اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدImproved CLEAN reconstructions for rotation measure synthesis with maximum likelihood estimation
87
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
The CLEAN deconvolution algorithm has well-known limitations due to the restriction of locating point source model components on a discretized grid. In this letter we demonstrate that these limitations are even more pronounced when applying CLEAN in the case of Rotation Measure (RM) synthesis imaging. We suggest a modification that uses Maximum Likelihood estimation to adjust the CLEAN-derived sky model. We demonstrate through the use of mock one-dimensional RM synthesis observations that this technique shows significant improvement over standard CLEAN and gives results that are independent of the chosen image pixelization. We suggest using this simple modification to CLEAN in upcoming polarization sensitive sky surveys.
قيم البحث
اقرأ أيضاً
Straightforward methods for adapting the familiar chi^2 statistic to histograms of discrete events and other Poisson distributed data generally yield biased estimates of the parameters of a model. The bias can be important even when the total number
of events is large. For the case of estimating a microcalorimeters energy resolution at 6 keV from the observed shape of the Mn K-alpha fluorescence spectrum, a poor choice of chi^2 can lead to biases of at least 10% in the estimated resolution when up to thousands of photons are observed. The best remedy is a Poisson maximum-likelihood fit, through a simple modification of the standard Levenberg-Marquardt algorithm for chi^2 minimization. Where the modification is not possible, another approach allows iterative approximation of the maximum-likelihood fit.
We revisit the problem of exact CMB likelihood and power spectrum estimation with the goal of minimizing computational cost through linear compression. This idea was originally proposed for CMB purposes by Tegmark et al. (1997), and here we develop i
t into a fully working computational framework for large-scale polarization analysis, adopting WMAP as a worked example. We compare five different linear bases (pixel space, harmonic space, noise covariance eigenvectors, signal-to-noise covariance eigenvectors and signal-plus-noise covariance eigenvectors) in terms of compression efficiency, and find that the computationally most efficient basis is the signal-to-noise eigenvector basis, which is closely related to the Karhunen-Loeve and Principal Component transforms, in agreement with previous suggestions. For this basis, the information in 6836 unmasked WMAP sky map pixels can be compressed into a smaller set of 3102 modes, with a maximum error increase of any single multipole of 3.8% at $ellle32$, and a maximum shift in the mean values of a joint distribution of an amplitude--tilt model of 0.006$sigma$. This compression reduces the computational cost of a single likelihood evaluation by a factor of 5, from 38 to 7.5 CPU seconds, and it also results in a more robust likelihood by implicitly regularizing nearly degenerate modes. Finally, we use the same compression framework to formulate a numerically stable and computationally efficient variation of the Quadratic Maximum Likelihood implementation that requires less than 3 GB of memory and 2 CPU minutes per iteration for $ell le 32$, rendering low-$ell$ QML CMB power spectrum analysis fully tractable on a standard laptop.
Rotation measure (RM) synthesis is a widely used polarization processing algorithm for reconstructing polarized structures along the line of sight. Performing RM synthesis on large datasets produced by telescopes like LOFAR can be computationally int
ensive as the computational cost is proportional to the product of the number of input frequency channels, the number of output Faraday depth values to be evaluated and the number of lines of sight present in the data cube. The required computational cost is likely to get worse due to the planned large area sky surveys with telescopes like the Low Frequency Array (LOFAR), the Murchison Widefield Array (MWA), and eventually the Square Kilometre Array (SKA). The massively parallel General Purpose Graphical Processing Units (GPGPUs) can be used to execute some of the computationally intensive astronomical image processing algorithms including RM synthesis. In this paper, we present a GPU-accelerated code, called cuFFS or CUDA-accelerated Fast Faraday Synthesis, to perform Faraday rotation measure synthesis. Compared to a fast single-threaded and vectorized CPU implementation, depending on the structure and format of the data cubes, our code achieves an increase in speed of up to two orders of magnitude. During testing, we noticed that the disk I/O when using the Flexible Image Transport System (FITS) data format is a major bottleneck and to reduce the time spent on disk I/O, our code supports the faster HDFITS format in addition to the standard FITS format. The code is written in C with GPU-acceleration achieved using Nvidias CUDA parallel computing platform. The code is available at https://github.com/sarrvesh/cuFFS.
Non-parametric maximum likelihood estimation encompasses a group of classic methods to estimate distribution-associated functions from potentially censored and truncated data, with extensive applications in survival analysis. These methods, including
the Kaplan-Meier estimator and Turnbulls method, often result in overfitting, especially when the sample size is small. We propose an improvement to these methods by applying kernel smoothing to their raw estimates, based on a BIC-type loss function that balances the trade-off between optimizing model fit and controlling model complexity. In the context of a longitudinal study with repeated observations, we detail our proposed smoothing procedure and optimization algorithm. With extensive simulation studies over multiple realistic scenarios, we demonstrate that our smoothing-based procedure provides better overall accuracy in both survival function estimation and individual-level time-to-event prediction by reducing overfitting. Our smoothing procedure decreases the discrepancy between the estimated and true simulated survival function using interval-censored data by up to 49% compared to the raw un-smoothed estimate, with similar improvements of up to 41% and 23% in within-sample and out-of-sample prediction, respectively. Finally, we apply our method to real data on censored breast cancer diagnosis, which similarly shows improvement when compared to empirical survival estimates from uncensored data. We provide an R package, SISE, for implementing our penalized likelihood method.
Radio polarimetry at decimetre wavelengths is the principal source of information on the Galactic magnetic field. The diffuse polarized emission is strongly influenced by Faraday rotation in the magneto-ionic medium and rotation measure is the prime
quantity of interest, implying that all Stokes parameters must be measured over wide frequency bands with many frequency channels. The DRAO 26-m Telescope has been equipped with a wideband feed, a polarization transducer to deliver both hands of circular polarization, and a receiver, all operating from 1277 to 1762 MHz. Half-power beamwidth is between 40 and 30 arcminutes. A digital FPGA spectrometer, based on commercially available components, produces all Stokes parameters in 2048 frequency channels over a 485-MHz bandwidth. Signals are digitized to 8 bits and a Fast Fourier Transform is applied to each data stream. Stokes parameters are then generated in each frequency channel. This instrument is in use at DRAO for a Northern sky polarization survey. Observations consist of scans up and down the Meridian at a drive rate of 0.9 degree per minute to give complete coverage of the sky between declinations -30 degree and 90 degree. This paper presents a complete description of the receiver and data acquisition system. Only a small fraction of the frequency band of operation is allocated for radio astronomy, and about 20 percent of the data are lost to interference. The first 8 percent of data from the survey are used for a proof-of-concept study, which has led to the first application of Rotation Measure Synthesis to the diffuse Galactic emission obtained with a single-antenna telescope. We find rotation measure values for the diffuse emission as high as approximately 100 rad per square metre, much higher than recorded in earlier work.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
