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Recent trends of ab initio studies and progress in methodologies for electronic structure calculations of strongly correlated electron systems are discussed. The interest for developing efficient methods is motivated by recent discoveries…

Strongly Correlated Electrons · Physics 2010-12-06 Masatoshi Imada , Takashi Miyake

We describe verification techniques for embedded memory systems using efficient memory modeling (EMM), without explicitly modeling each memory bit. We extend our previously proposed approach of EMM in Bounded Model Checking (BMC) for a…

Logic in Computer Science · Computer Science 2011-11-09 Malay K. Ganai , Aarti Gupta , Pranav Ashar

We have obtained an electromagnetic PIC (EM-PIC) algorithm based on time-space-extended particle in cell model. In this model particles are shaped objects extended over time and space around Lagrangian markers. Sources carried by these…

Plasma Physics · Physics 2011-09-09 J. Yazdanpanah

Electrical power systems are increasing in size, complexity, as well as dynamics due to the growing integration of renewable energy resources, which have sporadic power generation. This necessitates the development of near real-time power…

Machine Learning · Computer Science 2023-03-02 Ognjen Kundacina , Gorana Gojic , Mile Mitrovic , Dragisa Miskovic , Dejan Vukobratovic

Ab initio techniques have revolutionised the way in which theory can help practitioners to explore critical mechanisms that govern reactions or properties, and to develop new strategies for materials discovery and design. Yet, their…

Materials Science · Physics 2026-04-03 Mira Todorova , Stefan Wippermann , Jörg Neugebauer

The computational treatment of many-electron systems capable of exchanging {electrons and nuclei} with the environment represents one of the outermost frontiers in simulation methodology. The exchanging process occurs in a large variety of…

Chemical Physics · Physics 2019-02-21 Luigi Delle Site

Purpose: The computation methods for modeling, controlling and optimizing the transforming grid are evolving rapidly. We review and systemize knowledge for a special class of computation methods that solve large-scale power grid…

Systems and Control · Electrical Eng. & Systems 2025-01-09 Amritanshu Pandey , Mads Almassalkhi , Sam Chevalier

Electromagnetic transient (EMT) simulation is a crucial tool for power system dynamic analysis because of its detailed component modeling and high simulation accuracy. However, it suffers from computational burdens for large power grids…

Systems and Control · Electrical Eng. & Systems 2023-12-21 Min Xiong , Kaiyang Huang , Yang Liu , Rui Yao , Kai Sun , Feng Qiu

Electromagnetics has an important role to play in solving the next generation of geoscience problems. These problems are multidisciplinary, complex, and require collaboration. This is especially true at the base scientific level where the…

Geophysics · Physics 2022-03-29 Douglas W. Oldenburg , Lindsey J. Heagy , Seogi Kang , Rowan Cockett

Modeling and analysis of soft errors in electronic circuits has traditionally been done using computer simulations. Computer simulations cannot guarantee correctness of analysis because they utilize approximate real number representations…

Logic in Computer Science · Computer Science 2013-08-02 Naeem Abbasi , Osman Hasan , Sofiène Tahar

Modern electronic systems become evermore complex, yet remain modular, with integrated circuits (ICs) acting as versatile hardware components at their heart. Electronic design automation (EDA) for ICs has focused traditionally on power,…

The modern power system is evolving with increasing penetration of power electronics introducing complicated electromagnetic phenomenon. Electromagnetic transient (EMT) simulation is essential to understand power system behavior under…

Systems and Control · Electrical Eng. & Systems 2021-07-02 Yijing Liu , Xiang Zhang , Renchang Dai , Guangyi Liu

Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and transportation. In both of these areas, new electrochemical…

Many applications require that we learn the parameters of a model from data. EM is a method used to learn the parameters of probabilistic models for which the data for some of the variables in the models is either missing or hidden. There…

Machine Learning · Computer Science 2013-01-30 Luis E. Ortiz , Leslie Pack Kaelbling

The Expectation--Maximization (EM) algorithm is a simple meta-algorithm that has been used for many years as a methodology for statistical inference when there are missing measurements in the observed data or when the data is composed of…

Machine Learning · Statistics 2022-11-15 Hideitsu Hino , Shotaro Akaho , Noboru Murata

As the fast growth and large integration of distributed generation, renewable energy resource, energy storage system and load response, the modern power system operation becomes much more complicated with increasing uncertainties and…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-04-10 Guangyi Liu , Chen Yuan , Xi Chen , Jingjin Wu , Renchang Dai , Zhiwei Wang

Use of explicit integration methods for power electronic circuits with ideal switch models significantly improves simulation speed. The PLECS package [1] has effectively used this idea; however, the implementation details involved in PLECS…

Computational Engineering, Finance, and Science · Computer Science 2024-06-19 Mahesh B. Patil

Electrochemical hybrid battery models have major potential to enable advanced physics-based control, diagnostic, and prognostic features for next-generation lithium-ion battery management systems. This is due to the physical significance of…

Systems and Control · Electrical Eng. & Systems 2025-05-13 Jackson Fogelquist , Xinfan Lin

This paper has delved into the pressing need for intelligent emergency control in large-scale power systems, which are experiencing significant transformations and are operating closer to their limits with more uncertainties. Learning-based…

Systems and Control · Electrical Eng. & Systems 2023-10-10 Qiuhua Huang , Renke Huang , Tianzhixi Yin , Sohom Datta , Xueqing Sun , Jason Hou , Jie Tan , Wenhao Yu , Yuan Liu , Xinya Li , Bruce Palmer , Ang Li , Xinda Ke , Marianna Vaiman , Song Wang , Yousu Chen

The success of high energy physics programs relies heavily on accurate detector simulations and beam interaction modeling. The increasingly complex detector geometries and beam dynamics require sophisticated techniques in order to meet the…