6,437 research outputs found
Maximum likelihood, parametric component separation and CMB B-mode detection in suborbital experiments
We investigate the performance of the parametric Maximum Likelihood component
separation method in the context of the CMB B-mode signal detection and its
characterization by small-scale CMB suborbital experiments. We consider
high-resolution (FWHM=8') balloon-borne and ground-based observatories mapping
low dust-contrast sky areas of 400 and 1000 square degrees, in three frequency
channels, 150, 250, 410 GHz, and 90, 150, 220 GHz, with sensitivity of order 1
to 10 micro-K per beam-size pixel. These are chosen to be representative of
some of the proposed, next-generation, bolometric experiments. We study the
residual foreground contributions left in the recovered CMB maps in the pixel
and harmonic domain and discuss their impact on a determination of the
tensor-to-scalar ratio, r. In particular, we find that the residuals derived
from the simulated data of the considered balloon-borne observatories are
sufficiently low not to be relevant for the B-mode science. However, the
ground-based observatories are in need of some external information to permit
satisfactory cleaning. We find that if such information is indeed available in
the latter case, both the ground-based and balloon-borne experiments can detect
the values of r as low as ~0.04 at 95% confidence level. The contribution of
the foreground residuals to these limits is found to be then subdominant and
these are driven by the statistical uncertainty due to CMB, including E-to-B
leakage, and noise. We emphasize that reaching such levels will require a
sufficient control of the level of systematic effects present in the data.Comment: 18 pages, 12 figures, 6 table
Gravitational waves: search results, data analysis and parameter estimation
The Amaldi 10 Parallel Session C2 on gravitational wave (GW) search results, data analysis and parameter estimation included three lively sessions of lectures by 13 presenters, and 34 posters. The talks and posters covered a huge range of material, including results and analysis techniques for ground-based GW detectors, targeting anticipated signals from different astrophysical sources: compact binary inspiral, merger and ringdown; GW bursts from intermediate mass binary black hole mergers, cosmic string cusps, core-collapse supernovae, and other unmodeled sources; continuous waves from spinning neutron stars; and a stochastic GW background. There was considerable emphasis on Bayesian techniques for estimating the parameters of coalescing compact binary systems from the gravitational waveforms extracted from the data from the advanced detector network. This included methods to distinguish deviations of the signals from what is expected in the context of General Relativity
Studies on noise robust automatic speech recognition
Noise in everyday acoustic environments such as cars, traffic environments, and cafeterias remains one of the main challenges in automatic speech recognition (ASR). As a research theme, it has received wide attention in conferences and scientific journals focused on speech technology. This article collection reviews both the classic and novel approaches suggested for noise robust ASR. The articles are literature reviews written for the spring 2009 seminar course on noise robust automatic speech recognition (course code T-61.6060) held at TKK
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