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T. Souradeep

Publications and source records attributed to T. Souradeep.

3 recordsLinked to original sources

Spectral Distortions of the CMB as a Probe of Inflation, Recombination, Structure Formation and Particle Physics

Following the pioneering observations with COBE in the early 1990s, studies of the cosmic microwave background (CMB) have focused on temperature and polarization anisotropies. CMB spectral distortions - tiny departures of the CMB energy spectrum from that of a perfect blackbody - provide a second, independent probe of fundamental physics, with a reach deep into the primordial Universe. The theoretical foundation of spectral distortions has seen major advances in recent years, which highlight the immense potential of this emerging field. Spectral distortions probe a fundamental property of the Universe - its thermal history - thereby providing additional insight into processes within the cosmological standard model (CSM) as well as new physics beyond. Spectral distortions are an important tool for understanding inflation and the nature of dark matter. They shed new light on the physics of recombination and reionization, both prominent stages in the evolution of our Universe, and furnish critical information on baryonic feedback processes, in addition to probing primordial correlation functions at scales inaccessible to other tracers. In principle the range of signals is vast: many orders of magnitude of discovery space could be explored by detailed observations of the CMB energy spectrum. Several CSM signals are predicted and provide clear experimental targets, some of which are already observable with present-day technology. Confirmation of these signals would extend the reach of the CSM by orders of magnitude in physical scale as the Universe evolves from the initial stages to its present form. The absence of these signals would pose a huge theoretical challenge, immediately pointing to new physics.

astro-ph.CO

A re-analysis of the three-year WMAP temperature power spectrum and likelihood

We analyze the three-year WMAP temperature anisotropy data seeking to confirm the power spectrum and likelihoods published by the WMAP team. We apply five independent implementations of four algorithms to the power spectrum estimation and two implementations to the parameter estimation. Our single most important result is that we broadly confirm the WMAP power spectrum and analysis. Still, we do find two small but potentially important discrepancies: On large angular scales there is a small power excess in the WMAP spectrum (5-10% at l<~30) primarily due to likelihood approximation issues between 13 <= l <~30. On small angular scales there is a systematic difference between the V- and W-band spectra (few percent at l>~300). Recently, the latter discrepancy was explained by Huffenberger et al. (2006) in terms of over-subtraction of unresolved point sources. As far as the low-l bias is concerned, most parameters are affected by a few tenths of a sigma. The most important effect is seen in n_s. For the combination of WMAP, Acbar and BOOMERanG, the significance of n_s =/ 1 drops from ~2.7 sigma to ~2.3 sigma when correcting for this bias. We propose a few simple improvements to the low-l WMAP likelihood code, and introduce two important extensions to the Gibbs sampling method that allows for proper sampling of the low signal-to-noise regime. Finally, we make the products from the Gibbs sampling analysis publically available, thereby providing a fast and simple route to the exact likelihood without the need of expensive matrix inversions.

astro-ph

Cosmic Microwave Background Anisotropy Measurement From Python V

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.

astro-ph