Browsing by Author "Mukherjee, Pia"

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CMB Anisotropy Constraints on Flat-Lambda and Open CDM Cosmogonies from DMR, UCSB South Pole, Python, ARGO, MAX, White Dish, OVRO, and SuZIE Data
(2011-07-06) Mukherjee, Pia; Ken, Ganga; Ratra, Bharat; et al.
We use joint likelihood analyses of combinations of ﬁfteen cosmic microwave back- ground (CMB) anisotropy data sets from the DMR, UCSB South Pole 1994, Python I–III, ARGO, MAX 4 and 5, White Dish, OVRO, and SuZIE experiments to constrain cosmogonies. We consider open and spatially-ﬂat-Λ cold dark matter cosmogonies, with nonrelativistic-mass density parameter Ω0 in the range 0.1–1, baryonic-mass den- sity parameter ΩB in the range (0.005–0.029)h−2 , and age of the universe t0 in the range (10–20) Gyr. Marginalizing over all parameters but Ω0, the data favor Ω0 ≃ 0.9–1 (0.4–0.6) ﬂat- Λ (open) models. The range in deduced Ω0 values is partially a consequence of the diﬀerent combinations of smaller-angular-scale CMB anisotropy data sets used in the analyses, but more signiﬁcantly a consequence of whether the DMR quadrupole moment is accounted for or ignored in the analysis. While the open model is diﬃcult to reconcile with the results of less exact analyses of more recent CMB anisotropy data, the lower values of Ω0 found in this case are more easily reconciled with dynamical estimates of this parameter. For both ﬂat-Λ and open models, after marginalizing over all other parameters, a lower ΩBh2 ≃ 0.005–0.009 is favored. This is also marginally at odds with estimates from more recent CMB anisotropy data and some estimates from standard nucleosynthesis theory and observed light element abundances. For both sets of models a younger universe with t0 ≃ 12–15 Gyr is favored, consistent with other recent non- CMB indicators. We emphasize that since we consider only a small number of data sets, these results are tentative. More importantly, the analyses here do not rule out the currently favored ﬂat-Λ model with Ω0 ∼ 0.3, nor the larger ΩBh2 values favored by some other data.
Galactic foreground constraints from the Python V cosmic microwave background anisotropy data
(2011-07-05) Mukherjee, Pia; Coble, Kim; Dragovan, Mark
We constrain Galactic foreground contamination of the Python V cosmic microwave background anisotropy data by cross correlating it with foreground contaminant emis- sion templates. To model foreground emission we use 100 and 12 µm dust templates and two point source templates based on the PMN survey. The analysis takes account of inter-modulation correlations in 8 modulations of the data that are sensitive to a large range of angular scales and also densely sample a large area of sky. As a conse- quence the analysis here is highly constraining. We ﬁnd little evidence for foreground contamination in a analysis of the whole data set. However, there is indication that foregrounds are present in the data from the larger-angular-scale modulations of those Python V ﬁelds that overlap the region scanned earlier by the UCSB South Pole 1994 experiment. This is an independent consistency cross-check of ﬁndings from the South Pole 1994 data.
OVRO CMB anisotropy measurement constraints on flat - ^ and open CDM cosmogonies
(2012-03-13) Mukherjee, Pia; Souradeep, Tarun; Ratra, Bharat; et al.
We use Owens Valley Radio Observatory (OVRO) cosmic microwave backgroun (CMB) anisotropy data to constrain cosmological parameters. We account for th OVRO beamwidth and calibration uncertainties, as well as the uncertainty induced b the removal of non-CMB foreground contamination. We consider open and spatially ﬂat-Λ cold dark matter cosmogonies, with nonrelativistic-mass density parameter Ω0 the range 0.1–1, baryonic-mass density parameter ΩB in the range (0.005–0.029)h− and age of the universe t0 in the range (10–20) Gyr. Marginalizing over all paramete but Ω0, the OVRO data favors an open (spatially-ﬂat-Λ) model with Ω0 ≃ 0.33 (0.1 At the 2 σ conﬁdence level model normalizations deduced from the OVRO data a mostly consistent with those deduced from the DMR, UCSB South Pole 1994, Pytho I-III, ARGO, MAX 4 and 5, White Dish, and SuZIE data sets.