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Fiona McCarthy

Publications and source records attributed to Fiona McCarthy.

At least 19 recordsLinked to original sources
arXiv2026

Characterising the epoch of reionisation using the cross-correlation of the kSZ effect and CMB lensing

We investigate the cross-correlation of the kinematic Sunyaev-Zeldovich (kSZ) effect with lensing of the cosmic microwave background (CMB) as a probe of the epoch of reionisation. During reionisation, bubbles of ionised electrons form around overdensities, generating temperature perturbations in the CMB via the kSZ effect, which correlate with the projected matter density field probed by CMB lensing. We demonstrate using AMBER simulations that this effect can be probed via cross-correlating the squared kSZ field with the CMB lensing potential, and that the signal is sensitive to the duration and midpoint of reionisation. We forecast that for a Simons Observatory-like experiment with 5$\mu$K-arcmin white noise, covering 40% of the sky, the signal could be marginally detected at $S/N$ = 2 to 3. Meanwhile, a futuristic experiment like CMB-HD could provide a measurement of $S/N \sim 50$, yielding informative constraints on reionisation scenarios. We investigate potential challenges in measuring the signal and explore mitigation for each: contamination from extragalactic foregrounds at low redshift, contamination of the kSZ-squared estimator by lensing, and other estimator biases.

astro-ph.CO↗
arXiv2026

Single Frequency CMB Foreground Removal with Inter-scale Machine Learning

Accurate measurements of Cosmic Microwave Background (CMB) B-mode polarization, a key probe of inflationary physics, are hindered by complex Galactic dust foregrounds. Traditional foreground removal with Internal Linear Combination (ILC) fully preserves the primordial signal but requires multi-frequency data and is limited to two-point statistics. We present a novel way to estimate and remove foregrounds at single frequency using signal-preserving machine learning that leverages inter-scale correlations. Using the DustFilaments simulations, we train CNNs to reconstruct large-scale foregrounds ($\ell < 200$) from small-scales ($\ell > 200$). We quantify the effectiveness of foreground removal with the residual foreground power, $f_{\rm{resid}}$, which gives the fraction of foreground power remaining after removal. Predictions using only small-scale $B$-modes achieve $f_{\rm{resid}}\simeq 0.704$, while adding temperature and $E$-modes decreases it to $f_{\rm{resid}} \simeq 0.376$. These results are still higher than the spatial ILC, which leverages multi-frequency data at Simons-Observatory-like frequencies. However, a hybrid network that uses both multi-frequency and inter-scale correlations attains $f_{\rm{resid}}=4.71\times10^{-4}$ when using $B$-mode inputs alone, and $3.62\times10^{-4}$ when using temperature and $E/B$-mode inputs. This network achieves a residual power of $\sim 7\times$ lower than ILC, while inheriting ILC's signal-preserving property. This is $\sim 2$--$3\times$ lower than a network that only uses multi-frequency inputs, demonstrating that correlations across scale are not redundant with correlations across frequency and that our techniques are complementary to multi-frequency foreground removal. However, this is achieved only for DustFilments and network generalization across simulations remains a key challenge for robust ML-based foreground removal. (abridged)

astro-ph.CO↗
arXiv2026

New constraints on primordial non-Gaussianity from large-scale cross-correlations of CMB lensing and the cosmic infrared background

We present new constraints on the local-type primordial non-Gaussianity parameter, $f_\mathrm{NL}^\mathrm{local}$, through analysis of the scale-dependent bias effect on the cosmic infrared background (CIB). To avoid biases from galactic dust contamination on large scales, we use cross-correlations between the CIB and Planck cosmic microwave background (CMB) lensing maps to constrain non-Gaussianity. Our measurement employs new dust-cleaned CIB maps that have been designed to be unbiased on large scales, which allows us to improve our constraining power on $f_\mathrm{NL}^\mathrm{local}$ by a factor of $\sim 2$ over previous CIB analyses. We derive a constraint of $f_\mathrm{NL}^\mathrm{local}=43 \pm 23$, matching the precision of the tightest existing constraints from cross-correlation methods. Consistency- and null-tests demonstrate that our results are robust to modeling assumptions and residual dust contamination.

