Zobrazeno 1 - 10
of 126 546
pro vyhledávání: '"Li,Jun"'
Autor:
Li, Jun-Xian, Wang, Shuang
Holographic dark energy (HDE), which arises from a theoretical attempt of applying the holographic principle (HP) to the dark energy (DE) problem, has attracted significant attention over the past two decades. We perform a most comprehensive numerica
Externí odkaz:
http://arxiv.org/abs/2412.09064
Autor:
Zhang, Meng, Li, Jun
Achieving efficient, high-fidelity, high-resolution garment simulation is challenging due to its computational demands. Conversely, low-resolution garment simulation is more accessible and ideal for low-budget devices like smartphones. In this paper,
Externí odkaz:
http://arxiv.org/abs/2412.06285
Using an underdamped active Ornstein-Uhlenbeck particle, we propose two information swimmer models having either external or internal feedback control and perform their numerical simulations. Depending on the velocity that is measured after every fix
Externí odkaz:
http://arxiv.org/abs/2412.04723
This paper introduces a novel one-hop sub-query result cache for processing graph read transactions, gR-Txs, in a graph database system. The one-hop navigation is from a vertex using either its in-coming or out-going edges with selection predicates t
Externí odkaz:
http://arxiv.org/abs/2412.04698
In this paper, a learning based Model Predictive Control (MPC) using a low dimensional residual model is proposed for autonomous driving. One of the critical challenge in autonomous driving is the complexity of vehicle dynamics, which impedes the for
Externí odkaz:
http://arxiv.org/abs/2412.03874
The stochastic gravitational-wave background originating from cosmic sources contains vital information about the early universe. In this work, we comprehensively study the cross-correlations between the energy-density anisotropies in scalar-induced
Externí odkaz:
http://arxiv.org/abs/2412.02500
We propose a one-dimensional mixing model to investigate the impact of Ablative Rayleigh-Taylor Instability (ARTI) on compression, addressing the limitations of high-dimensional simulations. In this model, the scale of the mixed region is predicted u
Externí odkaz:
http://arxiv.org/abs/2412.00699
This paper investigates an intelligent reflecting surface (IRS) aided wireless federated learning (FL) system, where an access point (AP) coordinates multiple edge devices to train a machine leaning model without sharing their own raw data. During th
Externí odkaz:
http://arxiv.org/abs/2412.00422
Traditional standard single-mode fibers (SSMF) are unable to satisfy the future long-distance and high-speed optical channel transmission requirement due to their relatively large signal losses. To address this issue, the ultra-low loss and large eff
Externí odkaz:
http://arxiv.org/abs/2411.16159