Browsing by Author "Krachmalnicoff, Nicoletta"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    The Simons Observatory: Beam Characterization for the Small Aperture Telescopes
    (2024) Dachlythra, Nadia; Duivenvoorden, Adriaan J.; Gudmundsson, Jon E.; Hasselfield, Matthew; Coppi, Gabriele; Adler, Alexandre E.; Alonso, David; Azzoni, Susanna; Chesmore, Grace E.; Fabbian, Giulio; Ganga, Ken; Gerras, Remington G.; Jaffe, Andrew H.; Johnson, Bradley R.; Keating, Brian; Keskitalo, Reijo; Kisner, Theodore S.; Krachmalnicoff, Nicoletta; Lungu, Marius; Matsuda, Frederick; Naess, Sigurd; Page, Lyman; Puddu, Roberto; Puglisi, Giuseppe; Simon, Sara M.; Teply, Grant; Tsan, Tran; Wollack, Edward J.; Wolz, Kevin; Xu, Zhilei
    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 similar to 1.5% error for a multipole range l = 30-700 and an similar to 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
  • No Thumbnail Available
    Item
    The Simons Observatory: Combining cross-spectral foreground cleaning with multitracer B- mode delensing for improved constraints on inflation
    (2024) Hertig, Emilie; Wolz, Kevin; Namikawa, Toshiya; Lizancos, Anton Baleato; Azzoni, Susanna; Abril-Cabezas, Irene; Alonso, David; Baccigalupi, Carlo; Calabrese, Erminia; Challinor, Anthony; Errard, Josquin; Fabbian, Giulio; Hervias-Caimapo, Carlos; Jost, Baptiste; Krachmalnicoff, Nicoletta; Lonappan, Anto I.; Morshed, Magdy; Pagano, Luca; Sherwin, Blake
    The Simons Observatory (SO), due to start full science operations in early 2025, aims to set tight constraints on inflationary physics by inferring the tensor-to-scalar ratio r from measurements of cosmic microwave background (CMB) polarization B-modes. Its nominal design including three small-aperture telescopes (SATs) targets a precision sigma(r ( r 1 / 4 0) ) <= 0.003 without delensing. Achieving this goal and further reducing uncertainties requires a thorough understanding and mitigation of other large-scale B-mode sources such as Galactic foregrounds and weak gravitational lensing. We present an analysis pipeline aiming to estimate r by including delensing within a cross-spectral likelihood, and demonstrate it for the first time on SO-like simulations accounting for various levels of foreground complexity, inhomogeneous noise and partial sky coverage. As introduced in an earlier SO delensing paper, lensing Bmodes are synthesized using internal CMB lensing reconstructions as well as Planck-like cosmic infrared background maps and LSST-like galaxy density maps. We then extend SO's power-spectrum-based foreground- cleaning algorithm to include all auto- and cross-spectra between the lensing template and the SAT Bmodes in the likelihood function. This allows us to constrain r and the parameters of our foreground model simultaneously. Within this framework, we demonstrate the equivalence of map-based and cross-spectral delensing and use it to motivate an optimized pixel-weighting scheme for power spectrum estimation. We start by validating our pipeline in the simplistic case of uniform foreground spectral energy distributions. In the absence of primordial Bmodes, we find that the 16 statistical uncertainty on r, 6(r), ( r ) , decreases by 37% as a result of delensing. Tensor modes at the level of r 1 / 4 0.01 are successfully detected by our pipeline. Even when using more realistic foreground models including spatial variations in the dust and synchrotron spectral properties, we obtain unbiased estimates of r both with and without delensing by employing the moment-expansion method. In this case, uncertainties are increased due to the higher number of model parameters, and delensing-related improvements range between 27% and 31%. These results constitute the first realistic assessment of the delensing performance at SO's nominal sensitivity level.
  • No Thumbnail Available
    Item
    The Simons Observatory: Pipeline comparison and validation for large-scale B-modes
    (2024) Wolz, Kevin; Azzoni, Susanna; Hervias-Caimapo, Carlos; Errard, Josquin; Krachmalnicoff, Nicoletta; Alonso, David; Baccigalupi, Carlo; Baleato Lizancos, Anton; Brown, Michael L.; Calabrese, Erminia; Chluba, Jens; Dunkley, Jo; Fabbian, Giulio; Galitzki, Nicholas; Jost, Baptiste; Morshed, Magdy; Nati, Federico
    Context. The upcoming Simons Observatory Small Aperture Telescopes aim at achieving a constraint on the primordial tensor-to-scalar ratio r at the level of sigma(r = 0)less than or similar to 0.003, observing the polarized CMB in the presence of partial sky coverage, cosmic variance, inhomogeneous non-white noise, and Galactic foregrounds. Aims. We present three different analysis pipelines able to constrain r given the latest available instrument performance, and compare their predictions on a set of sky simulations that allow us to explore a number of Galactic foreground models and elements of instrumental noise, relevant for the Simons Observatory. Methods. The three pipelines employ different combinations of parametric and non-parametric component separation at the map and power spectrum levels, and use B-mode purification to estimate the CMB B-mode power spectrum. We applied them to a common set of simulated realistic frequency maps, and compared and validated them with focus on their ability to extract robust constraints on the tensor-to-scalar ratio r. We evaluated their performance in terms of bias and statistical uncertainty on this parameter. Results. In most of the scenarios the three methodologies achieve similar performance. Nevertheless, several simulations with complex foreground signals lead to a > 2 sigma 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 show two such extensions, using power-spectrum-based and map-based methods, that are able to fully reduce the bias on r below the statistical uncertainties in all foreground models explored, at a moderate cost in terms of sigma(r).