Related papers: Application of Bayes' theorem for pulse shape disc…
Scintillators capable of detecting both neutrons and gamma-rays have generated considerable interest. In particular, the use of such scintillators with silicon photomultipliers (SiPMs) enables low-power and compact-geometry applications.…
The quantum statistics of particles is determined by both the spins and the indistinguishability of quantum states. Here we studied the quantum statistics of partially distinguishable photons by defining the multi-photon…
Modeling of X-ray pulse profiles from millisecond pulsars offers a promising method of inferring the mass-to-radius ratios of neutron stars. Recent observations with NICER resulted in measurements of radii for three neutron stars using this…
The DEAP-1 low-background liquid argon detector was used to measure scintillation pulse shapes of electron and nuclear recoil events and to demonstrate the feasibility of pulse-shape discrimination (PSD) down to an electron-equivalent…
With a Bayesian approach, the linear optics correction algorithm for storage rings is revisited. Starting from the Bayes' theorem, a complete linear optics model is simplified as "likelihood functions" and "prior probability distributions".…
Gamma-ray emission from special nuclear material (SNM) is relatively easy to shield from detection using modest amounts of high-Z material. In contrast, fast-neutrons are much more penetrating and can escape relatively thick high-Z…
The energy and electric field dependence of pulse shape discrimination in liquid xenon have been measured in a 10 gm two-phase xenon time projection chamber. We have demonstrated the use of the pulse shape and charge-to-light ratio…
Understanding the properties of transient gravitational waves and their sources is of broad interest in physics and astronomy. Bayesian inference is the standard framework for astro-physical measurement in transient gravitational-wave…
Statistical tools of uncertainty quantification can be used to assess the information content of measured observables with respect to present-day theoretical models; to estimate model errors and thereby improve predictive capability; to…
Bayesian networks are powerful tools for probabilistic analysis and have been widely used in machine learning and data science. Unlike the time-consuming parameter training process of neural networks, Bayes classifiers constructed on…
Data selection and the determination of systematic uncertainties in the spectroscopic measurements of neutron star radii from thermonuclear X-ray bursts have been the subject of numerous recent studies. In one approach, the uncertainties…
The light output, $\alpha/\beta$ ratio, and pulse shape have been investigated at $-25^\circ$ C with PbWO$_4$ crystal scintillators undoped, and doped by F, Eu, Mo, Gd and S. The fast $0.01-0.06 \mu$s and middle $0.1-0.5 \mu$s components of…
We investigate photon--pion discrimination in regimes where electromagnetic showers overlap at the scale of calorimeter granularity. Using full detector simulations with fine-grained calorimeter segmentation of approximately…
I describe ongoing work developing Bayesian methods for flexible modeling of arrival time series data without binning, aiming to improve detection and measurement of X-ray and gamma-ray pulsars, and of pulses in gamma-ray bursts. The…
We have developed a frequentist approach for model selection which determines the consistency between any cosmological model and the data using the distribution of likelihoods from the iterative smoothing method. Using this approach, we…
The tilted-wave interferometer is a promising technique for the development of a reference measurement system for the highly accurate form measurement of aspheres and freeform surfaces. The technique combines interferometric measurements,…
Artificial Neural Networks are connectionist systems that perform a given task by learning on examples without having prior knowledge about the task. This is done by finding an optimal point estimate for the weights in every node.…
Short-pulse, ultra high-intensity lasers have opened new regimes for studying fusion plasmas and creating novel ultra-short ion beams and neutron sources. Diagnosing the plasma in these experiments is important for optimizing the fusion…
In this paper, Bayesian optimisation is used to simultaneously search the optimal values of the shape parameter and the radius in radial basis function partition of unity interpolation problem. It is a probabilistic iterative approach that…
In the framework of the ``ULTIMA'' project, we use ultra cold superfluid 3He bolometers for the direct detection of single particle events, aimed for a future use as a dark matter detector. One parameter of the pulse shape observed after…