Related papers: Application of a generalized likelihood ratio test…
The new generation research experiments will introduce huge data surge to a continuously increasing data production by current experiments. This data surge necessitates efficient compression techniques. These compression techniques must…
A new revision of the gamma flux that we expect to detect in Imaging Atmospheric Cherenkov Telescopes (IACTs) from SUSY dark matter annihilation in the Draco dSph is presented using the dark matter density profiles compatible with the…
The Major Atmospheric Gamma Imaging Cherenkov (MAGIC) telescope system consists of two imaging atmospheric Cherenkov telescopes (IACTs) and is located on the Canary island of La Palma. IACTs are excellent tools to inspect the…
Cherenkov Telescope Array (CTA) is an upcoming instrument that will start a new generation of atmospheric Cherenkov telescopes. CTA is expected not only to provide an unprecedented sensitivity in the tens of GeV to hundreds of TeV range,…
Gamma-ray astronomy at energies in excess of 100 GeV is carried out using arrays of imaging Cherenkov telescopes. Each telescope comprises a large reflector, of order 10 m diameter, made of many mirror facets, and a camera consisting of a…
The MAGIC telescope with its 17m diameter mirror is today the largest operating single-dish Imaging Air Cherenkov Telescope (IACT). It is located on the Canary Island La Palma, at an altitude of 2200m above sea level, as part of the Roque…
The main theme of this paper is a modification of the likelihood ratio test (LRT) for testing high dimensional covariance matrix. Recently, the correct asymptotic distribution of the LRT for a large-dimensional case (the case $p/n$…
In this paper, we present a method for computing the marginal likelihood, also known as the model likelihood or Bayesian evidence, from Markov Chain Monte Carlo (MCMC), or other sampled posterior distributions. In order to do this, one…
Loss tomography has received considerable attention in recent years and a number of estimators based on maximum likelihood (ML) or Bayesian principles have been proposed. Almost all of the estimators are devoted to the tree topology despite…
Generalized likelihood ratio statistics have been proposed in Fan, Zhang and Zhang [Ann. Statist. 29 (2001) 153-193] as a generally applicable method for testing nonparametric hypotheses about nonparametric functions. The likelihood ratio…
In this paper, we derive a unified method for establishing the distributional convergence of linear eigenvalue statistics (LES) for generalized patterned random matrices. We prove that for an $N \times N$ generalized patterned random matrix…
We present a sophisticated likelihood reconstruction algorithm for shower-image analysis of imaging Cherenkov telescopes. The reconstruction algorithm is based on the comparison of the camera pixel amplitudes with the predictions from a…
The peak photon detection efficiency (PDE) of silicon photomultipliers (SiPMs) can be as good or better than the PDE of photomultiplier tubes (PMTs). There are experiments where the signal is measured in the presence of a strong, steady…
This paper focuses on a challenging class of inverse problems that is often encountered in applications. The forward model is a complex non-linear black-box, potentially non-injective, whose outputs cover multiple decades in amplitude.…
We have developed a new regression technique, the maximum likelihood (ML)-based method and its variant, the KS-test based method, designed to obtain unbiased regression results from typical astronomical data. A normalizing flow model is…
The gamma/hadron separation in the imaging air Cherenkov telescope technique is based on differences between images of a hadronic shower and a gamma induced electromagnetic cascade. One may expect for a large telescope that a detection of…
A new generation of optical intensity interferometers are emerging in recent years taking advantage of the existing infrastructure of Imaging Atmospheric Cherenkov Telescopes (IACTs). The MAGIC SII (Stellar Intensity Interferometer) in La…
The randomized midpoint Langevin Monte Carlo (RLMC), introduced by Shen and Lee (2019), is a variant of classical Unadjusted Langevin Algorithm. It was shown in the literature that the RLMC is an efficient algorithm for approximating…
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…
The monitoring of the atmosphere is very relevant for Imaging Atmospheric Cherenkov Telescopes. Adverse weather conditions (strong wind, high humidity, etc.) may damage the telescopes and must therefore be monitored continuously to…