No Arabic abstract
The matched filter (MF) is one of the most popular and reliable techniques to the detect signals of known structure and amplitude smaller than the level of the contaminating noise. Under the assumption of stationary Gaussian noise, MF maximizes the probability of detection subject to a constant probability of false detection or false alarm (PFA). This property relies upon a priori knowledge of the position of the searched signals, which is usually not available. Recently, it has been shown that when applied in its standard form, MF may severely underestimate the PFA. As a consequence the statistical significance of features that belong to noise is overestimated and the resulting detections are actually spurious. For this reason, an alternative method of computing the PFA has been proposed that is based on the probability density function (PDF) of the peaks of an isotropic Gaussian random field. In this paper we further develop this method. In particular, we discuss the statistical meaning of the PFA and show that, although useful as a preliminary step in a detection procedure, it is not able to quantify the actual reliability of a specific detection. For this reason, a new quantity is introduced called the specific probability of false alarm (SPFA), which is able to carry out this computation. We show how this method works in targeted simulations and apply it to a few interferometric maps taken with the Atacama Large Millimeter/submillimeter Array (ALMA) and the Australia Telescope Compact Array (ATCA). We select a few potential new point sources and assign an accurate detection reliability to these sources.
The detection reliability of weak signals is a critical issue in many astronomical contexts and may have severe consequences for determining number counts and luminosity functions, but also for optimising the use of telescope time in follow-up observations. Because of its optimal properties, one of the most popular and widely-used detection technique is the matched filter (MF). This is a linear filter designed to maximise the detectability of a signal of known structure that is buried in additive Gaussian random noise. In this work we show that in the very common situation where the number and position of the searched signals within a data sequence (e.g. an emission line in a spectrum) or an image (e.g. a point-source in an interferometric map) are unknown, this technique, when applied in its standard form, may severely underestimate the probability of false detection. This is because the correct use of the MF relies upon a-priori knowledge of the position of the signal of interest. In the absence of this information, the statistical significance of features that are actually noise is overestimated and detections claimed that are actually spurious. For this reason, we present an alternative method of computing the probability of false detection that is based on the probability density function (PDF) of the peaks of a random field. It is able to provide a correct estimate of the probability of false detection for the one-, two- and three-dimensional case. We apply this technique to a real two-dimensional interferometric map obtained with ALMA.
The matched filter (MF) represents one of the main tools to detect signals from known sources embedded in the noise. In the Gaussian case the noise is assumed to be the realization of a Gaussian random field (GRF). The most important property of the MF, the maximization of the probability of detection subject to a constant probability of false detection or false alarm (PFA), makes it one of the most popular techniques. However, the MF technique relies upon the a priori knowledge of the number and the position of the searched signals in the GRF which usually are not available. A typical way out is to assume that the position of a signal coincides with one of the peaks in the matched filtered data. A detection is claimed when the probability that a given peak is due only to the noise (i.e. the PFA) is smaller than a prefixed threshold. In this case the probability density function (PDF) of the amplitudes has to be used for the computation of the PFA, which is different from the Gaussian. Moreover, the probability that a detection is false depends on the number of peaks present in the filtered GRF, the greater the number of peaks in a GRF, the higher the probability of peaks due to the noise that exceed the detection threshold. If not taken into account, the PFA can be severely underestimated. Many solutions proposed to this problem are non-parametric hence not able to exploit all the available information. This limitation has been overcome by means of two efficient parametric approaches, one based on the PDF of the peak amplitudes of a smooth and isotropic GRF whereas the other uses the Gumbel distribution (the asymptotic PDF of the corresponding extreme). Simulations and ALMA maps show that, although the two methods produce almost identical results, the first is more flexible and allows us to check the reliability of the detection procedure.
We consider a set of M images, whose pixel intensities at a common point can be treated as the components of a M-dimensional vector. We are interested in the estimation of the modulus of such a vector associated to a compact source. For instance, the detection/estimation of the polarized signal of compact sources immersed in a noisy background is relevant in some fields like Astrophysics. We develop two different techniques, one based on the Maximum Likelihood Estimator (MLE) applied to the modulus distribution, the modulus filter (ModF) and other based on prefiltering the components before fusion, the filtered fusion (FF), to deal with this problem. We present both methods in the general case of M images and apply them to the particular case of three images (linear plus circular polarization). Numerical simulations have been performed to test these filters considering polarized compact sources immersed in stationary noise. The FF performs better than the ModF in terms of errors in the estimated amplitude and position of the source, especially in the low signal-to-noise case. We also compare both methods with the direct application of a matched filter (MF) on the polarization data. This last technique is clearly outperformed by the new methods.
We present a new method for detection of the integrated Sachs-Wolfe (ISW) imprints of cosmic superstructures on the cosmic microwave background, based on a matched filtering approach. The expected signal-to-noise ratio for this method is comparable to that obtained from the full cross-correlation, and unlike other stacked filtering techniques it is not subject to an a posteriori bias. We apply this method to Planck CMB data using voids and superclusters identified in the CMASS galaxy data from the Sloan Digital Sky Survey Data Release 12, and measure the ISW amplitude to be $A_mathrm{ISW}=1.64pm0.53$ relative to the $Lambda$CDM expectation, corresponding to a $3.1sigma$ detection. In contrast to some previous measurements of the ISW effect of superstructures, our result is in agreement with the $Lambda$CDM model.
Pulsars are neutron stars, stellar corpses left over after supernova explosions of stars about ten times as massive as our Sun, with densities comparable to the atomic nucleus, spinning with periods from few milliseconds up to few seconds, and endowed with magnetic fields thousands billion times stronger than the Earths, where particles are accelerated to the relativistic regime producing electromagnetic radiation across the entire spectrum. Although there is a general consensus on the fact that pulsars radio emission is coherent in nature, whereas the emission from the optical to high-energy $gamma$-rays is due to incoherent processes, it has not been established yet at which wavelengths the transition occurs, a key information for all emission models of pulsar magnetospheres. Of course, to address this issue covering the spectral region between high-frequency radio waves and the mid-IR is crucial. We used the Atacama Large Millimetre Array (ALMA) to observe the Vela pulsar (PSR, B0833$-$45), one of the very few observed in radio and from the mid-infrared up to the very high-energy $gamma$-rays. We detected Vela at frequencies of 97.5, 145, 233, 343.5 GHz and found that its energy density spectrum follows a power-law of spectral index $alpha = -0.93 pm 0.16$. The ALMA spectrum corresponds to very high brightness temperatures - from $10^{17}$ to $10^{15}$ K - suggesting that a coherent radiative process still contributes to the mm/sub-mm emission. This is, therefore, the first indication of coherent emission other than radio originating in pulsars. At the same time, we identified an extended structure, preliminarily detected in ground-based observations. We support its interpretation as a counter-jet protruding from the pulsar.