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arXiv2026

Estimation and mitigation of foregrounds in projected kSZ velocity reconstruction

The kSZ effect has recently emerged as a powerful probe for precision cosmology through its ability to reconstruct the large-scale velocity field. In particular, the kSZ-reconstructed velocity-galaxy cross-correlation is sensitive to signatures of primordial non-Gaussianity through its imprint on the galaxy bias. The kSZ velocity reconstruction is performed using small-scale information from CMB temperature and galaxy overdensities. As the sensitivity of these measurements improves, systematic effects such as extragalactic foreground contamination present in CMB maps become increasingly important. We present a study of foreground biases to the kSZ-reconstructed velocity-galaxy cross-correlation. We derive the relevant foreground contributions from the thermal Sunyaev-Zel'dovich effect and the cosmic infrared background, modeling them using a halo model description of the dominant one- and two-halo terms. We compare our analytic predictions to measurements obtained using ACT DR6 temperature maps and DESI Legacy Imaging Survey galaxies, finding qualitative agreement. We introduce a parity-odd estimator constructed from antisymmetric combinations of tomographic velocity-galaxy correlations and show analytically that, under the Limber approximation, this estimator entirely cancels the foreground contamination while preserving the full cosmological signal without loss of signal-to-noise. Finally, we apply this parity-odd estimator to the data combination mentioned above and show that the fit to the velocity-galaxy correlation is dramatically improved compared to the analysis without mitigation; our estimator detects the signal at 11$\sigma$, with an amplitude consistent with recent studies.

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arXiv2025

Self-consistent secondary cosmic microwave background anisotropies and extragalactic foregrounds in the FLAMINGO simulations

Secondary anisotropies in the cosmic microwave background (CMB) contain information that can be used to test both cosmological models and models of galaxy formation. Starting from lightcone-based HEALPix maps and catalogues, we present a new set of mock CMB maps constructed in a self-consistent manner from the FLAMINGO suite of cosmological hydrodynamical simulations, including CMB lensing, thermal and kinetic Sunyaev-Zeldovich effects, cosmic infrared background, radio point source and anisotropic screening maps. We show that these simulations reproduce a wide range of observational constraints. We also compare our simulations with previous predictions based on dark matter-only simulations which generally model the secondary anisotropies independently from one another, concluding that our hydrodynamical simulation mocks perform at least as well as previous mocks in matching the observations whilst retaining self-consistency in the predictions of the different components. Using the model variations in FLAMINGO, we further explore how the signals depend on cosmology and feedback modelling, and we predict cross-correlations between some of the signals that differ significantly from those in previous mocks. The mock CMB maps should provide a valuable resource for exploring correlations between different secondary anisotropies and other large-scale structure tracers, and can be applied to forecasts for upcoming surveys.

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arXiv2025

The Atacama Cosmology Telescope: Cross-correlation of kSZ and continuity equation velocity reconstruction with photometric DESI LRGs

Over the last year, kinematic Sunyaev--Zel'dovich (kSZ) velocity reconstruction -- the measurement of the large-scale velocity field using the anisotropic statistics of the small-scale kSZ-galaxy overdensity correlation -- has emerged as a statistically significant probe of the large-scale Universe. In this work, we perform a 2-dimensional tomographic reconstruction using ACT DR6 CMB data and DESI legacy luminous red galaxies (LRGs). We measure the cross-correlation of the kSZ-reconstructed velocity $v^{\mathrm{kSZ}}$ with the velocity inferred from the continuity equation applied to the DESI LRGs $v^{\mathrm{cont}}$ at the $\sim 10 \sigma$ level, detecting the signal with an amplitude with respect to our theory of $b_v = 0.339\pm 0.034$. We fit a scale-dependent galaxy bias model to our measurement in order to constrain local primordial non-Gaussianity $f_{\mathrm{NL}}^{\mathrm{loc}}$, finding {$f_{\mathrm{NL}}^{\mathrm{loc}}=-180^{+61}_{-86}$} at 67\% confidence, with $f_{\mathrm{NL}}^{\mathrm{loc}}$ consistent with zero at 95\% confidence. We also measure an auto spectrum at $2.1\sigma$ significance which provides a constraint on $b_v$ of $b_v=0.26_{-0.05}^{+0.11}$, which is consistent with the measurement from the cross spectrum. Our combined measurement is $b_v=0.33\pm0.03$, an $11\sigma$ measurement. We find a good fit of our model to the data in all cases. Finally, we use different ACT frequency combinations to explore foreground contamination, finding no evidence for foreground contamination in our velocity cross correlation. We compare to a similar measurement where $v^{\mathrm{kSZ}}$ is directly cross correlated with the large-scale galaxy field, and find signs of foreground contamination which is contained in the equal-redshift spectra.

