Survey (SDSS). We find no significant tension between DESI and SDSS.

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arXiv2025

Galaxies as stochastic systems: why the next breakthrough in galaxy evolution requires one hundred million spectra

Each galaxy is observed only once along its life, making galaxy evolution fundamentally an inverse statistical problem: time-dependent physics must be inferred from ensembles of single-epoch snapshots. To move beyond descriptive scaling relations toward physical regulation mechanisms of star formation, quenching, chemical enrichment and black hole growth, galaxies must be treated as realizations of a stochastic process whose hyper-parameters (e.g., correlation timescales, burstiness, duty cycles) are inferred hierarchically. This demands both depth and scale: continuum S/N sufficient for absorption-line ages and chemistry, and samples far larger than those in SDSS, DESI, 4MOST or MOONS, which provide either depth or size but not both across $0<z<3$. Once the relevant axes of mass, redshift, environment, structure and evolutionary phase are populated, the requirement naturally rises from $10^7$ to $\sim10^8$ galaxies. This is the regime where stochastic hyper-parameters can be well constrained and where comparisons to simulations and cosmological forward models become limited by theory rather than observations. We outline the science enabled by such a programme and the corresponding requirements for a future ESO wide-field spectroscopic facility capable of delivering tens to hundreds of millions of rest-UV-optical spectra over $0\lesssim z\lesssim3$.

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arXiv2025

Narrowing the discovery space of the cosmological 21-cm signal using multi-wavelength constraints

The cosmic 21-cm signal is a promising probe of the early Universe, owing to its sensitivity to the thermal state of the neutral intergalactic medium (IGM) and properties of the first luminous sources. Here, we constrain the 21-cm signal and infer IGM properties using the Population II galaxy parameters derived in a previous study through multi-wavelength synergies. This includes high-redshift UV luminosity functions (UVLFs) from Hubble Space Telescope (HST) and James Webb Space Telescope (JWST), cosmic X-ray and radio backgrounds (CXB and CRB), the SARAS 3 global 21-cm signal non-detection, and HERA 21-cm power spectrum upper limits. From CXB and HERA data, we infer the IGM kinetic temperature to be $T_\text{K}(z=15)\lesssim 7.7~\text{K}$, $2.5~\text{K} \lesssim T_\text{K}(z=10) \lesssim 66~\text{K}$, and $20~\text{K}\lesssim T_\text{K}(z=6) \lesssim 2078~\text{K}$ at 95% credible interval (C.I.). Similarly, CRB and HERA data limit the radio emission efficiency of galaxies, giving $T_\text{rad}(z=15) \lesssim 47~\text{K}$, $T_\text{rad}(z=10)\lesssim 51~\text{K}$, and $T_\text{rad}(z=6)\lesssim 101~\text{K}$. These constraints, strengthened by UVLFs from HST and JWST, enable the first $\textit{lower bound}$ on the cosmic 21-cm signal. We infer an absorption trough of depth ${-201~\text{mK}\lesssim T_\text{21,min} \lesssim -68~\text{mK}}$ at $z_\text{min}\approx10-16$, and a power spectrum of $8.7~\text{mK}^2 < Δ_{21}^2(z=15) < 197~\text{mK}^2$ at $k=0.35~h\text{Mpc}^{-1}$. Our results highlight the power of multi-wavelength synergies in constraining the early Universe. While promising for upcoming 21-cm experiments, the results depend on our assumption of a redshift-independent X-ray and radio efficiency of galaxies, and the exclusion of a flexible model for Population III stars.

