Related papers: Emulator-based Bayesian Inference on Non-Proportio…
In order to develop a high spatial resolution (micron level) thermal neutron detector, a detector assembly composed of cerium doped lithium glass microfibers, each with a diameter of 1\,$\mu$m, is proposed, where the neutron absorption…
Computer experiments are becoming increasingly important in scientific investigations. In the presence of uncertainty, analysts employ probabilistic sensitivity methods to identify the key-drivers of change in the quantities of interest.…
These days we live in a world with a permanent electromagnetic field. This raises many questions about our health and the deployment of new equipment. The problem is that these fields remain difficult to visualize easily, which only some…
Nowadays, the current threat of international terrorism is set to a severe level, demanding worldwide enhanced security. Radioactive materials that could be fashioned into a radiation dispersal device typically emit gamma rays, while…
Uncertainty quantification plays an important role in achieving trustworthy and reliable learning-based computational imaging. Recent advances in generative modeling and Bayesian neural networks have enabled the development of…
Gaussian boson sampling (GBS) has emerged as a promising quantum computing paradigm, demonstrating its potential in various applications. However, most existing works focus on theoretical aspects or simple tasks, with limited exploration of…
This paper introduces a quasi-Bayesian method that integrates frequentist nonparametric estimation with Bayesian inference in a two-stage process. Applied to an endogenous discrete choice model, the approach first uses kernel or sieve…
Adsorption is a relevant process in many fields, such as product manufacturing or pollution remediation in porous materials. Adsorption takes place at the molecular scale, amenable to be modeled by Lagrangian numerical methods. We have…
We propose a new method to detect off-pulse (unpulsed and/or continuous) emission from pulsars, using the intensity modulations associated with interstellar scintillation. Our technique involves obtaining the dynamic spectra, separately for…
Interstellar scintillation can be used to probe transverse sizes of radio sources on scales inaccessible to the nominal resolution of any terrestrial telescope, e.g. $\lesssim 10^{-6}$ arc sec. Methodology is presented that exploits this…
Projected momentum distributions of electrons, i.e. Compton profiles above the topmost atomic layer have recently become experimentally accessible by kinetic electron emission in grazing-incidence scattering of atoms at atomically flat…
We present a cost-effective method for model calibration and solution of source inversion problems in atmospheric dispersion modelling. We use Gaussian process emulations of atmospheric dispersion models within a Bayesian framework for…
Bayesian inference provides a rigorous framework to encapsulate our knowledge and uncertainty regarding various physical quantities in a well-defined and self-contained manner. Utilising modern tools, such Bayesian models can be constructed…
A digital pulse shape discrimination system based on a programmable module NI-5772 has been established and tested with EJ-301 liquid scintillation detector. The module was operated by means of running programs developed in LabVIEW with the…
The detectors based on the liquid scintillator (LS) monitored by an array of photo-multiplier tubes (PMT) are often used in low energy experiments such as neutrino oscillation studies and search for dark matter. Detectors of this kind…
A comprehensive model for explaining scintillation yield in liquid xenon is introduced. We unify various definitions of work function which abound in the literature and incorporate all available data on electron recoil scintillation yield.…
A toy detector has been designed to simulate central detectors in reactor neutrino experiments in the paper. The electron samples from the Monte-Carlo simulation of the toy detector have been reconstructed by the method of Bayesian neural…
Tau neutrino is the least studied lepton of the Standard Model (SM). The NA65/DsTau experiment targets to investigate $D_s$, the parent particle of the $\nu_\tau$, using the nuclear emulsion-based detector and to decrease the systematic…
Model fitting is possibly the most extended problem in science. Classical approaches include the use of least-squares fitting procedures and maximum likelihood methods to estimate the value of the parameters in the model. However, in recent…
The continuous improvement in weather forecast skill over the past several decades is largely due to the increasing quantity of available satellite observations and their assimilation into operational forecast systems. Assimilating these…