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arXiv2025

CMB component-separated power spectrum estimation by Spectral Internal Linear Combination (SpILC)

Component separation methods mitigate the cross-contamination between different extragalactic and galactic contributions to cosmic microwave background (CMB) data. This is often done by linearly combining CMB maps from different frequency channels using internal linear combination (ILC) methods. We demonstrate that deriving power spectrum estimators directly by linearly combining auto- and cross-spectra instead of maps allows us to obtain a different constrained-optimization problem that allows fewer (deprojection) constraint equations than combining at map level using the constrained ILC method. Through simulations, we show that our Spectral internal linear combination (SpILC) produces CMB power spectrum estimators with more than 7 times smaller errorbars than constrained ILC (with thermal Sunyaev-Zel'dovich and cosmic infrared background deprojections) at $\ell\gtrsim 4000$ for Simons Observatory-like observations. Spectral ILC outperforms constrained ILC methods when some modeled components are spatially uncorrelated, e.g. the primary CMB is uncorrelated with foregrounds, and the difference in performance is most significant at noise-dominated scales. More generally, our work shows that component-separated maps with foreground deprojections do not necessarily produce minimum-variance two-or-higher-point estimators.

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arXiv2025

The Atacama Cosmology Telescope: High-redshift measurement of structure growth from the cross-correlation of Quaia quasars and CMB lensing from ACT DR6 and $\textit{Planck}$ PR4

We measure the amplitude of matter fluctuations over a wide range of redshifts by combining CMB lensing observations from ACT DR6 and $\textit{Planck}$ PR4 with the overdensity of quasars from Quaia, a $\textit{Gaia}$ and $\textit{unWISE}$ quasar catalog. Our analysis includes the CMB lensing power spectrum from ACT DR6, the auto-correlation of two Quaia quasar samples centered at $z \simeq 1.0$ and $z \simeq 2.1$, and their cross-correlations with CMB lensing from both ACT DR6 and $\textit{Planck}$ PR4. By performing a series of contamination and systematic null tests, we find no evidence for contamination in the lensing maps, contrary to what was suggested in previous Quaia cross-correlation analyses using $\textit{Planck}$ PR4 CMB lensing data. From the joint analysis of the quasar auto- and cross-correlations with CMB lensing, and including BOSS BAO data to break the degeneracy between $\Omega_m$ and $\sigma_8$, we obtain $\sigma_8 = 0.802^{+0.045}_{-0.057}$, consistent with $\Lambda$CDM predictions from $\textit{Planck}$ primary CMB measurements. Combining the CMB lensing auto-spectrum with the cross-correlation measurement improves the constraint on $\sigma_8$ by $12\%$ relative to the lensing auto-spectrum alone, yielding $\sigma_8 = 0.804 \pm 0.013$. This dataset combination also enables a reconstruction of structure growth across redshifts. We infer a $12\%$ constraint on the amplitude of matter fluctuations at $z > 3$, with a measurement at the median redshift of the signal of $\sigma_8(\tilde{z}=5.1) = 0.146^{+0.021}_{-0.014}$, consistent with $\textit{Planck}$ at the $1.4\sigma$ level. These results provide one of the highest redshift constraints on the growth of structure to date.

astro-ph.CO↗
arXiv2025

CLASS_SZ II: Notes and Examples of Fast and Accurate Calculations of Halo Model, Large Scale Structure and Cosmic Microwave Background Observables

These notes are very much work-in-progress and simply intended to showcase, in various degrees of details (and rigour), some of the cosmology calculations that class_sz can do. We describe the class_sz code in C, Python and Jax. Based on the Boltzmann code class, it can compute a wide range of observables relevant to current and forthcoming CMB and Large Scale Structure surveys. This includes galaxy shear and clustering, CMB lensing, thermal and kinetic Sunyaev and Zeldovich observables, Cosmic Infrared Background, cross-correlations and three-point statistics. Calculations can be done either within the halo model or the linear bias model. For standard $\Lambda$CDM cosmology and extensions, class_sz uses high-accuracy cosmopower emulators of the CMB and matter power spectrum to accelerate calculations. With this, along with efficient numerical integration routines, most class_sz output can be obtained in less than 500 ms (CMB $C_\ell$'s or matter $P(k)$ take $\mathcal{O}(1\mathrm{ms})$), allowing for fast or ultra-fast parameter inference analyses. Parts of the calculations are "jaxified", so the software can be integrated into differentiable pipelines.

