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We use time-domain simulations of Jupiter observations to test and develop a beam reconstruction pipeline for the Simons Observatory Small Aperture Telescopes. The method relies on a mapmaker that estimates and subtracts correlated atmospheric noise and a beam fitting code designed to compensate for the bias caused by the mapmaker. We test our reconstruction performance for four different frequency bands against various algorithmic parameters, atmospheric conditions, and input beams. We additionally show the reconstruction quality as a function of the number of available observations and investigate how different calibration strategies affect the beam uncertainty. For all of the cases considered, we find good agreement between the fitted results and the input beam model within an ∼1.5% error for a multipole range ℓ = 30–700 and an ∼0.5% error for a multipole range ℓ = 50–200. We conclude by using a harmonic-domain component separation algorithm to verify that the beam reconstruction errors and biases observed in our analysis do not significantly bias the Simons Observatory r-measurement

The history of the Universe is described by the Standard Model of Cosmology. This is commonly referred to as the Lambda-CDM model, as it describes the evolution of the Universe in terms of its main components, Dark energy (Lambda) and Cold Dark Matter. Great progress in precision Cosmology, particularly due to the measurements of the Cosmic Microwave Background (CMB) radiation, has allowed to establish the Standard Lambda-CDM Model to describe the evolution of the Universe. The forthcoming CMB observatories will record data across a range of frequencies and angular scales in order to measure the CMB B-modes. These measurements will support a large number of science goals, providing direct evidence for theories of inflation, whilst also measuring the properties of neutrinos, and further constraining cosmological parameters to enable multiple probes of the growth rate of structure of the Universe.These outstanding science goals require exceptional instrument capabilities. In particular, sub-kelvin cryogenic temperatures are needed to support the required sensitivities of the receivers. This thesis reports the development of several cryogenic subsystems which support CMB B-modes observations. These have been developed to support the sub-kelvin operation of the receiver and the preliminary detector and readout testing.Optimisation of a 4He sorption cooler with high capacity has been reported, which operates at 1 K the large optical throughput of the QUBIC (the Q & U Bolometric Interferometer) for Cosmology receiver. Alongside this, novel convective heat switches have been characterised and tested, which precool the 1 K stage and provide isolation whilst the cooler is recycled. A design for a double stage 3He/4He sorption cooler has been developed which supports testing of SQUIDs (Superconducting Quantum Interference Devices) readout at 350 mK within a dedicated magneto-optical cryostat. Furthermore, a novel Miniature Dilution Refrigerator (MDR) has been developed to support the fast-turnaround operation of detector wafer test cryostats. This has been originally designed to support the increasing production of arrays of transition edge sensor bolometer based detectors for the Simons Observatory, whose focal planes are operated at 100 mK.

In this paper we present the European Low Frequency Survey (ELFS), a project that will enable the detection of primordial B-mode polarization by measuring the Galactic and extra-Galactic foregrounds in the 5– 120 GHz frequency window. Indeed, the main difficulty in measuring the Bmode polarization comes not just from its sheer faintness, but from the fact that many other objects in the Universe also emit polarized microwaves, which mask the faint CMB signal. The first stage of this project will be carried out in synergy with the Simons Array (SA) collaboration, installing a 5.5–11 GHz coherent receiver at the focus of one of the three 3.5m SA telescopes in Atacama, Chile (“ELFS on SA”). The receiver will be equipped with a fully digital backend based on the latest Xilinx RF System-on-Chip devices that will provide frequency resolution of 1MHz across the whole observing band, allowing us to clean the scientific signal from unwanted radio frequency interference, particularly from low-Earth orbit satellite mega-constellations. This paper reviews the scientific motivation for ELFS and its instrumental characteristics, and provides an update on the development of ELFS on SA.

Parity-violating physics in the Universe can generate correlations between the Cosmic Microwave Background (CMB) \\(E\\)- and \\(B\\)-modes, but detecting such signals requires extremely accurate calibration of instruments. We describe a data-driven method to calibrate the relative polarisation angle between CMB experiments using cross-correlations of observations over a common sky region. Unlike standard self-calibration approaches, this method does not assume vanishing isotropic cosmic birefringence or primordial \\(EB\\) correlations when estimating the relative misalignment angle, and therefore preserves sensitivity to parity-violating physics. As a proof of concept, we forecast the performance of this method using the Simons Observatory (SO) Small Aperture Telescopes (SATs) as a calibrated reference. If they can be calibrated to an uncertainty of \\(0.08^\\), as anticipated from the SO wire grid calibration system, we show that the SO Large Aperture Telescope and Planck could be calibrated to uncertainties of \\(0.10^\\) and \\(0.17^\\), respectively, at \\( 145\\) GHz. This approach relies on the availability of at least one well-calibrated instrument, and provides a complementary path to improving polarisation calibration across experiments, enabling more robust searches for parity-violating physics in the CMB, such as cosmic birefringence.

The analysis of photometric large-scale structure data is often complicated by the need to account for many observational and astrophysical systematics. The elaborate models needed to describe them often introduce many ``nuisance parameters'', which can be a major inhibitor of an efficient parameter inference. In this paper we introduce an approximate method to analytically marginalise over a large number of nuisance parameters based on the Laplace approximation. We discuss the mathematics of the method, its relation to concepts such as volume effects and profile likelihood, and show that it can be further simplified for calibratable systematics by linearising the dependence of the theory on the associated parameters. We quantify the accuracy of this approach by comparing it with traditional sampling methods in the context of existing data from the Dark Energy Survey, as well as futuristic Stage-IV photometric data. The linearised version of the method is able to obtain parameter constraints that are virtually equivalent to those found by exploring the full parameter space for a large number of calibratable nuisance parameters, while reducing the computation time by a factor 3-10. Furthermore, the non-linearised approach is able to analytically marginalise over a large number of parameters, returning constraints that are virtually indistinguishable from the brute-force method in most cases, accurately reproducing both the marginalised uncertainty on cosmological parameters, and the impact of volume effects associated with this marginalisation. We provide simple recipes to diagnose when the approximations made by the method fail and one should thus resort to traditional methods. The gains in sampling efficiency associated with this method enable the joint analysis of multiple surveys, typically hindered by the large number of nuisance parameters needed to describe them.

