arXiv subjects

C. S. Chen

Publications and source records attributed to C. S. Chen.

13 recordsLinked to original sources

arXiv2025

3D Surface Reconstruction and Volume Approximation via the meshless methods

In this paper, we propose several mathematical models for 3D surface reconstruction and volume estimation from a set of scattered cloud data. Three meshless methods including the interpolation-based method by RBF, PDE-based approach by Kansa's method and the Method of Fundamental Solutions are employed and compared. For the optimal recovery of the surfaces, the selection of free parameters in related PDE models are further studied and analyzed. Besides, several criteria like distance are employed in above methods instead of the classical parameter lambda determination strategy, which leads to a more reliable reconstruction performance. Finally, the volume estimation of 3D irregular objects is proposed based on the optimal reconstructed geometric models via proposed meshless methods. Numerous numerical examples are presented to demonstrate the effectiveness of the proposed surface reconstruction methods and the volume estimation strategy.

math.NA↗

arXiv2024

Highway Networks for Improved Surface Reconstruction: The Role of Residuals and Weight Updates

Surface reconstruction from point clouds is a fundamental challenge in computer graphics and medical imaging. In this paper, we explore the application of advanced neural network architectures for the accurate and efficient reconstruction of surfaces from data points. We introduce a novel variant of the Highway network (Hw) called Square-Highway (SqrHw) within the context of multilayer perceptrons and investigate its performance alongside plain neural networks and a simplified Hw in various numerical examples. These examples include the reconstruction of simple and complex surfaces, such as spheres, human hands, and intricate models like the Stanford Bunny. We analyze the impact of factors such as the number of hidden layers, interior and exterior points, and data distribution on surface reconstruction quality. Our results show that the proposed SqrHw architecture outperforms other neural network configurations, achieving faster convergence and higher-quality surface reconstructions. Additionally, we demonstrate the SqrHw's ability to predict surfaces over missing data, a valuable feature for challenging applications like medical imaging. Furthermore, our study delves into further details, demonstrating that the proposed method based on highway networks yields more stable weight norms and backpropagation gradients compared to the Plain Network architecture. This research not only advances the field of computer graphics but also holds utility for other purposes such as function interpolation and physics-informed neural networks, which integrate multilayer perceptrons into their algorithms.

cs.CV↗

arXiv2024

Stable Weight Updating: A Key to Reliable PDE Solutions Using Deep Learning

Background: Deep learning techniques, particularly neural networks, have revolutionized computational physics, offering powerful tools for solving complex partial differential equations (PDEs). However, ensuring stability and efficiency remains a challenge, especially in scenarios involving nonlinear and time-dependent equations. Methodology: This paper introduces novel residual-based architectures, namely the Simple Highway Network and the Squared Residual Network, designed to enhance stability and accuracy in physics-informed neural networks (PINNs). These architectures augment traditional neural networks by incorporating residual connections, which facilitate smoother weight updates and improve backpropagation efficiency. Results: Through extensive numerical experiments across various examples including linear and nonlinear, time-dependent and independent PDEs we demonstrate the efficacy of the proposed architectures. The Squared Residual Network, in particular, exhibits robust performance, achieving enhanced stability and accuracy compared to conventional neural networks. These findings underscore the potential of residual-based architectures in advancing deep learning for PDEs and computational physics applications.

cs.AI↗

arXiv2024

Power-Enhanced Residual Network for Function Approximation and Physics-Informed Inverse Problems

In this study, we investigate how the updating of weights during forward operation and the computation of gradients during backpropagation impact the optimization process, training procedure, and overall performance of the neural network, particularly the multi-layer perceptrons (MLPs). This paper introduces a novel neural network structure called the Power-Enhancing residual network, inspired by highway network and residual network, designed to improve the network's capabilities for both smooth and non-smooth functions approximation in 2D and 3D settings. By incorporating power terms into residual elements, the architecture enhances the stability of weight updating, thereby facilitating better convergence and accuracy. The study explores network depth, width, and optimization methods, showing the architecture's adaptability and performance advantages. Consistently, the results emphasize the exceptional accuracy of the proposed Power-Enhancing residual network, particularly for non-smooth functions. Real-world examples also confirm its superiority over plain neural network in terms of accuracy, convergence, and efficiency. Moreover, the proposed architecture is also applied to solving the inverse Burgers' equation, demonstrating superior performance. In conclusion, the Power-Enhancing residual network offers a versatile solution that significantly enhances neural network capabilities by emphasizing the importance of stable weight updates for effective training in deep neural networks. The codes implemented are available at: \url{https://github.com/CMMAi/ResNet_for_PINN}.