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arXiv2025

The Power Spectrum of the Thermal Sunyaev-Zeldovich Effect

The power spectrum of unresolved thermal Sunyaev-Zeldovich (tSZ) clusters is extremely sensitive to the amplitude of the matter fluctuations. This paper present an analysis of the tSZ power spectrum using temperature power spectra of the cosmic microwave background (CMB) rather than maps of the Compton y-parameter. Our analysis is robust and insensitive to the cosmic infrared background. Using data from Planck, and higher resolution CMB data from the Atacama Cosmology Telescope and the South Pole Telescope, we find strong evidence that the tSZ spectrum has a shallower slope and a much lower amplitude at multipoles l > 2000$compared to the predictions of the FLAMINGO hydrodynamic simulations of the LCDM cosmology. Recent results on CMB lensing, cross-correlations of CMB lensing with galaxy surveys and full shape analysis of galaxies and quasars from the Dark Energy Spectroscopic Instrument suggests that this discrepancy cannot be resolved by lowering the amplitude of the matter fluctuations. An alternative possibility is that the impact of baryonic feedback in the FLAMINGO simulations is underestimated.

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arXiv2024

The Atacama Cosmology Telescope: A measurement of galaxy cluster temperatures through relativistic corrections to the thermal Sunyaev-Zeldovich effect

The high electron temperature in galaxy clusters ($>1\,$keV or $>10^7\,$K) leads to corrections at the level of a few percent in their thermal Sunyaev-Zeldovich effect signatures. Both the size and frequency dependence of these corrections, which are known as relativistic temperature corrections, depend upon the temperature of the objects. In this work we exploit this effect to measure the average temperature of a stack of Compton-$y$ selected clusters. Specifically, we apply the "spectroscopic method" and search for the temperature that best fits the clusters' signal measured at frequencies from 30 to 545 GHz by the Atacama Cosmology Telescope and Planck satellite. We measure the average temperature of clusters detected in the ACT maps to be $8.5\pm 2.4\,$keV, with an additional systematic error of comparable amplitude dominated by passband uncertainty. Upcoming surveys, such as the Simons Observatory and CMB-S4, have the potential to dramatically improve upon these measurements and thereby enable precision studies of cluster temperatures with millimeter observations. The key challenge for future observations will be mitigating instrumental systematic effects, which already limit this analysis.

astro-ph.CO↗
arXiv2024

The Atacama Cosmology Telescope: Large-scale velocity reconstruction with the kinematic Sunyaev--Zel'dovich effect and DESI LRGs

The kinematic Sunyaev--Zel'dovich (kSZ) effect induces a non-zero density-density-temperature bispectrum, which we can use to reconstruct the large-scale velocity field from a combination of cosmic microwave background (CMB) and galaxy density measurements, in a procedure known as ``kSZ velocity reconstruction''. This method has been forecast to constrain large-scale modes with future galaxy and CMB surveys, improving their measurement beyond what is possible with the galaxy surveys alone. Such measurements will enable tighter constraints on large-scale signals such as primordial non-Gaussianity, deviations from homogeneity, and modified gravity. In this work, we demonstrate a statistically significant measurement of kSZ velocity reconstruction for the first time, by applying quadratic estimators to the combination of the ACT DR6 CMB+kSZ map and the DESI LRG galaxies (with photometric redshifts) in order to reconstruct the velocity field. We do so using a formalism appropriate for the 2-dimensional projected galaxy fields that we use, which naturally incorporates the curved-sky effects important on the largest scales. We find evidence for the signal by cross-correlating with an external estimate of the velocity field from the spectroscopic BOSS survey and rejecting the null (no-kSZ) hypothesis at $3.8\sigma$. Our work presents a first step towards the use of this observable for cosmological analyses.

