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Register a new userA Measurement of Arcminute Anisotropy in the Cosmic Microwave Background with the Sunyaev-Zeldovich Array
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Matthew K. Sharp
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We present 30 GHz measurements of the angular power spectrum of the cosmic microwave background (CMB) obtained with the Sunyaev-Zeldovich Array. The measurements are sensitive to arcminute angular scales, where secondary anisotropy from the Sunyaev-Zeldovich effect (SZE) is expected to dominate. For a broad bin centered at multipole 4066 we find 67+77-50 uK^2, of which 26+/-5 uK^2 is the expected contribution from primary CMB anisotropy and 80+/-54 uK^2 is the expected contribution from undetected radio sources. These results imply an upper limit of 155 uK^2 (95% CL) on the secondary contribution to the anisotropy in our maps. This level of SZE anisotropy power is consistent with expectations based on recent determinations of the normalization of the matter power spectrum, i.e., sigma_8~0.8.
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We report the first detection of a Sunyaev-Zeldovich (S-Z) decrement with the Arcminute Microkelvin Imager (AMI). We have made commissioning observations towards the cluster A1914 and have measured an integrated flux density of -8.61 mJy in a uv-tapered map with noise level 0.19 mJy/beam. We find that the spectrum of the decrement, measured in the six channels between 13.5-18GHz, is consistent with that expected for a S-Z effect. The sensitivity of the telescope is consistent with the figures used in our simulations of cluster surveys with AMI.
Observations from the first flight of the Medium Scale Anisotropy Measurement (MSAM) are analyzed to place limits on Gaussian fluctuations in the Cosmic Microwave Background Radiation (CMBR). This instrument chops a 30arcmin beam in a 3 position pattern with a throw of $pm40arcmin$; the resulting data is analyzed in statistically independent single and double difference datasets. We observe in four spectral channels at 5.6, 9.0, 16.5, and 22.5~icm, allowing the separation of interstellar dust emission from CMBR fluctuations. The dust component is correlated with the IRAS 100~micron map. The CMBR component has two regions where the signature of an unresolved source is seen. Rejecting these two source regions, we obtain a detection of fluctuations which match CMBR in our spectral bands of $0.6 times 10^{-5} < Delta T/T < 2.2 times 10^{-5}$ (90% CL interval) for total rms Gaussian fluctuations with correlation angle 0fdg5, using the single difference demodulation. For the double difference demodulation, the result is $1.1 times 10^{-5} < Delta T/T < 3.1 times 10^{-5}$ (90% CL interval) at a correlation angle of 0fdg3.
If the gas in filaments and halos shares the same velocity field than the luminous matter, it will generate measurable temperature anisotropies due to the Kinematic Sunyaev-Zeldovich effect. We compute the distribution function of the KSZ signal produced by a typical filament and show it is highly non-gaussian. The combined contribution of the Thermal and Kinematic SZ effects of a filament of size $Lsimeq 5$Mpc and electron density $n_esimeq 10^3m^{-3}$ could explain the cold spots of $deltasim -200mu$K on scales of 30 found in the Corona Borealis Supercluster by the VSA experiment. PLANCK, with its large resolution and frequency coverage, could provide the first evidence of the existence of filaments in this region. The KSZ contribution of the network of filaments and halo structures to the radiation power spectrum peaks around $lsim 400$, a scale very different from that of clusters of galaxies, with a maximum amplitude $l(l+1)C_l/2pisim 10-25 (mu K)^2$, depending on model parameters, i.e., $sigma_8$ and the Jeans length. About 80% of the signal comes from filaments with redshift $zle 0.1$. Adding this component to the intrinsic Cosmic Microwave Background temperature anisotropies of the concordance model improves the fit to WMAP 3yr data by $Deltachi^2simeq 1$. The improvement is not statistically significant but a more systematic study could demonstrate that gas could significantly contribute to the anisotropies measured by WMAP.
We use Planck data to detect the cross-correlation between the thermal Sunyaev-Zeldovich (tSZ) effect and the infrared emission from the galaxies that make up the the cosmic infrared background (CIB). We first perform a stacking analysis towards Planck-confirmed galaxy clusters. We detect infrared emission produced by dusty galaxies inside these clusters and demonstrate that the infrared emission is about 50% more extended than the tSZ effect. Modelling the emission with a Navarro--Frenk--White profile, we find that the radial profile concentration parameter is $c_{500} = 1.00^{+0.18}_{-0.15}$. This indicates that infrared galaxies in the outskirts of clusters have higher infrared flux than cluster-core galaxies. We also study the cross-correlation between tSZ and CIB anisotropies, following three alternative approaches based on power spectrum analyses: (i) using a catalogue of confirmed clusters detected in Planck data; (ii) using an all-sky tSZ map built from Planck frequency maps; and (iii) using cross-spectra between Planck frequency maps. With the three different methods, we detect the tSZ-CIB cross-power spectrum at significance levels of (i) 6 $sigma$, (ii) 3 $sigma$, and (iii) 4 $sigma$. We model the tSZ-CIB cross-correlation signature and compare predictions with the measurements. The amplitude of the cross-correlation relative to the fiducial model is $A_{rm tSZ-CIB}= 1.2pm0.3$. This result is consistent with predictions for the tSZ-CIB cross-correlation assuming the best-fit cosmological model from Planck 2015 results along with the tSZ and CIB scaling relations.
We analyze observations of the microwave sky made with the Python experiment in its fifth year of operation at the Amundsen-Scott South Pole Station in Antarctica. After modeling the noise and constructing a map, we extract the cosmic signal from the data. We simultaneously estimate the angular power spectrum in eight bands ranging from large (l ~ 40) to small (l ~ 260) angular scales, with power detected in the first six bands. There is a significant rise in the power spectrum from large to smaller (l ~ 200) scales, consistent with that expected from acoustic oscillations in the early Universe. We compare this Python V map to a map made from data taken in the third year of Python. Python III observations were made at a frequency of 90 GHz and covered a subset of the region of the sky covered by Python V observations, which were made at 40 GHz. Good agreement is obtained both visually (with a filtered version of the map) and via a likelihood ratio test.
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