Related papers: Target mass correction, based on the re-scaled par…
Matrix rank minimization problem is in general NP-hard. The nuclear norm is used to substitute the rank function in many recent studies. Nevertheless, the nuclear norm approximation adds all singular values together and the approximation…
The approach exposed in the recent paper (A. Shebeko, P. Papakonstantinou, E. Mavrommatis, Eur. Phys. J. A 27, 143 (2006)) has been applied in studying center-of-mass motion effects on the nucleon density and momentum distributions in…
The {\it Principle of Maximum Conformality} (PMC), which generalizes the conventional Gell-Mann-Low method for scale-setting in perturbative QED to non-Abelian QCD, provides a rigorous method for achieving unambiguous scheme-independent,…
Markov Chain Monte Carlo (MCMC) algorithms are essential tools in computational statistics for sampling from unnormalised probability distributions, but can be fragile when targeting high-dimensional, multimodal, or complex target…
Target mass corrections to the twist-4 terms $\tilde f_2^{p,n,d}$ as well as to the leading-twist $\tilde a_2$ are discussed.
We consider the recently introduced Transformation-based Markov Chain Monte Carlo (TMCMC) (Dutta and Bhattacharya (2014)), a methodology that is designed to update all the parameters simultaneously using some simple deterministic…
Markov chain Monte Carlo (MCMC) is a powerful tool for sampling from complex probability distributions. Despite its versatility, MCMC often suffers from strong autocorrelation and the negative sign problem, leading to slowing down the…
In the paper, we study approximation properties of the Malmquist-Takenaka-Christov (MTC) system. We show that the discrete MTC approximations converge rapidly under mild restrictions on functions asymptotic at infinity. This makes them…
We present an improved method of reconstructing New Physics (NP) masses from invariant mass endpoints. While the traditional method focuses on a single NP decay, our method considers the decays of two or more NP particles ($ABC...$) in a…
We derive mass corrections for semi-inclusive deep inelastic scattering of leptons from nucleons using a collinear factorization framework which incorporates the initial state mass of the target nucleon and the final state mass of the…
We propose a sampling-based framework for finite-horizon trajectory and policy optimization under differentiable dynamics by casting controller design as inference. Specifically, we minimize a KL-regularized expected trajectory cost, which…
Markov chain Monte Carlo (MCMC) methods are simulated by local exploration of complex statistical distributions, and while bypassing the cumbersome requirement of a specific analytical expression for the target, this stochastic exploration…
We have studied the deep inelastic scattering (DIS) of polarized charged leptons from polarized nucleon targets and evaluated the polarized nucleon structure functions $g_{1N,2N}(x,Q^2)$ as well as the nucleon asymmetries $A_{1N,2N}(x,Q^2)$…
Nuclear modification factors (NMFs) applied to A-B collision systems consist of $p_t$ spectrum ratios rescaled by an estimated number of nucleon-nucleon binary collisions. Interest in NMFs is motivated by possible modification…
The Peierls-Yoccoz projection method is used to study the motion of a relativistic system of nucleons interacting with sigma and omega mesons. The nuclear system is described in a mean-field Hartree approach, including explicitly the meson…
We discuss results from our global QCD analyses including nuclear data off deuterium from various measurements, as well as off $\htri$ and $\hetri$ targets from the \mara{} experiment. We simultaneously determine the parton distribution…
In this paper, we propose new proximal Newton-type methods for convex optimization problems in composite form. The applications include model predictive control (MPC) and embedded MPC. Our new methods are computationally attractive since…
The Markov Chain Monte Carlo (MCMC) methods are popular when considering sampling from a high-dimensional random variable $\mathbf{x}$ with possibly unnormalised probability density $p$ and observed data $\mathbf{d}$. However, MCMC requires…
A paramount goal in the field of nuclear physics is to unify ab-initio treatments of bound and unbound states. The position-space quantum Monte Carlo (QMC) methods have a long history of successful bound state calculations in light systems…
We present results for the scalar and tensor isovector-couplings ($g_S$ and $g_T$) of the nucleon measured at the physical point ($M_{\pi}=135$ MeV) with a single lattice spacing of $0.085\ \mathrm{fm}$ in 2+1 flavor QCD. Our calculations…