Related papers: Real-time Likelihood Methods for Improved Gamma-ra…

Recent investigations reveal an important new class of transient radio phenomena that occur on sub-millisecond timescales. Often transient surveys' data volumes are too large to archive exhaustively. Instead, an on-line automatic system…

With the development of aerospace technology, the increasing population of space debris has posed a great threat to the safety of spacecraft. However, the low intensity of reflected light and high angular velocity of space debris impede the…

The Fermi Gamma-ray Burst Monitor (GBM) triggers on-board in response to $\sim$ 40 short gamma-ray bursts (SGRBs) per year; however, their large localization regions have made the search for optical counterparts a challenging endeavour. We…

Detection of moving sources over complicated background is important for several reasons. First is measuring the astrophysical motion of the source. Second is that such motion resulting from atmospheric scintillation, color refraction, or…

Extreme precision radial velocity (EPRV) surveys usually require extensive observational baselines to confirm planetary candidates, making them resource-intensive. Traditionally, periodograms are used to identify promising candidate signals…

We present a novel method for identifying transients suitable for both strong signal-dominated and background-dominated objects. By employing the unsupervised machine learning algorithm known as Expectation Maximization, we achieve…

In recent years there has been a growing interest in developing "streaming algorithms" for efficient processing and querying of continuous data streams. These algorithms seek to provide accurate results while minimizing the required storage…

Macrolensing of gamma-ray bursts (GRBs) is expected to manifest as a GRB recurring with the same light curve and spectrum as a previous one, but with a different flux and a slightly offset position. Identifying such lensed GRBs may give…

The max-log-map (MLM) receiver is an approximated version of the well-known, Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm. The MLM algorithm is attractive due to its implementation simplicity. In practice, sliding-window implementations are…

The detection of gravitational waves (GWs) from binary neutron stars (BNSs) with possible telescope follow-ups opens a window to ground-breaking discoveries in the field of multi-messenger astronomy. With the improved sensitivity of current…

Crosscorrelation of the outputs of two Gravitational Wave (GW) detectors has recently been proposed [1] as a method for detecting statistical association between GWs and Gamma Ray Bursts (GRBs). Unfortunately, the method can be effectively…

Maximum-likelihood (ML) detection in high-order MIMO systems is computationally prohibitive due to exponential complexity in the number of transmit layers and constellation size. In this white paper, we demonstrate that for practical MIMO…

Transfer learning for high-dimensional Gaussian graphical models (GGMs) is studied with the goal of estimating the target GGM by utilizing the data from similar and related auxiliary studies. The similarity between the target graph and each…

The Cadmium Zinc Telluride Imager on AstroSat has proven to be a very effective all-sky monitor in the hard X-ray regime, detecting over three hundred GRBs and putting highly competitive upper limits on X-ray emissions from gravitational…

Gamma-ray bursts (GRBs) are the most powerful transient objects in the Universe, and they are a primary target for the MAGIC Collaboration. Recognizing the challenges of observing these elusive objects with Imaging Atmospheric Cherenkov…

This paper describes a new method, HMM gauge likelihood analysis, or GLA, of detecting anomalies in discrete time series using Hidden Markov Models and clustering. At the center of the method lies the comparison of subsequences. To achieve…

The currently developing space-based gamma-ray telescope GAMMA-400 will measure the gamma-ray and electron + positron fluxes using the main top-down aperture in the energy range from ~20 MeV to several TeV in a highly elliptic orbit…

Machine-learning (ML) algorithms will play a crucial role in studying the large datasets delivered by new facilities over the next decade and beyond. Here, we investigate the capabilities and limits of such methods in finding galaxies with…

Soft error, namely silent corruption of signal or datum in a computer system, cannot be caverlierly ignored as compute and communication density grow exponentially. Soft error detection has been studied in the context of enterprise…

Context. Gamma-ray bursts (GRBs) have traditionally been classified by duration into long (LGRBs) and short (SGRBs), with the former believed to originate from massive star collapses and the latter from compact binary mergers. However,…