相关论文: The East Lansing Model: a Bayesian uncertainty qua…
The primary aim of this research is to evaluate several convolutional neural network-based object detection algorithms for identifying oscillation-like patterns in light curves of eclipsing binaries. This involves creating a robust…
A model is proposed for the statistical analysis of arbitrary-strength quantum measurements, based on a picture of "sampling weak values" from different configurations of the system. The model is comprised of two elements: a "local weak…
Over the last two decades, the Latent Position Model (LPM) has become a prominent tool to obtain model-based visualizations of networks. However, the geometric structure of the LPM is inherently symmetric, in the sense that outgoing and…
The isoscaling behavior is investigated using the isotopic/isobaric yields from the equilibrated thermal source which is prepared by the lattice gas model for lighter systems with A = 36. The isoscaling parameters $\alpha$ and -$\beta$ are…
In this contribution, we briefly present the equation-of-state modelling for application to neutron stars and discuss current constraints coming from nuclear physics theory and experiments. To assess the impact of model uncertainties, we…
Measurements of neutron star mass and radius or tidal deformability deliver unique insight into the equation of state (EOS) of cold dense matter. EOS inference is very often done using generalized parametric or non-parametric models which…
A central open problem in nuclear physics is the determination of a physically robust equation of state (EoS) for dense nuclear matter, which directly informs our understanding of the internal composition and macroscopic properties of…
The equation of state (EOS) of dense nuclear matter is a key factor to determine the internal structure and properties of neutron stars. However, the EOS of high-density nuclear matter has great uncertainty mainly because the terrestrial…
In this thesis the polarized and unpolarized photon distributions of the nucleon (proton, neutron) $(\Delta)\gamma^N$, evaluated in the equivalent photon approximation (EPA), are computed theoretically and the possibility of their…
The reliability of a previous $\alpha$-particle optical-model potential (OMP) on nuclei with mass number 45$\leq$$A$$\leq$209 was proved for emitted $\alpha$ particles as well, for proton--induced reactions on Zn isotopes [Phys. Rev. C {\bf…
Identification of defects or anomalies in 3D objects is a crucial task to ensure correct functionality. In this work, we combine Bayesian learning with recent developments in quantum and quantum-inspired machine learning, specifically…
We investigate the possibility of measuring the Hubble constant, the fractional energy density components and the equation of state parameter of the ``dark energy'' using lensed multiple images of high-redshift supernovae. With future…
A relativistic microscopic optical model potential for nucleon-nucleus scattering is developed based on the \emph{ab initio} relativistic Brueckner-Hartree-Fock (RBHF) theory with the improved local density approximation, which is…
The use of quasi-elastic electron nucleus scattering is shown to provide significant constraints on models of the proton electromagnetic form factor of off-shell nucleons. Such models can be constructed to be consistent with constraints…
Nuclear matter and neutron stars are studied in the framework of an extended relativistic mean-field (RMF) model with higher-order derivative and density dependent couplings of nucleons to the meson fields. The derivative couplings lead to…
A sensitive search for neutron-antineutron oscillations can provide a unique probe of some of the central questions in particle physics and cosmology: the energy scale and mechanism for baryon number violation, the origin of the…
We investigate the isovector component in the phenomenological mean field model of nuclei. Lane's isospin dependence, initially proposed for the nuclear optical potential, is reexamined within the context of bound states using the…
The equation of state (EOS) for neutron stars is modeled using the Relativistic Mean Field (RMF) approach with a mesonic nonlinear (NL) interaction, a modified sigma cut potential (NL-$\sigma$ cut), and the influences of dark matter in the…
Machine learning potentials (MLPs) have become essential for large-scale atomistic simulations, enabling ab initio-level accuracy with computational efficiency. However, current MLPs struggle with uncertainty quantification, limiting their…
Cosmic shear estimation is an essential scientific goal for large galaxy surveys. It refers to the coherent distortion of distant galaxy images due to weak gravitational lensing along the line of sight. It can be used as a tracer of the…