Classification of Argyres-Douglas theories from M5 branes

We obtain a large class of new 4d Argyres-Douglas theories by classifying irregular punctures for the 6d (2,0) superconformal theory of ADE type on a sphere. Along the way, we identify the connection between the Hitchin system and three-fold singularity descriptions of the same Argyres-Douglas theory. Other constructions such as taking degeneration limits of the irregular puncture, adding an extra regular puncture, and introducing outer-automorphism twists are also discussed. Later we investigate various features of these theories including their Coulomb branch spectrum and central charges.Comment: 35 pages, 9 tables, 6 figures. v2: minor correction

Customer environmental concerns and profit margin: Evidence from manufacturing firms

This study evaluates the impact of customer environmental concerns on manufacturing firms’ profit margin. Eco-conscious customers may have a high demand for green products and are willing to pay a price premium for those products. The green effect is subject to the degree of greenness in production processes. In addition, environmental investments reduce the negative impact of production processes on the natural environment, alleviating customers’ environmental concerns. However, environmental investments increase product costs, which may subsequently offset economic benefits from eco-conscious customers. As such, we test the impact of customer environmental concerns on profit margin by controlling for the greenness levels (represented by energy consumption) and environmental investments (represented by energy efficiency measures). Based on a sample of 5390 manufacturing firms in 25 Central and Eastern European and Central Asian countries, our empirical results indicate a positive impact of customer environmental concerns on profit margins for low energy-intensity firms and a negative impact for high energy-intensity firms. In addition, high energy-intensity firms with energy efficiency measures are more negatively affected by customer environmental concerns than those with energy efficiency measures.publishedVersio

Tensor Neural Network and Its Numerical Integration

In this paper, we introduce a type of tensor neural network. For the first time, we propose its numerical integration scheme and prove the computational complexity to be the polynomial scale of the dimension. Based on the tensor product structure, we develop an efficient numerical integration method by using fixed quadrature points for the functions of the tensor neural network. The corresponding machine learning method is also introduced for solving high-dimensional problems. Some numerical examples are also provided to validate the theoretical results and the numerical algorithm.Comment: 27 pages, 30 figure

DBDNet:Partial-to-Partial Point Cloud Registration with Dual Branches Decoupling

Point cloud registration plays a crucial role in various computer vision tasks, and usually demands the resolution of partial overlap registration in practice. Most existing methods perform a serial calculation of rotation and translation, while jointly predicting overlap during registration, this coupling tends to degenerate the registration performance. In this paper, we propose an effective registration method with dual branches decoupling for partial-to-partial registration, dubbed as DBDNet. Specifically, we introduce a dual branches structure to eliminate mutual interference error between rotation and translation by separately creating two individual correspondence matrices. For partial-to-partial registration, we consider overlap prediction as a preordering task before the registration procedure. Accordingly, we present an overlap predictor that benefits from explicit feature interaction, which is achieved by the powerful attention mechanism to accurately predict pointwise masks. Furthermore, we design a multi-resolution feature extraction network to capture both local and global patterns thus enhancing both overlap prediction and registration module. Experimental results on both synthetic and real datasets validate the effectiveness of our proposed method.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl