arXiv subjects

Junqiang Bai

Publications and source records attributed to Junqiang Bai.

3 recordsLinked to original sources

arXiv2026

Ultraviolet boundary condition and the Higgs mass

Within the emergence framework, in which infrared physics is not fixed by ultraviolet Lagrangian parameters, the hypothesis that the Higgs quartic coupling vanishes at the Planck scale is tested within the full two-loop Standard Model. With lambda(M_P) = 0 imposed as the sole boundary condition and all other inputs fixed by experiment, a Higgs mass of m_h = 121.99 GeV is obtained from complete two-loop renormalisation-group evolution and full two-loop threshold matching. This lies 3.21 GeV (2.6%) below the measured value of 125.20 GeV. The dominant theoretical uncertainty, +/- 1.5 GeV, arises from unknown three-loop effects and is estimated by perturbative power counting. The calculation tests the simplest ultraviolet boundary condition consistent with the emergence framework of Ref. [1]. The agreement is meaningful at the available precision, since the hypothesis could easily have been excluded by a wide margin. A sharper test requires a complete three-loop calculation and an improved top-quark mass measurement.

hep-ph↗

arXiv2025

A point cloud reconstruction method based on uncertainty feature enhancement for aerodynamic shape optimization

The precision of shape representation and the dimensionality of the design space significantly influence the cost and outcomes of aerodynamic optimization. The design space can be represented more compactly by maintaining geometric precision while reducing dimensions, hence enhancing the cost-effectiveness of the optimization process. This research presents a new point cloud autoencoder architecture, called AE-BUFE, designed to attain efficient and precise generalized representations of 3D aircraft through uncertainty analysis of the deformation relationships among surface grid points. The deep learning architecture consists of two components: the uncertainty index-based feature enhancement module and the point cloud autoencoder module. It learns the shape features of the point cloud geometric representation to establish a low-dimensional latent space. To assess and evaluate the efficiency of the method, a comparison was conducted with the prevailing point cloud autoencoder architecture and the proper orthogonal decomposition (POD) linear dimensionality reduction method under conditions of complex shape deformation. The results showed that the new architecture significantly improved the extraction effect of the low-dimensional latent space. Then, we developed the SBO optimization framework based on the AE-BUFE parameterization method and completed a multi-objective aerodynamic optimization design for a wide-speed-range vehicle considering volume and moment constraints. While ensuring the take-off and landing performance, the aerodynamic performance is improved at transonic and hypersonic conditions, which verifies the efficiency and engineering practicability of this method.

math.OC↗

arXiv2020

Topology optimization of surface flows

This paper presents a topology optimization approach for surface flows, which can represent the viscous and incompressible fluidic motions at the solid/liquid and liquid/vapor interfaces. The fluidic motions on such material interfaces can be described by the surface Navier-Stokes equations defined on 2-manifolds or two-dimensional manifolds, where the elementary tangential calculus is implemented in terms of exterior differential operators expressed in a Cartesian system. Based on the topology optimization model for fluidic flows with porous medium filling the design domain, an artificial Darcy friction is added to the area force term of the surface Navier-Stokes equations and the physical area forces are penalized to eliminate their existence in the fluidic regions and to avoid the invalidity of the porous medium model. Topology optimization for steady and unsteady surface flows can be implemented by iteratively evolving the impermeability of the porous medium on the 2-manifolds, where the impermeability is interpolated by the material density derived from a design variable. The related partial differential equations are solved by using the surface finite element method. Numerical examples have been provided to demonstrate this topology optimization approach for surface flows, including the boundary velocity driven flows, area force driven flows and convection-diffusion flows.

physics.comp-ph↗