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arXiv2025

Exploiting synergies between JWST and cosmic 21-cm observations to uncover star formation in the early Universe

In the current era of JWST, we continue to uncover a wealth of information about the Universe deep into the Epoch of Reionization. In this work, we use a suite of simulations with 21cmSPACE, to explore the astrophysical properties of early galaxies and their imprint on high-redshift observables. Our analysis incorporates a range of multi-wavelength datasets including UV luminosity functions (UVLFs) from HST and JWST spanning $z=6-14.5$, the 21-cm global signal and power spectrum limits from SARAS 3 and HERA respectively, as well as present-day diffuse X-ray and radio backgrounds. We constrain a flexible halo-mass and redshift dependent model of star-formation efficiency (SFE), defined as the fraction of gas converted into stars, and find that it is best described by minimal redshift evolution at $z\approx 6-10$, followed by rapid evolution at $z\approx10-15$. Using Bayesian inference, we derive functional posteriors of the SFE, inferring that halos of mass $M_h=10^{10}\,\mathrm{M}_\odot$ have efficiencies of $\approx 1 - 2\%$ at $z\lesssim10$, $\approx8\%$ at $z=12$ and $\approx21\%$ at $z=15$. We also highlight the synergy between UVLFs and global 21-cm signal from SARAS 3 in constraining the minimum virial conditions required for star-formation in halos. In parallel, we find the X-ray and radio efficiencies of early galaxies to be $f_X = 0.8^{+9.7}_{-0.4}$ and $f_r \lesssim 16.9$ respectively, improving upon previous works that exclude UVLF data. Our results underscore the critical role of UVLFs in constraining early galaxy properties, and their synergy with 21-cm and other multi-wavelength observations.

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arXiv2025

Rapid and Late Cosmic Reionization Driven by Massive Galaxies: a Joint Analysis of Constraints from 21-cm, Lyman Line & CMB Data Sets

Observations of the Epoch of Reionization (EoR) have the potential to answer long-standing questions of astrophysical interest regarding the nature of the first luminous sources and their effects on the intergalactic medium (IGM). We present astrophysical constraints from a Neural Density Estimation-Accelerated Bayesian joint analysis of constraints deriving from Cosmic Microwave Background power spectrum measurements from Planck and SPT, IGM neutral fraction measurements from Lyman-line-based data sets and 21-cm power spectrum upper limits from HERA, LOFAR and the MWA. In the context of the model employed, the data is found to be consistent with galaxies forming from predominantly atomic-cooled hydrogen gas in dark matter halos, with masses $M_\mathrm{min} \gtrsim 2.6 \times 10^{9}~M_{\odot} ((1+z)/10)^{\frac{1}{2}}$ at 95% credibility ($V_\mathrm{c} \gtrsim 50~\mathrm{km~s^{-1}}$) being the dominant galactic population driving reionization. These galaxies reionize the neutral hydrogen in the IGM over a narrow redshift interval ($Δz_\mathrm{re} < 1.8$ at 95% credibility), with the midpoint of reionization (when the sky-averaged IGM neutral fraction is 50%) constrained to $z_{50} = 7.16^{+0.15}_{-0.12}$. Given the parameter posteriors from our joint analysis, we find that the posterior predictive distribution of the global 21-cm signal is reduced in amplitude and shifted to lower redshifts relative to the model prior. We caution, however, that our inferences are model-dependent. Future work incorporating updated, mass-dependent star formation efficiencies in atomic cooling halos, informed by the latest UV luminosity function constraints from the James Webb Space Telescope, promises to refine these inferences further and enhance our understanding of cosmic reionization.

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arXiv2025

Accounting for Noise and Singularities in Bayesian Calibration Methods for Global 21-cm Cosmology Experiments

Due to the large dynamic ranges involved with separating the cosmological 21-cm signal from the Cosmic Dawn from galactic foregrounds, a well-calibrated instrument is essential to avoid biases from instrumental systematics. In this paper we present three methods for calibrating a global 21-cm cosmology experiment using the noise wave parameter formalisation to characterise a low noise amplifier including a careful consideration of how calibrator temperature noise and singularities will bias the result. The first method presented in this paper builds upon the existing conjugate priors method by weighting the calibrators by a physically motivated factor, thereby avoiding singularities and normalising the noise. The second method fits polynomials to the noise wave parameters by marginalising over the polynomial coefficients and sampling the polynomial orders as parameters. The third method introduces a physically motivated noise model to the marginalised polynomial method. Running these methods on a suite of simulated datasets based on the REACH receiver design and a lab dataset, we found that our methods produced a calibration solution which is equally as or more accurate than the existing conjugate priors method when compared with an analytic estimate of the calibrator's noise. We find in the case of the measured lab dataset the conjugate priors method is biased heavily by the large noise on the shorted load calibrator, resulting in incorrect noise wave parameter fits. This is mitigated by the methods introduced in this paper which calibrate the validation source spectra to within 5% of the noise floor.

