Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userOptimal matched filter in the low-number count Poisson noise regime and implications for X-ray source detection
92
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
Detection of templates (e.g., sources) embedded in low-number count Poisson noise is a common problem in astrophysics. Examples include source detection in X-ray images, gamma-rays, UV, neutrinos, and search for clusters of galaxies and stellar streams. However, the solutions in the X-ray-related literature are sub-optimal -- in some cases by considerable factors. Using the lemma of Neyman-Pearson we derive the optimal statistics for template detection in the presence of Poisson noise. We demonstrate that this method provides higher completeness, for a fixed false-alarm probability value, compared with filtering the image with the point-spread function (PSF). In turn, we find that filtering by the PSF is better than filtering the image using the Mexican-hat wavelet (used by wavedetect). For some background levels, our method improves the sensitivity of source detection by more than a factor of two over the popular Mexican-hat wavelet filtering. This filtering technique can also be used also for fast PSF photometry and flare detection, and it is efficient, as well as straight forward to implement. We provide an implementation in MATLAB.
rate research
Read More
The matched filter (MF) is widely used to detect signals hidden within the noise. If the noise is Gaussian, its performances are well-known and describable in an elegant analytical form. The treatment of non-Gaussian noises is often cumbersome as in most cases there is no analytical framework. This is true also for Poisson noise which, especially in the low-number count regime, presents the additional difficulty to be discrete. For this reason in the past methods have been proposed based on heuristic or semi-heuristic arguments. Recently, an analytical form of the MF has been introduced but the computation of the probability of false detection or false alarm (PFA) is based on numerical simulations. To overcome this inefficient and time consuming approach we propose here an effective method to compute the PFA based on the saddle point approximation (SA). We provide the theoretical framework and support our findings by means of numerical simulations. We discuss also the limitations of the MF in practical applications.
We report on the detection of source noise in the time domain at 162MHz with the Murchison Widefield Array. During the observation the flux of our target source Virgo A (M87) contributes only $sim$1% to the total power detected by any single antenna, thus this source noise detection is made in an intermediate regime, where the source flux detected by the entire array is comparable with the noise from a single antenna. The magnitude of source noise detected is precisely in line with predictions. We consider the implications of source noise in this moderately strong regime on observations with current and future instruments.
Context: The eROSITA X-ray telescope onboard the Spectrum-Roentgen-Gamma (SRG) satellite has started to observe new X-ray sources over the full sky at an unprecedented rate. Understanding the selection function of the source detection is important to the subsequent scientific analysis of the eROSITA catalogs. Aims: Through simulations, we test and optimize the eROSITA source detection procedures, and characterize the detected catalog quantitatively. Methods: Taking the eROSITA Final Equatorial-Depth Survey (eFEDS) as an example, we run extensive photon event simulations using our best knowledge of the instrument characteristics, the background spectrum, and the population of astronomical X-ray sources. We analyze the source detection results based on the origin of each photon. Results. The source detection procedure is optimized according to the source detection efficiency. We choose a two-pronged strategy to build the eFEDS X-ray catalogs, creating a main catalog using only the most sensitive band (0.2-2.3 keV) and an independent hard-band selected catalog using multi-band detection in a range up to 5 keV. From the mock catalogs (available with this paper), we measure the catalog completeness and purity, which can be used in both choosing the sample selection thresholds and in further studies of AGN and cluster demography.
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.
Different forms of long gamma-ray bursts (GRBs) Luminosity Functions are considered on the basis of an explicit physical model. The inferred flux distributions are compared with the observed ones from two samples of GRBs, Swift and Fermi GBM. The best fit parameters of the Luminosity functions are found and the physical interpretations are discussed. The results are consistent with the observation of a comparable number of flat phase afterglows and monotonic decreasing ones.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
