2,743 research outputs found
Quasar-galaxy associations revisited
Gravitational lensing predicts an enhancement of the density of bright,
distant QSOs around foreground galaxies. We measure this QSO-galaxy correlation
w_qg for two complete samples of radio-loud quasars, the southern 1Jy and
Half-Jansky samples. The existence of a positive correlation between z~1
quasars and z~0.15 galaxies is confirmed at a p=99.0% significance level
(>99.9%) if previous measurements on the northern hemisphere are included). A
comparison with the results obtained for incomplete quasar catalogs (e.g. the
Veron-Cetty and Veron compilation) suggests the existence of an `identification
bias', which spuriously increases the estimated amplitude of the quasar-galaxy
correlation for incomplete samples. This effect may explain many of the
surprisingly strong quasar-galaxy associations found in the literature.
Nevertheless, the value of w_qg that we measure in our complete catalogs is
still considerably higher than the predictions from weak lensing. We consider
two effects which could help to explain this discrepancy: galactic dust
extinction and strong lensing.Comment: 9 pages, 6 figures, MNRAS accepte
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 Fully-Integrated CMOS LDO Regulator for Battery-Operated On-Chip Measurement Systems
This paper presents a fully-integrated 0.18 mu m CMOS low drop-out (LDO) regulator designed to drive on-chip low power frontend sensor nodes. The proposed LDO is based on a simple telescopic amplifier stage with internal cascode compensation driving a PMOS pass-device, providing a high precision 1.8 V output voltage for input voltages from 3.6 V to 1.92 V up to a 50 mA load current with only 22 mu A quiescent current. Line and load regulation are respectively better than 0.017 mV/V and 0.003 mV/mA, while recovery times are below 4 mu s over a (-40 degrees C, 120 degrees C) temperature span
Microelectronic cmos implementation of a machine learning technique for sensor calibration
An integrated machine-learning based adaptive circuit for sensor calibration implemented in standard 0.18Όm CMOS technology with 1.8V power supply is presented in this paper. In addition to linearizing the device response, the proposed system is also capable to correct offset and gain errors. The building blocks conforming the adaptive system are designed and experimentally characterized to generate numerical high-level models which are used to verify the proper performance of each analog block within a defined multilayer perceptron architecture. The network weights, obtained from the learning phase, are stored in a microcontroller EEPROM memory, and then loaded into each of the registers of the proposed integrated prototype. In order to verify the proposed system performance, the non-linear characteristic of a thermistor is compensated as an application example, achieving a relative error er below 3% within an input span of 130°C, which is almost 6 times less than the uncorrected response. The power consumption of the whole system is 1.4mW and it has an active area of 0.86mm 2 . The digital programmability of the network weights provides flexibility when a sensor change is required
Detection of non-Gaussianity in the WMAP 1-year data using spherical wavelets
A non-Gaussian detection in the WMAP 1-year data is reported. The detection
has been found in the combined Q-V-W map proposed by the WMAP team (Komatsu et
al. 2003) after applying a wavelet technique based on the Spherical Mexican Hat
Wavelet (SMHW). The skewness and the kurtosis of the SMHW coefficients are
calculated at different scales. A non-Gaussian signal is detected at scales of
the SMHW around 4 deg (size in the sky of around 10 deg). The right tail
probability of the detection is approx. 0.4%. In addition, a study of
Gaussianity is performed in each hemisphere. The northern hemisphere is
compatible with Gaussianity, whereas the southern one deviates from Gaussianity
with a right tail probability of approx. 0.1%. Systematics, foregrounds and
uncertainties in the estimation of the cosmological parameters are carefully
studied in order to identify the possible source of non-Gaussianity. The
detected deviation from Gaussianity is not found to be caused by systematic
effects: 1) each one of the Q, V and W receivers shows the same non-Gaussianity
pattern, and 2) several combinations of the different receivers at each
frequency band do not show this non-Gaussian pattern. Similarly, galactic
foregrounds show a negligible contribution to the non-Gaussian detection:
non-Gaussianity is detected in all the WMAP maps and no frequency dependence is
observed. Moreover, the expected foreground contribution to the combined WMAP
map was added to CMB Gaussian simulations showing a behaviour compatible with
the Gaussian model. Influence of uncertainties in the CMB power spectrum
estimation are also quantified. Hence, possible intrinsic temperature
fluctuations (like secondary anisotropies and primordial features) can not be
rejected as the source of this non-Gaussian detection.Comment: 33 pages, 14 figures. Revised to match version accepted for
publication in Ap
A CMOS Mixed Mode Non-Linear Processing Unit for Adaptive Sensor Conditioning in Portable Smart Systems
This paper presents the architecture of a novel non-linear digitally programmable analog unit for sensor output conditioning in battery-operated smart systems. Designed in an 180nm 1.8V standard CMOS technology, by properly setting the 6-bit registers in the arithmetic unit, the voltage inputs are weighted before being processed by a non-linear circuit. Thus, a processing system consisting of a set of these devices suitably tuned and interconnected can be applied to condition a non-linear sensor, improving its behavior both in linearity and operating range, while reducing the effects of cross sensitivity. The robustness of the digital weight tuning is tested simulating a chip-on-the-loop training using a Levenberg-Marquardt-based algorithm. Electric simulations of the proposed unit and the results of its application in a complete neural network-based processing system to improve the linear operating range of a thermistor are presented
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