cs.LG↗

arXiv2024

Two-Dimensional Phase-Fluctuating Superconductivity in Bulk-Crystalline NdO$_{0.5}$F$_{0.5}$BiS$_2$

We present a combined growth and transport study of superconducting single-crystalline NdO$_{0.5}$F$_{0.5}$BiS$_2$. Evidence of two-dimensional superconductivity with significant phase fluctuations of preformed Cooper pairs preceding the superconducting transition is reported. This result is based on three key observations. (1) The resistive superconducting transition temperature $T_c$ (defined by resistivity $ρ\rightarrow 0$) increases with increasing disorder. (2) As $T\rightarrow T_c$, the conductivity diverges significantly faster than what is expected from Gaussian fluctuations in two and three dimensions. (3) Non-Ohmic resistance behavior is observed in the superconducting state. Altogether, our observations are consistent with a temperature regime of phase-fluctuating superconductivity. The crystal structure with magnetic ordering tendencies in the NdO$_{0.5}$F$_{0.5}$ layers and (super)conductivity in the BiS$_2$ layers is likely responsible for the two-dimensional phase fluctuations. As such, NdO$_{0.5}$F$_{0.5}$BiS$_2$ falls into the class of unconventional ``laminar" bulk superconductors that include cuprate materials and 4Hb-TaS$_2$.

cond-mat.supr-con↗

arXiv2022

Spin excitations in the quantum dipolar magnet Yb(BaBO$_3$)$_3$

We report results of magnetization, specific-heat and muon-spin relaxation measurements on single crystals of disorder-free Yb$^{3+}$ triangular lattice Yb(BaBO$_3$)$_3$. The magnetization experiments show anisotropic magnetic properties with Curie-Weiss temperatures $θ_{\perp}=-1.40$~K ($H \perp c$) and $θ_{\parallel}=-1.16$~K ($H \parallel c$) determined from low temperature data. The absence of both long-range antiferromagnetic order and spin freezing is confirmed down to 0.27 K at zero field. A two-level Schottky anomaly due to the opening of the ground-state Kramers doublet is observed from the low-temperature specific-heat measurements when the applied magnetic fields $μ_0H >0.7$~T. At zero field, the increase of both $C_{\rm mag}/T$ and the muon spin relaxation rate $λ$ below 1~K is due to the electronic spin excitations, which often exist in quantum magnets where dipole-dipole interaction creates an anisotropy of magnetic properties. The spin excitation is also supported by the unusual maximum of field dependence of $λ$ due to the field-induced increase of the density of excitations. We argue that dipolar interaction is dominant and induces the spin dynamics in the quantum magnet Yb(BaBO$_3$)$_3$.

cond-mat.str-el↗

arXiv2021

Fluctuating magnetic droplets immersed in a sea of quantum spin liquid

The search of quantum spin liquid (QSL), an exotic magnetic state with strongly-fluctuating and highly-entangled spins down to zero temperature, is a main theme in current condensed matter physics. However, there is no smoking-gun evidence for deconfined spinons in any QSL candidate so far. The disorders and competing exchange interactions may prevent the formation of an ideal QSL state on frustrated spin lattices. Here we report comprehensive and systematic measurements of the magnetic susceptibility, ultra-low temperature specific heat, muon spin relaxation (muSR), nuclear magnetic resonance (NMR), and thermal conductivity for NaYbSe2 single crystals, in which Yb3+ ions with effective spin-1/2 form a perfect triangular lattice. All these complementary techniques find no evidence of long-range magnetic order down to their respective base temperatures. Instead, specific heat, muSR and NMR measurements suggest the coexistence of quasi-static and dynamic spins in NaYbSe2. The scattering from these quasi-static spins may cause the absence of magnetic thermal conductivity. Thus, we propose a scenario of fluctuating ferrimagnetic droplets immersed in a sea of QSL. This may be quite common on the way pursuing an ideal QSL, and provides a brand-new platform to study how a QSL state survives impurities and coexists with other magnetically ordered states.

