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We present a multiscale mixed finite element method for solving second order elliptic equations with general $L^{\infty}$-coefficients arising from flow in highly heterogeneous porous media. Our approach is based on a multiscale spectral…

Numerical Analysis · Mathematics 2024-04-05 Christian Alber , Chupeng Ma , Robert Scheichl

The density matrix renormalization group (DMRG) method and its applications to finite temperatures and two-dimensional systems are reviewed. The basic idea of the original DMRG method, which allows precise study of the ground state…

Strongly Correlated Electrons · Physics 2009-11-10 Naokazu Shibata

The availability of large-scale datasets collected via mobile phones has opened up opportunities to study human mobility at an individual level. The granular nature of these datasets calls for the design of summary statistics that can be…

Physics and Society · Physics 2021-08-19 Rohit Sahasrabuddhe , Renaud Lambiotte , Laura Alessandretti

An orbital-angular-momentum (OAM) mode-group multiplexing (MGM) scheme based on a graded-index ring-core fiber (GIRCF) is proposed, in which a single-input two-output (or receive diversity) architecture is designed for each MG channel and…

Signal Processing · Electrical Eng. & Systems 2018-03-14 Junwei Zhang , Guoxuan Zhu , Liu Jie , Xiong Wu , Jianbo Zhu , Cheng Du , Wenyong Luo , Siyuan Yu

We present an approach to extend plasma transport theory into the Warm Dense Matter (WDM) regime characterized by moderate Coulomb coupling and electron degeneracy. It is based on a recently proposed closure of the BBGKY hierarchy that…

Plasma Physics · Physics 2020-01-31 Shane Rightley , Scott D. Baalrud

The construction of the Hamiltonian matrix \textbf{H} is an essential, yet computationally expensive step in \textit{ab-initio} device simulations based on density-functional theory (DFT). In homogeneous structures, the fact that a unit…

Disordered Systems and Neural Networks · Physics 2026-02-03 Chen Hao Xia , Manasa Kaniselvan , Marko Mladenoivić , Mathieu Luisier

We introduce a novel model called GAMMT (Generative Ambiguity Models using Multiple Transformers) for sequential data that is based on sets of probabilities. Unlike conventional models, our approach acknowledges that the data generation…

Machine Learning · Computer Science 2023-04-05 Xingcheng Xu

This paper presents a formulation of the reactive dynamic user equilibrium problem in continuum form using a network-level Macroscopic Fundamental Diagram (MFD). Compared to existing continuum models for cities -- all based in Hughes'…

Analysis of PDEs · Mathematics 2020-08-25 Rafegh Aghamohammadi , Jorge A. Laval

Integrated sensing and communication is widely acknowledged as a foundational technology for next-generation mobile networks. Compared with monostatic sensing, multi-access point (AP) collaborative sensing endows mobile networks with…

Signal Processing · Electrical Eng. & Systems 2025-12-03 Shengheng Liu , Xingkang Li , Yongming Huang , Yuan Fang , Qingji Jiang , Dazhuan Xu , Ziguo Zhong , Dongming Wang , Xiaohu You

Sensorless control of Permanent-Magnet Synchronous Motors (PMSM) at low velocity remains a challenging task. A now well-established method consists in injecting a high-frequency signal and use the rotor saliency, both geometric and…

Optimization and Control · Mathematics 2012-07-25 Al Kassem Jebai , Francois Malrait , Philippe Martin , Pierre Rouchon

In this letter, a novel communication paradigm for simultaneous wireless information and power transfer (SWIPT) is proposed, which leverages the thermal characteristics of electromagnetic signals. In particular, the proposed scheme exploits…

Information Theory · Computer Science 2024-03-27 Elio Faddoul , Yuan Guo , Christodoulos Skouroumounis , Ioannis Krikidis

The Density Matrix Renormalization Group (DMRG) has become a powerful numerical method that can be applied to low-dimensional strongly correlated fermionic and bosonic systems. It allows for a very precise calculation of static, dynamical…

Condensed Matter · Physics 2007-05-23 Karen Hallberg

Numerical analytical heat transfer models play a critical role in geothermal design and feasibility studies. Classical solutions, such as those proposed by Gringarten et al. 1975, rely on simplified assumptions and systematically…

We explore the response of many-body localized (MBL) systems to periodic driving of arbitrary amplitude, focusing on the rate at which they exchange energy with the drive. To this end, we introduce an infinite-temperature generalization of…

Disordered Systems and Neural Networks · Physics 2016-09-21 Sarang Gopalakrishnan , Michael Knap , Eugene Demler

Energy-based models for discrete domains, such as graphs, explicitly capture relative likelihoods, naturally enabling composable probabilistic inference tasks like conditional generation or enforcing constraints at test-time. However,…

To determine the electron heat flux density on macroscopic scales, the most widely used approach is to solve a diffusion equation through a multi-group technique. This method is however restricted to transport induced by temperature…

Multi-output Gaussian process (MGP) models have attracted significant attention for their flexibility and uncertainty-quantification capabilities, and have been widely adopted in multi-source transfer learning scenarios due to their ability…

Machine Learning · Computer Science 2025-12-12 Duo Wang , Xinming Wang , Chao Wang , Xiaowei Yue , Jianguo Wu

Spatial multiscale methods have established themselves as useful tools for extending the length scales accessible by conventional statics (i.e., zero temperature molecular dynamics). Recently, extensions of these methods, such as the…

Numerical Analysis · Mathematics 2014-09-23 Andrew Binder , Mitchell Luskin , Danny Perez , Arthur F. Voter

We propose a unified, few-step generative modeling framework based on \emph{cumulative flow maps} for long-range transport in probability space, inspired by flow-map techniques for physical transport and dynamics. At its core is a…

Machine Learning · Computer Science 2026-05-06 Zhiqi Li , Duowen Chen , Yuchen Sun , Bo Zhu

We propose a multivariate log-normal distribution to jointly model received power, mean delay, and root mean square (rms) delay spread of wideband radio channels, referred to as the standardized temporal moments. The model is validated…

Signal Processing · Electrical Eng. & Systems 2021-09-01 Ayush Bharti , Ramoni Adeogun , Xuesong Cai , Wei Fan , François-Xavier Briol , Laurent Clavier , Troels Pedersen