Zobrazeno 1 - 10
of 293 357
pro vyhledávání: '"hybrid approach"'
Autor:
Agatha Jin Jin Lau1, Chi Wee Tan2
Publikováno v:
Journal of Telecommunications & the Digital Economy. Sep2024, Vol. 12 Issue 3, p73-96. 24p.
An accurate calculation of the leading-order hadronic vacuum polarisation (LOHVP) contribution to the anomalous magnetic moment of the muon ($a_\mu$) is key to determining whether a discrepancy, suggesting new physics, exists between the Standard Mod
Externí odkaz:
http://arxiv.org/abs/2410.23832
Scatterometry is a tested method for measuring periodic semiconductor structures. Since the sizes of modern semiconductor structures have reached the nanoscale regime, the challenge is to determine the shape of periodic nanostructures with sub-nanome
Externí odkaz:
http://arxiv.org/abs/2410.24048
The recent rise of deep learning has led to numerous applications, including solving partial differential equations using Physics-Informed Neural Networks. This approach has proven highly effective in several academic cases. However, their lack of ph
Externí odkaz:
http://arxiv.org/abs/2410.02819
Large language models (LLMs) have demonstrated remarkable performance across various downstream tasks. However, the high computational and memory requirements of LLMs are a major bottleneck. To address this, parameter-efficient fine-tuning (PEFT) met
Externí odkaz:
http://arxiv.org/abs/2410.20777
Autor:
Roy, Nirmali, Jha, Anuradha
In this article, we study a two-dimensional singularly perturbed parabolic equation of the convection-diffusion type, characterized by discontinuities in the source term and convection coefficient at a specific point in the domain. These discontinuit
Externí odkaz:
http://arxiv.org/abs/2410.14125
Autor:
Sripat, Abhiram
We propose a novel hybrid quantum-classical framework that integrates the Quantum Approximate Optimization Algorithm (QAOA) and Quantum-enhanced Markov Chain Monte Carlo (QMCMC) with variational particle filters to tackle the computational challenges
Externí odkaz:
http://arxiv.org/abs/2410.03853
We present phenomenological findings on charm quark transport while including its energy loss in both pre-equilibrium and hydrodynamic stages of the evolution. We employed the MARTINI event generator for the production and evolution of heavy quarks i
Externí odkaz:
http://arxiv.org/abs/2409.15038
The present study introduces an innovative approach to the synthesis of Electroencephalogram (EEG) signals by integrating diffusion models with reinforcement learning. This integration addresses key challenges associated with traditional EEG data acq
Externí odkaz:
http://arxiv.org/abs/2410.00013