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arXiv2024

Constraints on axions from patchy screening of the cosmic microwave background

The resonant conversion of cosmic microwave background (CMB) photons into axions within large-scale structure induces an anisotropic spectral distortion in CMB temperature maps. Applying state-of-the-art foreground cleaning techniques to $\textit{Planck}$ CMB observations, we construct maps of axion-induced "patchy screening" of the CMB. We cross-correlate these maps with data from the $\textit{unWISE}$ galaxy survey and find no evidence of axions. We constrain the axion-photon coupling, $g_{aγγ} \lesssim 2 \times 10^{-12}~{\rm GeV}^{-1}$, at the 95% confidence level for axion masses in the range $10^{-13}~{\rm eV} \lesssim m_a \lesssim 10^{-12}~{\rm eV}$. These constraints are competitive with the tightest astrophysical axion limits in this mass range and are inferred from robust population-level statistics, which makes them complementary to existing searches that rely on modeling of individual systems.

astro-ph.CO↗
arXiv2024

Signal-preserving CMB component separation with machine learning

Analysis of microwave sky signals, such as the cosmic microwave background, often requires component separation with multi-frequency methods, where different signals are isolated by their frequency behaviors. Many so-called "blind" methods, such as the internal linear combination (ILC), make minimal assumptions about the spatial distribution of the signal or contaminants, and only assume knowledge of the frequency dependence of the signal. The ILC is a minimum-variance linear combination of the measured frequency maps. In the case of Gaussian, statistically isotropic fields, this is the optimal linear combination, as the variance is the only statistic of interest. However, in many cases the signal we wish to isolate, or the foregrounds we wish to remove, are non-Gaussian and/or statistically anisotropic (in particular for Galactic foregrounds). In such cases, it is possible that machine learning (ML) techniques can be used to exploit the non-Gaussian features of the foregrounds and thereby improve component separation. However, many ML techniques require the use of complex, difficult-to-interpret operations on the data. We propose a hybrid method whereby we train an ML model using only combinations of the data that $\textit{do not contain the signal}$, and combine the resulting ML-predicted foreground estimate with the ILC solution to reduce the error from the ILC. We demonstrate our methods on simulations of extragalactic temperature and Galactic polarization foregrounds, and show that our ML model can exploit non-Gaussian features, such as point sources and spatially-varying spectral indices, to produce lower-variance maps than ILC - eg, reducing the variance of the B-mode residual by factors of up to 5 - while preserving the signal of interest in an unbiased manner. Moreover, we often find improved performance when applying our model to foreground models on which it was not trained.

astro-ph.CO↗
arXiv2024

Dark photon limits from patchy dark screening of the cosmic microwave background

Dark photons that kinetically mix with the Standard Model photon give rise to new spectral anisotropies (patchy dark screening) in the cosmic microwave background (CMB) due to conversion of photons to dark photons within large-scale structure. We utilize predictions for this patchy dark screening signal to provide the tightest constraints to date on the dark photon kinetic mixing parameter ($\varepsilon \lesssim 4\times 10^{-8}$ (95% confidence level)) over the mass range $10^{-13} \,\, {\rm eV} \lesssim m_{A^\prime} \lesssim 10^{-11}$ eV, almost an order of magnitude stronger than previous limits, by applying state-of-the-art component separation techniques to the cross-correlation of $\textit{Planck}$ CMB and $\textit{unWISE}$ galaxy survey data.

hep-ph↗
arXiv2024

Large-scale galactic-dust-cleaned cosmic infrared background maps from \textit{Planck} PR4 and HI4PI with \texttt{pyilc}

