Related papers: False negative probability in iGSR detection: a Ba…
The Standard Model (SM) predicts a branching ratio of the Higgs boson decaying to invisible particles of $\mathcal{O}$(0.001), though current measurements have only set upper limits on this value. The small SM-allowed rate can be enhanced…
A detector material or configuration that can provide an unambiguous indication of neutron capture can substantially reduce random coincidence backgrounds in antineutrino detection and capture-gated neutron spectrometry applications. Here…
We propose an experiment to search for invisible decays of orthopositronium (o-Ps) with a 90% confidence sensitivity in the branching ratio as low as $10^{-8}$. Evidence for this decay mode would unambigously signal new physics: either the…
Nuclear recoil measurements with high-purity Germanium detectors are very promising to directly detect dark matter candidates. The main background sources in such experiments are natural radioactivity and microphonic noise. Digital pulse…
To accurately reproduce measurements from the real world, simulators need to have an adequate model of the physical system and require the parameters of the model be identified. We address the latter problem of estimating parameters through…
This work observed the problem of fingerprint image recognition in the case of missing pixels from the original image. The possibility of missing pixels recovery is tested by applying the Compressive Sensing approach. Namely, different…
We study the recovery of sparse vectors from subsampled random convolutions via $\ell_1$-minimization. We consider the setup in which both the subsampling locations as well as the generating vector are chosen at random. For a subgaussian…
Gamma Ray Bursts (GRBs) are expected to leave behind GRB remnants, similar to how ``standard'' supernovae (SN) leave behind SN remnants. The identification of these remnants in our own and in nearby galaxies would allow a much closer look…
This paper addresses the standard generalized likelihood ratio test (GLRT) detection problem of weak signals in background noise. In so doing, we consider a nonfluctuating target embedded in complex white Gaussian noise (CWGN), in which the…
This paper indicates that the sensitivity and accuracy of an infrared radiometer for emissivity measurements depends not only on its design and the measurement method, but also on the spurious radiation. This spurious radiation must be…
Buchanan et al. [Nature 436, p. 475 (2005)] have shown that it is possible to recognize paper samples via their speckle pattern by using a line-shaped laser focus, four photo detectors and a scanning mechanism. In this report recognition of…
This paper reports a CPU-level real-time stereo matching method for surgical images (10 Hz on 640 * 480 image with a single core of i5-9400). The proposed method is built on the fast ''dense inverse searching'' algorithm, which estimates…
We consider the problem of detecting the overlap between a pair of short fragments sampled in random locations from an exponentially longer sequence, via their possibly noisy reads. We consider a noiseless setting, in which the reads are…
In this work, we propose a novel methodology for robustly estimating particle size distributions from optical scattering measurements using constrained Gaussian process regression. The estimation of particle size distributions is commonly…
It is an active topic to investigate the schemes based on machine learning (ML) methods for detecting pulsars as the data volume growing exponentially in modern surveys. To improve the detection performance, input features into an ML model…
Nuclear emulsions are capable of very high position resolution in the detection of ionizing particles. This feature can be exploited to directly resolve the micrometric-scale fringe pattern produced by a matter-wave interferometer for low…
We propose a new wide-field imaging method that exploits the Localized Surface Plasmon Resonance phenomenon to produce super-resolution images with an optical microscope equipped with a custom design polarization analyzer module. In this…
Anomaly detection is a key application of machine learning, but is generally focused on the detection of outlying samples in the low probability density regions of data. Here we instead present and motivate a method for unsupervised…
Spent nuclear fuel imaging before disposal is of utmost importance before long term disposal in dedicated storage facilities. Passive Gamma Emission Tomography (PGET) is an approved method by the International Atomic Energy Agency. The…
In recent years, neural network-based anomaly detection methods have attracted considerable attention in the hyperspectral remote sensing domain due to the powerful reconstruction ability compared with traditional methods. However, actual…