69 research outputs found
Crossover from Non-Fermi-Liquid to Pseudogap Behavior in the Spectral of Local Impurity in Power-Law Diverging Multichannel Kondo Model
Full text linkMotivated by the emergence of higher-order van Hove singularities (VHS) with
power-law divergent density of states (DOS)
(, ) in materials, we investigate a
multichannel Kondo model involving conduction electrons near the higher-order
van Hove filling. This model considers channel and spin degrees of
freedom. Employing a renormalization group analysis and dynamical large-
approach, our results reveal a crossover from a non-Fermi liquid to pseudogap
behavior in the spectral properties of the local impurity at the overscreened
fixed point. At this critical fixed point, we precisely determine the
conditions under which the crossover occurs, either by tuning the exponent
or the ratio to a critical value. The results of this study
provide novel insights into the non-Fermi liquid and pseudogap behaviors
observed in strongly correlated systems, shedding light on the intriguing
interplay between higher-order van Hove singularities and multichannel Kondo
physics.Comment: 5 pages, 5 fugure
Hybrid high-order methods for elliptic PDEs on curved and complicated domains
Get PDFInternational audienceWe introduce a variant of the hybrid high-order method (HHO) employing Nitsche’s boundary penalty techniques for the Poisson problem on the curved and complicated Lipschitz domain. The proposed method has two advantages: Firstly, there are no face unknowns introduced on the boundary of the domain, which avoids the computation of the parameterized mapping for the face unknowns on the curved domain boundary. Secondly, using Nitsche’s boundary penalty techniques for weakly imposing Dirichlet boundary conditions one can obtain the stability and optimal error estimate independent of the number and measure of faces on the domain boundary. Finally, a numerical experiment is presented in this chapter to confirm the theoretical results
Preparation and Properties of Cross-Linked Starch Nanocrystals/Polylactic Acid Nanocomposites
Get PDFCross-linked starch nanocrystals (CStN)/polylactic acid (PLA) nanocomposites were prepared by blending CStN and PLA, wherein CStN were homogeneously dispersed in the nanocomposites. The structure and morphology of the nanocomposites were studied through FTIR, XRD, and SEM. The results of mechanical test showed that the strength and toughness of the nanocomposites could be improved when the additive amount of hydrophobic CStN was 3% (weight ratio). Meanwhile, the microstructures of tensile fracture surface showed that CStN were uniformly dispersed in PLA matrix, and the tensile fracture surface was presented as ductile fracture. Moreover, water vapor permeability experiments illustrated that the addition of CStN reduced the water vapor permeability of PLA nanocomposites, so CStN have some resistance to water vapor. Those above indicated that CStN have functions of reinforcement and toughness in PLA matrix; therefore, they are expected to be used as functional additives in polymer matrix such as PLA, polycaprolactone (PCL), and polybutylene succinate (PBS)
The Dawn of AI-Native EDA: Opportunities and Challenges of Large Circuit Models
Full text linkWithin the Electronic Design Automation (EDA) domain, AI-driven solutions
have emerged as formidable tools, yet they typically augment rather than
redefine existing methodologies. These solutions often repurpose deep learning
models from other domains, such as vision, text, and graph analytics, applying
them to circuit design without tailoring to the unique complexities of
electronic circuits. Such an AI4EDA approach falls short of achieving a
holistic design synthesis and understanding, overlooking the intricate
interplay of electrical, logical, and physical facets of circuit data. This
paper argues for a paradigm shift from AI4EDA towards AI-native EDA,
integrating AI at the core of the design process. Pivotal to this vision is the
development of a multimodal circuit representation learning technique, poised
to provide a comprehensive understanding by harmonizing and extracting insights
from varied data sources, such as functional specifications, RTL designs,
circuit netlists, and physical layouts. We champion the creation of large
circuit models (LCMs) that are inherently multimodal, crafted to decode and
express the rich semantics and structures of circuit data, thus fostering more
resilient, efficient, and inventive design methodologies. Embracing this
AI-native philosophy, we foresee a trajectory that transcends the current
innovation plateau in EDA, igniting a profound shift-left in electronic design
methodology. The envisioned advancements herald not just an evolution of
existing EDA tools but a revolution, giving rise to novel instruments of design
tools that promise to radically enhance design productivity and inaugurate a
new epoch where the optimization of circuit performance, power, and area (PPA)
is achieved not incrementally, but through leaps that redefine the benchmarks
of electronic systems' capabilities.Comment: The authors are ordered alphabetically. Contact:
qxu@cse[dot]cuhk[dot]edu[dot]hk, gluo@pku[dot]edu[dot]cn,
yuan.mingxuan@huawei[dot]co
China’s 10-year progress in DC gas-insulated equipment: From basic research to industry perspective
Get PDFThe construction of the future energy structure of China under the 2050 carbon-neutral vision requires compact direct current (DC) gas-insulation equipment as important nodes and solutions to support electric power transmission and distribution of long-distance and large-capacity. This paper reviews China's 10-year progress in DC gas-insulated equipment. Important progresses in basic research and industry perspective are presented, with related scientific issues and technical bottlenecks being discussed. The progress in DC gas-insulated equipment worldwide (Europe, Japan, America) is also reported briefly
Hybrid high-order methods for elliptic PDEs on curved and complicated domains
Get PDFWe introduce a hybrid high-order method employing Nitsche's boundary penalty techniques for the Poisson problem on the curved and complicated domain. There are two key ideas in this work: Firstly, the methods employ the Nitsche-type boundary penalty technique to weakly enforce the boundary conditions, which avoids the computation of the parameterized mapping for the curved boundary. Secondly, an optimal L2 error estimate for the Poisson problem with mixed Dirichlet and Neumann boundary conditions is derived. Moreover, the stability and optimal error estimate for the proposed HHO methods are independent of the number and measure of faces on the domain boundary. Finally, a numerical experiment is presented in this chapter to confirm the theoretical results
A priori and a posteriori error estimates of a DG-CG method for the wave equation in second order formulation
No full textWe establish fully-discrete a priori and semi-discrete in time a posteriori error estimates for a discontinuous-continuous Galerkin discretization of the wave equation in second order formulation; the resulting method is a Petrov-Galerkin scheme based on piecewise and piecewise continuous polynomial in time test and trial spaces, respectively. Crucial tools in the a priori analysis for the fully-discrete formulation are the design of suitable projection and interpolation operators extending those used in the parabolic setting, and stability estimates based on a nonstandard choice of the test function; a priori estimates are shown, which are measured in -type norms in time. For the semi-discrete in time formulation, we exhibit constant-free, reliable a posteriori error estimates for the error measured in the norm; to this aim, we design a reconstruction operator into piecewise polynomials over the time grid with optimal approximation properties in terms of the polynomial degree distribution and the time steps. Numerical examples illustrate the theoretical findings
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