The cosmic infrared background (CIB) traces star-forming galaxies throughout cosmic history, with emission peaking at $z\sim1-2$. CIB anisotropies are present at the far-infrared frequencies observed by cosmic microwave background (CMB) experiments such as $\textit{Planck}$. These contain a lot of astrophysical and cosmological information, but are hard to separate from the dust emission in our own Milky Way galaxy, especially on large scales where the Milky Way contamination severely dominates. This galactic component is often cleaned using information from other galactic tracers such as neutral hydrogen (HI). In this work we use HI data from the HI4PI survey to clean the 353, 545, and 857 GHz $\textit{Planck}$ NPIPE single-frequency maps using a needlet internal linear combination (NILC) method, with $\texttt{pyilc}$. This allows us to preserve the CIB anisotropy information on $\textit{all}$ scales, while reducing the variance sourced by the galactic contamination. We also create a NILC CMB map from the $\textit{Planck}$ NPIPE data, to subtract a CMB template from the 353 GHz map. Our resulting CIB maps are appropriate for cross-correlation studies with cosmological tracers such as CMB lensing maps down to very low $\ell$ ($\ell\sim10$), while achieving similar performance to previous works on intermediate scales. The use of the NPIPE data additionally allows us to achieve lower instrumental noise in the maps than in previous works. We use our maps, in combination with the $\textit{Planck}$ NPIPE CMB lensing reconstruction, to measure the CIB-CMB lensing cross correlation down to $\ell\sim10$. We make various versions of our maps publicly available to the community for further use in cross-correlation studies, along with a script (and the intermediate data products required) to produce dust-cleaned CIB maps on an arbitrary region of sky.

astro-ph.CO↗
arXiv2024

Component-separated, CIB-cleaned thermal Sunyaev--Zel'dovich maps from $\textit{Planck}$ PR4 data with a flexible public needlet ILC pipeline

We use the full-mission $\textit{Planck}$ PR4 data to construct maps of the thermal Sunyaev$--$Zel'dovich effect (Compton-$y$ parameter) in our Universe. To do so, we implement a custom needlet internal linear combination (NILC) pipeline in a Python package, $\texttt{pyilc}$, which we make publicly available. We publicly release our Compton-$y$ maps, which we construct using various constrained ILC ("deprojection") options in order to minimize contamination from the cosmic infrared background (CIB) in the reconstructed signal. In particular, we use a moment-based deprojection which minimizes sensitivity to the assumed frequency dependence of the CIB. Our code $\texttt{pyilc}$ performs needlet or harmonic ILC on mm-wave sky maps in a flexible manner, with options to deproject various components on all or some scales. We validate our maps and compare them to the official $\textit{Planck}$ 2015 $y$-map, finding that we obtain consistent results on large scales and 10-20$\%$ lower noise on small scales. We expect that these maps will be useful for many auto- and cross-correlation analyses; in a companion paper, we use them to measure the tSZ -- CMB lensing cross-correlation. We anticipate that $\texttt{pyilc}$ will be useful both for data analysis and for pipeline validation on simulations to understand the propagation of foreground components through a full NILC pipeline.

astro-ph.CO↗
arXiv2024

Constraints on Dark Matter-Dark Energy Scattering from ACT DR6 CMB Lensing

The predicted present-day amplitude of matter fluctuations based on cosmic microwave background (CMB) anisotropy data has sometimes been found discrepant with more direct measurements of late-time structure. This has motivated many extensions to the standard cosmological model, including kinetic interactions between dark matter and dark energy that introduce a drag force slowing the growth of structure at late times. Exploring this scenario, we develop a model for quasi-linear scales in the matter power spectrum by calculating the critical overdensity in the presence of this interaction and a varying dark energy equation of state. We explicitly avoid modeling or interpretation of data on non-linear scales in this model (such as use of $Λ$CDM-calibrated priors), which would require numerical simulations. We find that the presence of the drag force hinders halo formation, thus increasing the deviation from $Λ$CDM in the mildly non-linear regime. We use CMB lensing observations from the sixth data release of the Atacama Cosmology Telescope up to $L=1250$ (in combination with Planck, Sloan Digital Sky Survey, and 6dFGS data) to derive the strongest constraints to date on the amplitude of the drag term, finding the dimensionless interaction strength $Γ_\mathrm{DMDE}/(H_0ρ_\mathrm{c})<0.831\; (2.81)$ at the 68\% (95\%) confidence level. The inclusion of non-linear corrections improves our constraints by about 35\% compared to linear theory. Our results do not exclude the best-fit values of $Γ_\mathrm{DMDE}$ found in previous studies using information from galaxy weak lensing, though we find no statistical preference for the dark matter-dark energy kinetic interactions over $Λ$CDM. We implement our model in a publicly available fork of the Boltzmann code CLASS at https://github.com/fmccarthy/Class_DMDE.

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