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Creators/Authors contains: "Dunkley, Jo"

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  1. ABSTRACT We use the emulation framework CosmoPower to construct and publicly release neural network emulators of cosmological observables, including the cosmic microwave background (CMB) temperature and polarization power spectra, matter power spectrum, distance-redshift relation, baryon acoustic oscillation (BAO) and redshift-space distortion (RSD) observables, and derived parameters. We train our emulators on Einstein–Boltzmann calculations obtained with high-precision numerical convergence settings, for a wide range of cosmological models including ΛCDM, wCDM, ΛCDM + Neff, and ΛCDM + Σmν. Our CMB emulators are accurate to better than 0.5 per cent out to ℓ = 104, which is sufficient for Stage-IV data analysis, and our P(k) emulators reach the same accuracy level out to $$k=50 \, \, \mathrm{Mpc}^{-1}$$, which is sufficient for Stage-III data analysis. We release the emulators via an online repository (CosmoPower Organisation), which will be continually updated with additional extended cosmological models. Our emulators accelerate cosmological data analysis by orders of magnitude, enabling cosmological parameter extraction analyses, using current survey data, to be performed on a laptop. We validate our emulators by comparing them to class and camb and by reproducing cosmological parameter constraints derived from Planck TT, TE, EE, and CMB lensing data, as well as from the Atacama Cosmology Telescope Data Release 4 CMB data, Dark Energy Survey Year-1 galaxy lensing and clustering data, and Baryon Oscillation Spectroscopic Survey Data Release 12 BAO and RSD data. 
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  2. Upcoming imaging surveys will allow for high signal-to-noise measurements of galaxy clustering at small scales. In this work, we present the results of the Rubin Observatory Legacy Survey of Space and Time (LSST) bias challenge, the goal of which is to compare the performance of different nonlinear galaxy bias models in the context of LSST Year 10 (Y10) data. Specifically, we compare two perturbative approaches, Lagrangian perturbation theory (LPT) and Eulerian perturbation theory (EPT) to two variants of Hybrid Effective Field Theory (HEFT), with our fiducial implementation of these models including terms up to second order in the bias expansion as well as nonlocal bias and deviations from Poissonian stochasticity. We consider a variety of different simulated galaxy samples and test the performance of the bias models in a tomographic joint analysis of LSST-Y10-like galaxy clustering, galaxy-galaxy-lensing and cosmic shear. We find both HEFT methods as well as LPT and EPT combined with non-perturbative predictions for the matter power spectrum to yield unbiased constraints on cosmological parameters up to at least a maximal scale ofkmax = 0.4 Mpc-1for all samples considered, even in the presence of assembly bias. While we find that we can reduce the complexity of the bias model for HEFT without compromising fit accuracy, this is not generally the case for the perturbative models. We find significant detections of non-Poissonian stochasticity in all cases considered, and our analysis shows evidence that small-scale galaxy clustering predominantly improves constraints on galaxy bias rather than cosmological parameters. These results therefore suggest that the systematic uncertainties associated with current nonlinear bias models are likely to be subdominant compared to other sources of error for tomographic analyses of upcoming photometric surveys, which bodes well for future galaxy clustering analyses using these high signal-to-noise data. 
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  3. Abstract We present a reproduction of thePlanck2018 angular power spectra at ℓ > 30, and associated covariance matrices, for intensity and polarization maps at 100, 143 and 217 GHz. This uses a new, publicly available, pipeline that is part of thePSpipepackage. As a test case we use the same input maps, ancillary products, and analysis choices as in thePlanck2018 analysis, and find that we can reproduce the spectra to 0.1σprecision, and the covariance matrices to 10%. We show that cosmological parameters estimated from our re-derived products agree with the publicPlanckproducts to 0.1σ, providing an independent cross-check of thePlanckteam's analysis. Going forward, the publicly-available code can be easily adapted to use alternative input maps, data selections and analysis choices, for future optimal analysis ofPlanckdata with new ground-based Cosmic Microwave Background data. 
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  4. We present Weak Gravitational Lensing measurements of a sample of 157 clusters within the Kilo Degree Survey (KiDS), detected with a > 5σthermal Sunyaev-Zel’dovich (SZ) signal by the Atacama Cosmology Telescope (ACT). Using a halo-model approach, we constrained the average total cluster mass,MWL, accounting for the ACT cluster selection function of the full sample. We find that the SZ cluster mass estimateMSZ, which was calibrated using X-ray observations, is biased withMSZ/MWL = (1 − bSZ) = 0.65 ± 0.05. Separating the sample into six mass bins, we find no evidence of a strong mass dependency for the mass bias, (1 − bSZ). Adopting this ACT-KiDS SZ mass calibration would bring thePlanckSZ cluster count into agreement with the counts expected from thePlanckcosmic microwave background ΛCDM cosmological model, although it should be noted that the cluster sample considered in this work has a lower average massMSZ, uncor = 3.64 × 1014 Mcompared to thePlanckcluster sample which has an average mass in the rangeMSZ, uncor = (5.5 − 8.5)×1014 M, depending on the sub-sample used. 
