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Using photoemission intensities and a detection system employed by many groups in the electron spectroscopy community as an example, we have quantitatively characterized and corrected detector non-linearity effects over the full dynamic…

In a Bayesian analysis, the likelihood that specific candidate parameters govern the evolution of a quantum system are conditioned on the outcome of measurements which, in turn, cause measurement backaction on the state of the system [M.…

Having actual models for power system components (such as generators and loads or auxiliary equipment) is vital to correctly assess the power system operating state and to establish stability margins. However, power system operators often…

Laser cooling and trapping offers the possibility of confining a sample of radioactive atoms in free space. Here, we address the question of how best to take advantage of cold atom properties to perform the observation of as highly…

In many modern applications, large-scale sensor networks are used to perform statistical inference tasks. In this paper, we propose Bayesian methods for multiple change-point detection using a sensor network in which a fusion center (FC)…

Atomic detection by fluorescence may fail because of reflection from the laser or transmission without excitation. The detection probability for a given velocity range may be improved by controlling the detuning and the spatial dependence…

Neutron capture cross sections of unstable isotopes are important for neutron-induced nucleosynthesis as well as for technological applications. A combination of a radioactive beam facility, an ion storage ring and a high flux reactor would…

The prediction of cross sections for nuclei far off stability is crucial in the field of nuclear astrophysics. We discuss the model mostly employed for such calculations: the statistical model (Hauser-Feshbach). Special emphasis is put on…

Determining the adsorption isotherms is an issue of significant importance in preparative chromatography. A modern technique for estimating adsorption isotherms is to solve an inverse problem so that the simulated batch separation coincides…

Worldwide several radiation sources contribute to the delivered dose to the human population. This radiation also acts as natural background when detecting radiation, for instance from radioactive sources. In this work a medium-size plastic…

The method of location and spectral estimation of weak signals on a noise background is being considered. The method is based on the optimized on order and noise dispersion autoregressive model of a sought signal. A new approach of model…

Transient detection and flux measurement via image subtraction stand at the base of time domain astronomy. Due to the varying seeing conditions, the image subtraction process is non-trivial, and existing solutions suffer from a variety of…

As commonly understood, the noise spectroscopy problem---characterizing the statistical properties of a noise process affecting a quantum system by measuring its response---is ill-posed. Ad-hoc solutions assume implicit structure which is…

The recent development of compressed sensing has led to spectacular advances in the understanding of sparse linear estimation problems as well as in algorithms to solve them. It has also triggered a new wave of developments in the related…

We present a statistical method for detecting and analysing state changes in experimental measurements using the Cuscore statistic and its special case, the Centred Cuscore statistic. These statistics are designed to identify deviations in…

Bayesian neural networks (BNNs) with latent variables are probabilistic models which can automatically identify complex stochastic patterns in the data. We describe and study in these models a decomposition of predictive uncertainty into…

Fundamental research on bistatic radar reflectivity is highly relevant, e.g., to the upcoming mobile communication standard 6G, which includes integrated sensing and communication (ISAC). We introduce a model for correcting instrumentation…

Increasing interest in energetic particle effects on weather and climate has motivated development of a miniature scintillator-based detector intended for deployment on meteorological radiosondes or unmanned airborne vehicles. The detector…

We consider the high energy physics unfolding problem where the goal is to estimate the spectrum of elementary particles given observations distorted by the limited resolution of a particle detector. This important statistical inverse…

The prediction of cross sections for nuclei far off stability is crucial in the field of nuclear astrophysics. In recent calculations the nuclear level density -- as an important ingredient to the statistical model (Hauser-Feshbach) -- has…