cond-mat.str-el↗

arXiv2021

Muon spin rotation and relaxation study on topological noncentrosymmetric superconductor PbTaSe$_2$

Topological superconductivity is an exotic phenomenon due to the symmetry-protected topological surface state, in which a quantum system has an energy gap in the bulk but supports gapless excitations confined to its boundary. Symmetries including central and time-reversal (TRS), along with their relations with topology, are crucial for topological superconductivity. We report muon spin relaxation/rotation ($μ$SR) experiments on a topological noncentrosymmetric superconductor PbTaSe$_2$ to study its TRS and gap symmetry. Zero-field $μ$SR experiments indicate the absence of internal magnetic field in the superconducting state, consistent with previous $μ$SR results. Furthermore, transverse-field $μ$SR measurements reveals that the superconducting gap of PbTaSe$_2$ is an isotropic three-dimensional fully-gapped single-band. The fully-gapped results can help understand the pairing mechanism and further classify the topological superconductivity in this system.

cond-mat.supr-con↗

arXiv2009

Searching for doubly charged Higgs bosons in Möller scattering by resonance effects at linear $e^-e^-$ collider

We discuss the parity-violating left-right asymmetries (LRAs) in Möller scattering at the International Linear Collider (ILC) induced by doubly charged Higgs bosons in models with $SU(2)_L$ triplet and singlet scalar bosons, which couple to the left- and right-handed charged leptons, respectively. These bosons are important in the scenarios for the generation of the neutrino mass. We demonstrate that the contributions to the LRAs from the triplet and singlet bosons are opposite to each other. In particular, we show that the doubly charged Higgs boson from the singlet scalar can be tested at the ILC by using the resonance effect.

hep-ph↗

arXiv2008

Leptogenesis in the extension of the Zee-Babu model

We demonstrate that the extension of the Zee-Babu model can generate not only the small neutrino masses but also the baryon number asymmetry in the universe. In particular, we show that the scale of the singlet scalar responsible for the leptogenesis can be of order 1 TeV, that can be tested at the LHC and ILC. We also considered the possible minimal extension of this model to generate the dark matter.

hep-ph↗

arXiv2006

Generalized Study with Isospin-phased Topological Approach on the $B \to Kπ$ Puzzle

We study the decay processes $B \to K π$ by using generalized decay amplitudes with both the final state re-scattering strong phases and the topological quark diagrammatic strong phases included together as part of fitting parameters. Using a generalized approach, so called ``isospin phased topological approach'', for all the currently available data of $B \to K π$ decays, we determine the allowed values of the relevant theoretical parameters, corresponding to the electroweak penguin, the color-suppressed tree contribution, strong phase differences, etc. In order to find the most likely values of the parameters in a statistically reliable way, we use the $χ^2$ minimization technique. We find that the long distance final state re-scattering, when taken at proper value, can provide a reasonable fit to the standard model with the perturbative QCD estimated values, and therefore, it is premature to conclude that it requires new physics to explain the CP violating $B \to Kπ$ data.

hep-ph↗

arXiv2001

Data Acquisition and Uesr Interface of Beam Instrumentation System at SRRC

Data acquisition systems for the accelerator complex at SRRC composed various hardware and software components. Beam signals are processed by related processing electronics, and connect to control system by various type of interfaces in data acquisition front-end. These front-end include VME crates, personal computers and instruments bus adapters. Fast Ethernet connected all elements together with control consoles. User interface is running on control console. Real-time data capture; display and alaysis are supported on control console. Analysis tools based on Matlab scripts are adopted. Hardware and software implementation of the system will be presented. User interface supports are also described.

physics.ins-det↗

arXiv2001

Orbit Feedback System for the Storage Ring of SRRC

Orbit feedback system plays crucial roles for the operation of the 3rd generation light source. There are various issues in orbit feedback system should be addressed to achieve ultimate performance. The orbit feedback system in SRRC is upgraded recently to satisfy the requirement of demanding users. Based upon operational experiences of the last few years, new system was designed with more robustness and flexibility. Performance analysis tools are also developed to monitor system performance. Algorithms for feedback control, data acquisition and analysis are described and measurement is also presented.

physics.ins-det↗