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By performing an analysis in moment space using high statistics DIS world data, we extract the values of both the QCD parameter $\Lambda^{(4)}_{\bar{MS}}$ up to NLO and of the power corrections to the proton structure function, $F_2$. At…
Bubble detectors are widely used to measure neutron flux from laser-driven sources employing a pitcher-catcher setup, due to their insensitivity to intense $\gamma$-ray backgrounds and strong electromagnetic pulses (EMP).\\ This paper…
Data-driven models analyze power grids under incomplete physical information, and their accuracy has been mostly validated empirically using certain training and testing datasets. This paper explores error bounds for data-driven models…
The exploration of complex physical or technological processes usually requires exploiting available information from different sources: (i) physical laws often represented as a family of parameter dependent partial differential equations…
I consider the $\gamma W$-box correction to superallowed nuclear $\beta$-decays in the framework of dispersion relations. I address a novel effect of a distortion of the emitted electron energy spectrum by nuclear polarizabilities and show…
Radiative corrections are playing an increasingly significant role in low-energy nuclear physics. We investigate the influence of photons as explicit degrees of freedom within nuclear EFT on the deuteron binding energy, charge form factor,…
We identify a new, flux-dependent correction to the antineutrino spectrum as produced in nuclear reactors. The abundance of certain nuclides, whose decay chains produce antineutrinos above the threshold for inverse beta decay, has a…
There are many complementing strategies to estimate the extrapolation errors of a model which was calibrated in least-squares fits. We consider the Skyrme-Hartree-Fock model for nuclear structure and dynamics and exemplify the following…
The inverse problem methodology is a commonly-used framework in the sciences for parameter estimation and inference. It is typically performed by fitting a mathematical model to noisy experimental data. There are two significant sources of…
Nuclear density functional theory (DFT) is one of the main theoretical tools used to study the properties of heavy and superheavy elements, or to describe the structure of nuclei far from stability. While on-going efforts seek to better…
Over past years, the easy accessibility to the large scale datasets has significantly shifted the paradigm for developing highly accurate prediction models that are driven from Neural Network (NN). These models can be potentially impacted…
Electric dipole moments (edms) of bound states that arise from the constituents having edms are studied with field-theoretic techniques. The systems treated are the neutron and a set of paramagnetic atoms. In the latter case it is well…
The nuclear-polarization (NP) energies with the collective model commonly employed in the NP calculations for hydrogenlike heavy ions are found to have serious gauge violations when the ladder and cross diagrams only are taken into account.…
Power flow analysis plays a critical role in the control and operation of power systems. The high computational burden of traditional solution methods led to a shift towards data-driven approaches, exploiting the availability of digital…
A quantitative understanding of the weak nuclear response is a prerequisite for the analyses of neutrino experiments such as K2K and MiniBOONE, which measure energy and angle of the muons produced in neutrino-nucleus interactions in the…
Power flow analysis is used to evaluate the flow of electricity in the power system network. Power flow calculation is used to determine the steady-state variables of the system, such as the voltage magnitude/phase angle of each bus and the…
New constraints for the nuclear equation of state at suprasaturation densities have been obtained by measuring collective particle flows in heavy-ion reactions at relativistic energies. Ratios and differences of neutron and hydrogen flows…
Some inverse problems in high-energy physics, neutron diffraction and NMR spectroscopy are discussed. To solve them, the Fourier integrated transformation method and the Maximum Entropy Technique (MENT) were used. The integrated images of…
We consider a model-based approach to perform batch off-policy evaluation in reinforcement learning. Our method takes a mixture-of-experts approach to combine parametric and non-parametric models of the environment such that the final value…
Nuclear reactors provide intense sources of electron antineutrinos, characterized by few-MeV energy E and unoscillated spectral shape Phi(E). High-statistics observations of reactor neutrino oscillations over medium-baseline distances L ~…