arXiv subjects

Mengyao Huang

Publications and source records attributed to Mengyao Huang.

5 recordsLinked to original sources

arXiv2026

Halo structure of $^6$He from $\textit{ab initio}$ two-nucleon spatial correlations

We evaluate pairwise correlations using ground state wave functions for $^4$He and $^6$He obtained by $\textit{ab initio}$ no-core shell model calculations with the Daejeon16 nucleon-nucleon interaction plus Coulomb interaction, to characterize the structures of these two systems. We demonstrate that two-nucleon spatial correlations, specifically the pair-number operator $r^0$ and the square-separation operator $r^2$ projected on two-body spin $S$ and isospin $z$ components encode important details of the halo structure of $^6$He. We also analyze the single-particle state occupancies and the two-body state occupancies for the ground state of $^4$He and $^6$He. Our results indicate that the two valence neutrons in the ground state of $^6$He dominantly form a spin-singlet configuration. The rms pair separations between core nucleons and halo neutrons of $^6$He are, on average, about 80% larger than pair separations within the swollen and off-centered "$α$ core". We show that this off-centering effect is primarily responsible for the observed increase in point-proton radius $r_p$ in $^6$He relative to $^4$He.

nucl-th↗

arXiv2025

Quantifying uncertainty in machine learning on nuclear binding energy

Techniques from artificial intelligence and machine learning are increasingly employed in nuclear theory, however, the uncertainties that arise from the complex parameter manifold encoded by the neural networks are often overlooked. Epistemic uncertainties arising from training the same network multiple times for an ensemble of initial weight sets offer a first insight into the confidence of machine learning predictions, but they often come with a high computational cost. Instead, we apply a single-model uncertainty quantification method called Δ-UQ that gives epistemic uncertainties with one-time training. We demonstrate our approach on a 2-feature model of nuclear binding energies per nucleon with proton and neutron number pairs as inputs. We show that Δ-UQ can produce reliable and self-consistent epistemic uncertainty estimates and can be used to assess the degree of confidence in predictions made with deep neural networks.

nucl-th↗

arXiv2023

Quantum Information Science and Technology for Nuclear Physics. Input into U.S. Long-Range Planning, 2023

In preparation for the 2023 NSAC Long Range Plan (LRP), members of the Nuclear Science community gathered to discuss the current state of, and plans for further leveraging opportunities in, QIST in NP research at the Quantum Information Science for U.S. Nuclear Physics Long Range Planning workshop, held in Santa Fe, New Mexico on January 31 - February 1, 2023. The workshop included 45 in-person participants and 53 remote attendees. The outcome of the workshop identified strategic plans and requirements for the next 5-10 years to advance quantum sensing and quantum simulations within NP, and to develop a diverse quantum-ready workforce. The plans include resolutions endorsed by the participants to address the compelling scientific opportunities at the intersections of NP and QIST. These endorsements are aligned with similar affirmations by the LRP Computational Nuclear Physics and AI/ML Workshop, the Nuclear Structure, Reactions, and Astrophysics LRP Town Hall, and the Fundamental Symmetries, Neutrons, and Neutrinos LRP Town Hall communities.

nucl-ex↗

arXiv2022

Critical Coupling for Two-dimensional $ϕ^4$ Theory in Discretized Light-Cone Quantization

We solve for the critical coupling in the symmetric phase of two-dimensional $ϕ^4$ field theory using Discretized Light-Cone Quantization. We adopt periodic boundary conditions, neglect the zero mode, and obtain a critical coupling consistent with the critical coupling reported using conformal truncation in light-front quantization. We find a 17% dfference from the critical coupling reported with light-front quantization in a symmetric polynomial basis.

hep-th↗

arXiv2019

Simulation Study of Energy Resolution with Changing Pixel Size for Radon Monitor Based on \textit{Topmetal-${II}^-$} TPC

In this paper, we study how pixel size influences energy resolution for a proposed pixelated detector---a high sensitivity, low cost, and real-time radon monitor based on \textit{Topmetal-${II}^-$} time projection chamber (TPC). Using \textit{Topmetal-${II}^-$} sensors assembled by 0.35 $μ$m CMOS Integrated Circuit process, this monitor is designed to improve the spatial resolution of detecting radon alpha particles. Concerning small pixel size might has a side effect of worsening energy resolution due to lower signal to noise ratio, a Great4-based simulation is used to figure out energy resolution dependence on pixel size ranging from 60 $μ$m to 600 $μ$m. A non-monotonic trend in this region shows a combination effect of pixel size with threshold on pixel, and is analyzed by introducing an empirical expression. Noise on pixel contributes 50 keV Full Width at Half Maximum (FWHM) energy resolution for 400 $μ$m pixel size at 1 $\sim$ 4 $σ$ threshold, which is comparable to the energy resolution caused by energy fluctuation in ionization process of TPC ($\sim$ 20 keV). The total energy resolution after combining both factors is estimated to be 54 keV for 400 $μ$m pixel size at 1 $\sim$ 4 $σ$ threshold. The analysis presented in this paper is helpful to choosing suitable pixel size for future pixelated detectors.

physics.ins-det↗