8,155 research outputs found
Limits on Arcminute Scale Cosmic Microwave Background Anisotropy with the BIMA Array
We have used the Berkeley-Illinois-Maryland-Association (BIMA) millimeter
array outfitted with sensitive cm-wave receivers to search for Cosmic Microwave
Background (CMB) anisotropies on arcminute scales. The interferometer was
placed in a compact configuration which produces high brightness sensitivity,
while providing discrimination against point sources. Operating at a frequency
of 28.5 GHz, the FWHM primary beam of the instrument is 6.6 arcminutes. We have
made sensitive images of seven fields, five of which where chosen specifically
to have low IR dust contrast and be free of bright radio sources. Additional
observations with the Owens Valley Radio Observatory (OVRO) millimeter array
were used to assist in the location and removal of radio point sources.
Applying a Bayesian analysis to the raw visibility data, we place limits on CMB
anisotropy flat-band power Q_flat = 5.6 (+3.0 -5.6) uK and Q_flat < 14.1 uK at
68% and 95% confidence. The sensitivity of this experiment to flat band power
peaks at a multipole of l = 5470, which corresponds to an angular scale of
approximately 2 arcminutes. The most likely value of Q_flat is similar to the
level of the expected secondary anisotropies.Comment: 15 pages, 5 figures, LaTex, aas2pp4.sty, ApJ submitte
Predicted Planck Extragalactic Point Source Catalogue
An estimation of the number and amplitude (in flux) of the extragalactic
point sources that will be observed by the Planck Mission is presented in this
paper. The study is based on the Mexican Hat wavelet formalism introduced by
Cayon et al. 2000. Simulations at Planck observing frequencies are analysed,
taking into account all the possible cosmological, Galactic and Extragalactic
emissions together with noise. With the technique used in this work the Planck
Mission will produce a catalogue of extragalactic point sources above fluxes:
1.03 Jy (857 GHz), 0.53 Jy (545 GHz), 0.28 Jy (353 GHz), 0.24 Jy (217 GHz),
0.32 Jy (143 GHz), 0.41 Jy (100 GHz HFI), 0.34 Jy (100 GHz LFI), 0.57 Jy (70
GHz), 0.54 Jy (44 GHz) and 0.54 Jy (30 GHz), which are only slightly model
dependent (see text). Amplitudes of these sources are estimated with errors
below 15%. Moreover, we also provide a complete catalogue (for the point
sources simulation analysed) with errors in the estimation of the amplitude
below 10%. In addition we discuss the possibility of identifying different
point source populations in the Planck catalogue by estimating their spectral
indices.Comment: 13 pages, 2 figures, submitted to MNRA
Filtering techniques for the detection of Sunyaev-Zel'dovich clusters in multifrequency CMB maps
The problem of detecting Sunyaev-Zel'dovich (SZ) clusters in multifrequency
CMB observations is investigated using a number of filtering techniques. A
multifilter approach is introduced, which optimizes the detection of SZ
clusters on microwave maps. An alternative method is also investigated, in
which maps at different frequencies are combined in an optimal manner so that
existing filtering techniques can be applied to the single combined map. The SZ
profiles are approximated by the circularly-symmetric template , with and , where the core radius and the overall amplitude of the effect
are not fixed a priori, but are determined from the data. The background
emission is modelled by a homogeneous and isotropic random field, characterized
by a cross-power spectrum with . The
filtering methods are illustrated by application to simulated Planck
observations of a patch of sky in 10 frequency
channels. Our simulations suggest that the Planck instrument should detect
SZ clusters in 2/3 of the sky. Moreover, we find the catalogue
to be complete for fluxes mJy at 300 GHz.Comment: 12 pages, 7 figures; Corrected figures. Submitted to MNRA
Cosmological applications of a wavelet analysis on the sphere
The cosmic microwave background (CMB) is a relic radiation of the Big Bang
and as such it contains a wealth of cosmological information. Statistical
analyses of the CMB, in conjunction with other cosmological observables,
represent some of the most powerful techniques available to cosmologists for
placing strong constraints on the cosmological parameters that describe the
origin, content and evolution of the Universe. The last decade has witnessed
the introduction of wavelet analyses in cosmology and, in particular, their
application to the CMB. We review here spherical wavelet analyses of the CMB
that test the standard cosmological concordance model. The assumption that the
temperature anisotropies of the CMB are a realisation of a statistically
isotropic Gaussian random field on the sphere is questioned. Deviations from
both statistical isotropy and Gaussianity are detected in the reviewed works,
suggesting more exotic cosmological models may be required to explain our
Universe. We also review spherical wavelet analyses that independently provide
evidence for dark energy, an exotic component of our Universe of which we know
very little currently. The effectiveness of accounting correctly for the
geometry of the sphere in the wavelet analysis of full-sky CMB data is
demonstrated by the highly significant detections of physical processes and
effects that are made in these reviewed works.Comment: 17 pages, 8 figures; JFAA invited review, in pres
A low CMB variance in the WMAP data
We have estimated the CMB variance from the three-year WMAP data, finding a
value which is significantly lower than the one expected from Gaussian
simulations using the WMAP best-fit cosmological model, at a significance level
of 98.7 per cent. This result is even more prominent if we consider only the
north ecliptic hemisphere (99.8 per cent). Different analyses have been
performed in order to identify a possible origin for this anomaly. In