We explore a novel analysis framework for parameter inference with large-scale CMB polarization data. Our method uses simulation-based inference combined with the needlet internal linear combination (NILC) algorithm and cross-correlation-based statistics to compress the data into a vector that is robust to model misspecification and small enough to be amenable to neural posterior estimation with normalizing flows. By leveraging this compressed data representation, our method enables the robust use of the anisotropic and non-Gaussian information in the foreground fields to more accurately separate the CMB polarization signal from these contaminants. Using an idealized ground-based experimental setup inspired by the Simons Observatory Small Aperture Telescopes, we demonstrate improved statistical constraining power for the tensor-to-scalar ratio \\(r\\) compared to the (constrained) NILC algorithm and improved robustness to complex foregrounds compared to other techniques in the literature. Trained on a relatively simple semi-analytical foreground model, the method yields unbiased \\(r\\) results across a range of PySM Galactic foreground simulations, including the high-complexity d12 model, for which we obtain \\(r=(1.09 0.27) 10^-2\\) for input \\(r=0.01\\) and sky fraction \\(f_sky = 0.21\\). We thus demonstrate the feasibility and advantages of a complete, maps-to-parameters, simulation-based analysis of large-scale CMB polarization for current ground-based observatories.

We present a transfer function-based method to estimate angular power spectra from filtered maps for cosmic microwave background (CMB) surveys. This is especially relevant for experiments targeting the faint primordial gravitational wave signatures in CMB polarisation at large scales, such as the Simons Observatory (SO) small aperture telescopes. While timestreams can be filtered to mitigate the contamination from low-frequency noise, usual methods that calculate the mode coupling at individual multipoles can be challenging for experiments covering large sky areas or reaching few-arcminute resolution. The method we present here, although approximate, is more practical and faster for larger data volumes. We validate it through the use of simulated observations approximating the first year of SO data, going from half-wave plate-modulated timestreams to maps, and using simulations to estimate the mixing of polarisation modes induced by an example of time-domain filtering. We show its performance through an example null test and with an end-to-end pipeline that performs inference on cosmological parameters, including the tensor-to-scalar ratio \\(r\\). The performance demonstration uses simulated observations at multiple frequency bands. We find that the method can recover unbiased parameters for our simulated noise levels.

The Simons Observatory (SO), a next-generation ground-based CMB experiment in its final stages of construction, will target primordial \\(B\\)-modes with unprecedented sensitivity to set tight bounds on the amplitude of inflationary gravitational waves. Aiming to infer the tensor-to-scalar ratio \\(r\\) with precision \\((r=0) 0.003\\), SO will rely on powerful component-separation algorithms to distinguish the faint primordial signal from stronger sources of large-scale \\(B\\)-modes such as Galactic foregrounds and weak gravitational lensing. We present an analysis pipeline that performs delensing and foreground cleaning simultaneously by including multifrequency CMB data and a lensing \\(B\\)-mode template in a power-spectrum-based likelihood. Here, we demonstrate this algorithm on masked SO-like simulations containing inhomogeneous noise and non-Gaussian foregrounds. The lensing convergence is reconstructed from high-resolution simulations of the CMB and external mass tracers. Using optimized pixel weights for power spectrum estimation, the target precision for SO's nominal design is achieved and delensing reduces \\((r)\\) by 27-37%, depending on foreground complexity.

We use time-domain simulations of Jupiter observations to test and develop a beam reconstruction pipeline for the Simons Observatory Small Aperture Telescopes. The method relies on a map maker that estimates and subtracts correlated atmospheric noise and a beam fitting code designed to compensate for the bias caused by the map maker. We test our reconstruction performance for four different frequency bands against various algorithmic parameters, atmospheric conditions and input beams. We additionally show the reconstruction quality as function of the number of available observations and investigate how different calibration strategies affect the beam uncertainty. For all of the cases considered, we find good agreement between the fitted results and the input beam model within a ~1.5% error for a multipole range l = 30 - 700 and an ~0.5% error for a multipole range l = 50 - 200. We conclude by using a harmonic-domain component separation algorithm to verify that the beam reconstruction errors and biases observed in our analysis do not significantly bias the Simons Observatory r-measurement.

The upcoming Simons Observatory (SO) Small Aperture Telescopes aim at observing the degree-scale anisotropies of the polarized CMB to constrain the primordial tensor-to-scalar ratio \\(r\\) at the level of \\((r=0)0.003\\) to probe models of the very early Universe. We present three complementary \\(r\\) inference pipelines and compare their results on a set of sky simulations that allow us to explore a number of Galactic foreground and instrumental noise models, relevant for SO. In most scenarios, the pipelines retrieve consistent and unbiased results. However, several complex foreground scenarios lead to a \\(>2\\) bias on \\(r\\) if analyzed with the default versions of these pipelines, highlighting the need for more sophisticated pipeline components that marginalize over foreground residuals. We present two such extensions, using power-spectrum-based and map-based methods, and show that they fully reduce the bias on \\(r\\) to sub-sigma level in all scenarios, and at a moderate cost in terms of \\((r)\\).