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arXiv2024

Global 21 cm Signal Recovery Under Changing Environmental Conditions

The redshifted 21 cm line of cosmic atomic hydrogen is one of the most auspicious tools in deciphering the early Universe. Recovering this signal remains an ongoing problem for cosmologists in the field, with the signal being hidden behind foregrounds approximately five orders of magnitude brighter than itself. A traditional forward modelling data analysis pipeline using Bayesian data analysis and a physically motivated foreground model to find this signal shows great promise in the case of unchanging environmental conditions. However we demonstrate in this paper that in the presence of a soil with changing dielectric properties under the antenna over time, or a changing soil temperature in the far field of our observation these traditional methods struggle. In this paper we detail a tool using Masked Auto-regressive Flows that improves upon previous physically motivated foreground models when one is trying to recover this signal in the presence of changing environmental conditions. We demonstrate that with these changing parameters our tool consistently recovers the signal with a much greater Bayesian evidence than the traditional data analysis pipeline, decreasing the root mean square error in the recovery of the injected signal by up to 45 %.

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arXiv2023

Marginal Post Processing of Bayesian Inference Products with Normalizing Flows and Kernel Density Estimators

Bayesian analysis has become an indispensable tool across many different cosmological fields including the study of gravitational waves, the Cosmic Microwave Background and the 21-cm signal from the Cosmic Dawn among other phenomena. The method provides a way to fit complex models to data describing key cosmological and astrophysical signals and a whole host of contaminating signals and instrumental effects modelled with `nuisance parameters'. In this paper, we summarise a method that uses Masked Autoregressive Flows and Kernel Density Estimators to learn marginal posterior densities corresponding to core science parameters. We find that the marginal or 'nuisance-free' posteriors and the associated likelihoods have an abundance of applications including; the calculation of previously intractable marginal Kullback-Leibler divergences and marginal Bayesian Model Dimensionalities, likelihood emulation and prior emulation. We demonstrate each application using toy examples, examples from the field of 21-cm cosmology and samples from the Dark Energy Survey. We discuss how marginal summary statistics like the Kullback-Leibler divergences and Bayesian Model Dimensionalities can be used to examine the constraining power of different experiments and how we can perform efficient joint analysis by taking advantage of marginal prior and likelihood emulators. We package our multipurpose code up in the pip-installable code margarine for use in the wider scientific community.

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arXiv2023

Joint analysis constraints on the physics of the first galaxies with low frequency radio astronomy data

The first billion years of cosmic history remains largely unobserved. We demonstrate, using a novel machine learning technique, how combining upper limits on the spatial fluctuations in the 21-cm signal with observations of the sky-averaged 21-cm signal from neutral hydrogen can improve our understanding of this epoch. By jointly analysing data from SARAS3 (redshift $z\approx15-25$) and limits from HERA ($z\approx8$ and $10$), we show that such a synergetic analysis provides tighter constraints on the astrophysics of galaxies 200 million years after the Big Bang than can be achieved with the individual data sets. Although our constraints are weak, this is the first time data from a sky-averaged 21-cm experiment and power spectrum experiment have been analysed together. In synergy, the two experiments leave only $64.9^{+0.3}_{-0.1}$% of the explored broad theoretical parameter space to be consistent with the joint data set, in comparison to $92.3^{+0.3}_{-0.1}$% for SARAS3 and $79.0^{+0.5}_{-0.2}$% for HERA alone. We use the joint analysis to constrain star formation efficiency, minimum halo mass for star formation, X-ray luminosity of early emitters and the radio luminosity of early galaxies. The joint analysis disfavours at 68% confidence a combination of galaxies with X-ray emission that is $\lesssim 33$ and radio emission that is $\gtrsim 32$ times as efficient as present day galaxies. We disfavour at $95$% confidence scenarios in which power spectra are $\geq126$ mK$^{2}$ at $z=25$ and the sky-averaged signals are $\leq-277$ mK.

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