particular we have studied the behaviour of single radiometers and single year
data as well as the effect of residual foregrounds and 1/f noise, finding that
none of these possibilities can explain the low value of the variance. We have
also tested the effect of varying the cosmological parameters, finding that the
estimated CMB variance tends to favour higher values of than the one of
the WMAP best-fit model. In addition, we have also tested the consistency
between the estimated CMB variance and the actual measured CMB power spectrum
of the WMAP data, finding a strong discrepancy. A possible interpretation of
this result could be a deviation from Gaussianity and/or isotropy of the CMB.Comment: 13 pages, 5 figures. Some new tests added. Section 5 largely
modified. Accepted for publication in MNRA
Characterizing Planetary Orbits and the Trajectories of Light
Exact analytic expressions for planetary orbits and light trajectories in the
Schwarzschild geometry are presented. A new parameter space is used to
characterize all possible planetary orbits. Different regions in this parameter
space can be associated with different characteristics of the orbits. The
boundaries for these regions are clearly defined. Observational data can be
directly associated with points in the regions. A possible extension of these
considerations with an additional parameter for the case of Kerr geometry is
briefly discussed.Comment: 49 pages total with 11 tables and 10 figure
Bayesian modelling of clusters of galaxies from multi-frequency pointed Sunyaev--Zel'dovich observations
We present a Bayesian approach to modelling galaxy clusters using
multi-frequency pointed observations from telescopes that exploit the
Sunyaev--Zel'dovich effect. We use the recently developed MultiNest technique
(Feroz, Hobson & Bridges, 2008) to explore the high-dimensional parameter
spaces and also to calculate the Bayesian evidence. This permits robust
parameter estimation as well as model comparison. Tests on simulated Arcminute
Microkelvin Imager observations of a cluster, in the presence of primary CMB
signal, radio point sources (detected as well as an unresolved background) and
receiver noise, show that our algorithm is able to analyse jointly the data
from six frequency channels, sample the posterior space of the model and
calculate the Bayesian evidence very efficiently on a single processor. We also
illustrate the robustness of our detection process by applying it to a field
with radio sources and primordial CMB but no cluster, and show that indeed no
cluster is identified. The extension of our methodology to the detection and
modelling of multiple clusters in multi-frequency SZ survey data will be
described in a future work.Comment: 12 pages, 7 figures, submitted to MNRA
Interactional positioning and narrative self-construction in the first session of psychodynamic-interpersonal psychotherapy
The purpose of this study is to identify possible session one indicators of end of treatment psychotherapy outcome using the framework of three types of interactional positioning; client’s self-positioning, client’s positioning between narrated self and different partners, and the positioning between client and therapist. Three successful cases of 8-session psychodynamic-interpersonal (PI) therapy were selected on the basis of client Beck Depression Inventory scores. One unsuccessful case was also selected against which identified patterns could be tested. The successful clients were more descriptive about their problems and demonstrated active rapport-building, while the therapist used positionings expressed by the client in order to explore the positionings developed between them during therapy. The unsuccessful case was characterized by lack of positive self-comment, minimization of agentic self-capacity, and empathy-disrupting narrative confusions. We conclude that the theory of interactional positioning has been useful in identifying patterns worth exploring as early indicators of success in PI therapy
Neural networks and separation of Cosmic Microwave Background and astrophysical signals in sky maps
The Independent Component Analysis (ICA) algorithm is implemented as a neural
network for separating signals of different origin in astrophysical sky maps.
Due to its self-organizing capability, it works without prior assumptions on
the signals, neither on their frequency scaling, nor on the signal maps
themselves; instead, it learns directly from the input data how to separate the
physical components, making use of their statistical independence. To test the
capabilities of this approach, we apply the ICA algorithm on sky patches, taken
from simulations and observations, at the microwave frequencies, that are going
to be deeply explored in a few years on the whole sky, by the Microwave
Anisotropy Probe (MAP) and by the {\sc Planck} Surveyor Satellite. The maps are
at the frequencies of the Low Frequency Instrument (LFI) aboard the {\sc
Planck} satellite (30, 44, 70 and 100 GHz), and contain simulated astrophysical
radio sources, Cosmic Microwave Background (CMB) radiation, and Galactic
diffuse emissions from thermal dust and synchrotron. We show that the ICA
algorithm is able to recover each signal, with precision going from 10% for the
Galactic components to percent for CMB; radio sources are almost completely
recovered down to a flux limit corresponding to , where
is the rms level of CMB fluctuations. The signal recovering
possesses equal quality on all the scales larger then the pixel size. In
addition, we show that the frequency scalings of the input signals can be
partially inferred from the ICA outputs, at the percent precision for the
dominant components, radio sources and CMB.Comment: 15 pages; 6 jpg and 1 ps figures. Final version to be published in
MNRA
- …