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  5. ABSTRACT We have performed targeted searches of known extragalactic transient events at millimetre wavelengths using nine seasons (2013–2021) of 98, 150, and 229 GHz Atacama Cosmology Telescope (ACT) observations that mapped ∼40 per cent of the sky for most of the data volume. Our data cover 88 gamma-ray bursts (GRBs), 12 tidal disruption events (TDEs), and 203 other transients, including supernovae (SNe). We stack our ACT observations to increase the signal-to-noise ratio of the maps. In all cases but one, we do not detect these transients in the ACT data. The single candidate detection (event AT2019ppm), seen at ∼5σ significance in our data, appears to be due to active galactic nuclei activity in the host galaxy coincident with a transient alert. For each source in our search we provide flux upper limits. For example, the medians for the 95 per cent confidence upper limits at 98 GHz are 15, 18, and 16 mJy for GRBs, SNe, and TDEs, respectively, in the first month after discovery. The projected sensitivity of future wide-area cosmic microwave background surveys should be sufficient to detect many of these events using the methods described in this paper. 
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  6. Abstract The increasing statistical power of cosmic microwave background (CMB) datasets requires a commensurate effort in understanding their noise properties. The noise in maps from ground-based instruments is dominated by large-scale correlations, which poses a modeling challenge. This paper develops novel models of the complex noise covariance structure in the Atacama Cosmology Telescope Data Release 6 (ACT DR6) maps. We first enumerate the noise properties that arise from the combination of the atmosphere and the ACT scan strategy. We then prescribe a class of Gaussian, map-based noise models, including a new wavelet-based approach that uses directional wavelet kernels for modeling correlated instrumental noise. The models are empirical, whose only inputs are a small number of independent realizations of the same region of sky. We evaluate the performance of these models against the ACT DR6 data by drawing ensembles of noise realizations. Applying these simulations to the ACT DR6 power spectrum pipeline reveals a ∼ 20% excess in the covariance matrix diagonal when compared to an analytic expression that assumes noise properties are uniquely described by their power spectrum. Along with our public code,mnms, this work establishes a necessary element in the science pipelines of both ACT DR6 and future ground-based CMB experiments such as the Simons Observatory (SO). 
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  7. Abstract We present a cross-correlation analysis between 1 resolution total intensity and polarization observations from the Atacama Cosmology Telescope (ACT) at 150 and 220 GHz and 15″ mid-infrared photometry from the Wide-field Infrared Survey Explorer (WISE) over 107 12.°5 × 12.°5 patches of sky. We detect a spatially isotropic signal in the WISE×ACTTTcross-power spectrum at 30σsignificance that we interpret as the correlation between the cosmic infrared background at ACT frequencies and polycyclic aromatic hydrocarbon (PAH) emission from galaxies in WISE, i.e., the cosmic PAH background. Within the Milky Way, the Galactic dustTTspectra are generally well described by power laws inℓover the range 103<ℓ< 104, but there is evidence both for variability in the power-law index and for non-power-law behavior in some regions. We measure a positive correlation between WISE total intensity and ACTE-mode polarization at 1000 <ℓ≲ 6000 at >3σin each of 35 distinct ∼100 deg2regions of the sky, suggesting that alignment between Galactic density structures and the local magnetic field persists to subparsec physical scales in these regions. The distribution ofTEamplitudes in thisℓrange across all 107 regions is biased to positive values, while there is no evidence for such a bias in theTBspectra. This work constitutes the highest-ℓmeasurements of the Galactic dustTEspectrum to date and indicates that cross-correlation with high-resolution mid-infrared measurements of dust emission is a promising tool for constraining the spatial statistics of dust emission at millimeter wavelengths. 
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  8. Abstract Uncertain feedback processes in galaxies affect the distribution of matter, currently limiting the power of weak lensing surveys. If we can identify cosmological statistics that are robust against these uncertainties, or constrain these effects by other means, then we can enhance the power of current and upcoming observations from weak lensing surveys such as DES, Euclid, the Rubin Observatory, and the Roman Space Telescope. In this work, we investigate the potential of the electron density auto-power spectrum as a robust probe of cosmology and baryonic feedback. We use a suite of (magneto-)hydrodynamic simulations from the CAMELS project and perform an idealized analysis to forecast statistical uncertainties on a limited set of cosmological and physically-motivated astrophysical parameters. We find that the electron number density auto-correlation, measurable through either kinematic Sunyaev-Zel'dovich observations or through Fast Radio Burst dispersion measures, provides tight constraints on Ω m and the mean baryon fraction in intermediate-mass halos, f̅ bar . By obtaining an empirical measure for the associated systematic uncertainties, we find these constraints to be largely robust to differences in baryonic feedback models implemented in hydrodynamic simulations. We further discuss the main caveats associated with our analysis, and point out possible directions for future work. 
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  9. Abstract Diverse astrophysical observations suggest the existence of cold dark matter that interacts only gravitationally with radiation and ordinary baryonic matter. Any nonzero coupling between dark matter and baryons would provide a significant step towards understanding the particle nature of dark matter. Measurements of the cosmic microwave background (CMB) provide constraints on such a coupling that complement laboratory searches. In this work we place upper limits on a variety of models for dark matter elastic scattering with protons and electrons by combining large-scale CMB data from the Planck satellite with small-scale information from Atacama Cosmology Telescope (ACT) DR4 data. In the case of velocity-independent scattering, we obtain bounds on the interaction cross section for protons that are 40% tighter than previous constraints from the CMB anisotropy. For some models with velocity-dependent scattering we find best-fitting cross sections with a 2 σ deviation from zero, but these scattering models are not statistically preferred over ΛCDM in terms of model selection. 
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