Search

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. [ABSTRACT FROM AUTHOR]

A key challenge in the search for primordial B -modes is the presence of polarized Galactic foregrounds, especially thermal dust emission. Power-spectrum-based analysis methods generally assume the foregrounds to be Gaussian random fields when constructing a likelihood and computing the covariance matrix. In this paper, we investigate how non-Gaussianity in the dust field instead affects CMB and foreground parameter inference in the context of inflationary B -mode searches, capturing this effect via modifications to the dust power-spectrum covariance matrix. For upcoming experiments such as the Simons Observatory, we find no dependence of the tensor-to-scalar ratio uncertainty |$\sigma (r)$| on the degree of dust non-Gaussianity or the nature of the dust covariance matrix. We provide an explanation of this result, noting that when frequency decorrelation is negligible, dust in mid-frequency channels is cleaned using high-frequency data in a way that is independent of the spatial statistics of dust. We show that our results hold also for non-zero levels of frequency decorrelation that are compatible with existing data. We find, however, that neglecting the impact of dust non-Gaussianity in the covariance matrix can lead to inaccuracies in goodness-of-fit metrics. Care must thus be taken when using such metrics to test B -mode spectra and models, although we show that any such problems can be mitigated by using only cleaned spectrum combinations when computing goodness-of-fit statistics. [ABSTRACT FROM AUTHOR]

We present an analysis of errors on the tensor-to-scalar ratio due to residual diffuse foregrounds. We use simulated observations of a cosmic microwave background (CMB) polarization satellite, the Cosmic Origins Explorer (COrE), using the specifications of the version proposed to ESA in 2010.We construct a full pipeline from microwave sky maps to r likelihood, using two models of diffuse Galactic foregrounds with different complexity and assuming component separation with varying degrees of accuracy. Our pipeline uses a linear mixture (generalized least squares) solution for component separation, and a hybrid approach for power spectrum estimation, with a quadratic maximum likelihood estimator at low ℯ s and a pseudo-Cℯ deconvolution at high ℯs. In the likelihood for r, we explore modelling foreground residuals as nuisance parameters. Our analysis aims at measuring the bias introduced in r by mismodelling the foregrounds and to determine what error is tolerable while still successfully detecting r. We find that r = 0.01 can be measured successfully even for a complex sky model and in the presence of foreground parameters error. However, the detection of r = 0.001 is a lot more challenging, as inaccurate modelling of the foreground spectral properties may result in a biased measurement of r. Once biases are eliminated, the total error on r allows setting an upper limit rather than a detection, unless the uncertainties on the foreground spectral indices are very small, i.e. equal or better than 0.5 per cent error for both dust and synchrotron. This emphasizes the need for pursuing research on component separation and foreground characterization in view of next-generation CMB polarization experiments. [ABSTRACT FROM AUTHOR]

We present a new model of the microwave sky in polarization that can be used to simulate data from cosmic microwave background polarization experiments. We exploit the most recent results from the Planck satellite to provide an accurate description of the diffuse polarized foreground synchrotron and thermal dust emission. Our model can include the two mentioned foregrounds, and also a constructed template of Anomalous Microwave Emission. Several options for the frequency dependence of the foregrounds can be easily selected, to reflect our uncertainties and to test the impact of different assumptions. Small angular scale features can be added to the foreground templates to simulate high-resolution observations. We present tests of the model outputs to show the excellent agreement with Planck and Wilkinson Microwave Anisotropy Probe (WMAP) data. We determine the range within which the foreground spectral indices can be varied to be consistent with the current data. We also show forecasts for a high-sensitivity, high-resolution full-sky experiment such as the Cosmic ORigin Explorer. Our model is released as a PYTHON script that is quick and easy to use, available at http://www.jb.man.ac.uk/chervias. [ABSTRACT FROM AUTHOR]