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Positron physics touches on a wide-ranging variety of fields from materials science to medical imaging to high energy physics. In this paper we present the development of a flexible positron annihilation spectrometer appropriate for the…
Several emerging post-Bayesian methods target a probability distribution for which an entropy-regularised variational objective is minimised. This increased flexibility introduces a computational challenge, as one loses access to an…
Dimensionality reduction is a main step in the learning process which plays an essential role in many applications. The most popular methods in this field like SVD, PCA, and LDA, only can be applied to data with vector format. This means…
This paper depicts a brief revision of Generalized Regression Neural Networks (GRNN) applications in system identification and control of dynamic systems. In addition, a comparison study between the performance of back-propagation neural…
We show that one loop GUT scale threshold corrections to gauge couplings are a significant constraint on the GUT symmetry breaking sector of the theory. The one loop threshold corrections relate the prediction for $\alpha_s(M_Z)$ to the…
The weak Galerkin (WG) finite element method is an effective and flexible general numerical technique for solving partial differential equations. It is a natural extension of the classic conforming finite element method for discontinuous…
We present a method to calculate the electronic charge density of periodic solids in the GW approximation, using the space-time method. We investigate for the examples of silicon and germanium to what extent the GW approximation is…
We performed a detailed analysis and the Monte Carlo simulation of the neutron lifetime experiment [S. Arzumanov et al., Phys. Lett. B 483 (2000) 15] because of the strong disagreement by 5.6 standard deviations between the results of this…
The PAMELA satellite experiment has measured the cosmic-ray positron fraction between 1.5 GeV and 100 GeV. The need to reliably discriminate between the positron signal and proton background has required the development of an ad hoc…
This paper introduces a novel family of generalized exponentiated gradient (EG) updates derived from an Alpha-Beta divergence regularization function. Collectively referred to as EGAB, the proposed updates belong to the category of…
Radiative corrections are calculated for antineutrino proton quasielastic scattering, neutrino deuteron scattering, and the asymmetry of polarised neutron beta decay from which $G_{A}/G_{V}$ is determined. A particular emphasis is given to…
Tracing of the magnetic field with Velocity Gradient Technique (VGT) allows observers to probe magnetic field directions with spectroscopic data. In this paper, we employ the method of Principal Component Analysis (PCA) to extract the…
To improve the accuracy of the e+e- -> pi+pi-gamma Radiative Return method, one has to control the theoretical uncertainty of the final-state photon emission. It is of particular importance at DAPHNE for the analysis, where cuts are relaxed…
Tests of general relativity (GR) with gravitational waves (GWs) introduce additional deviation parameters in the waveform model. The enlarged parameter space makes inference computationally costly, which has so far limited systematic,…
We introduce a general approximation scheme in order to calculate gauge invariant observables in the canonical formulation of general relativity. Using this scheme we will show how the observables and the dynamics of field theories on a…
Searching for a modified dispersion relation is one of the general relativity tests performed by the LIGO-Virgo-KAGRA collaboration with each new cumulative Gravitational Wave Transient Catalog (GWTC). It considers classes of theories that…
We use data from the Gravitational Wave Transient Catalog 3.0 to update constraints on parameterized deviations from General Relativity, as encountered in pseudo-complex general relativity (pcGR) theory and models of dirty black holes. The…
Gradient restarting has been shown to improve the numerical performance of accelerated gradient methods. This paper provides a mathematical analysis to understand these advantages. First, we establish global linear convergence guarantees…
Composite optimization offers a powerful modeling tool for a variety of applications and is often numerically solved by means of proximal gradient methods. In this paper, we consider fully nonconvex composite problems under only local…
Many traditional signal recovery approaches can behave well basing on the penalized likelihood. However, they have to meet with the difficulty in the selection of hyperparameters or tuning parameters in the penalties. In this article, we…