Results 161 to 170 of about 19,239 (301)

Computation of H-infinity norm of linear discrete-time periodic systems

, 2006
We propose an efficient an numerically reliable procedure for the computation of H-infinity norm of discrete-time linear periodic systems. The new procedure is general being applicable to both standard as well as descriptor periodic systems with time ...
Varga, Andreas
core  

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

From outside in: external structures and internal properties in linear systems

, 2014
Slides of the semi-plenary ...
Rapisarda, Paolo
core  

Mechanisms of Alkali Ionic Transport in Amorphous Oxyhalides Solid State Conductors

Advanced Energy Materials, EarlyView.
Large‐scale machine learning‐based molecular dynamics simulations are used to investigate isovalent amorphous oxyhalides, revealing a remarkable chemically independent ionic conductivity. A rigorous analysis of alkali residence times across different metal–anion environments identifies divalent anions as key diffusion bottlenecks.
Luca Binci, KyuJung Jun, Bowen Deng, Gerbrand Ceder   +3 more
wiley   +1 more source

Long-Time Dynamics for the Kelvin-Helmholtz Equations Close to Circular Vortex Sheets. [PDF]

Arch Ration Mech Anal
Murgante F, Roulley E, Scrobogna S.
europepmc   +1 more source

Limitations of Foundation Models in Energy Materials Simulations: A Case Study in Polyanion Sodium Cathode Materials

Advanced Intelligent Discovery, EarlyView.
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen, Chiku Parida, Jonas Busk, Jin Hyun Chang, Arghya Bhowmik, Juan Maria Garcia Lastra   +5 more
wiley   +1 more source

Hamiltonian simulation for nonlinear partial differential equation by Schrödingerization. [PDF]

Sci Rep
Sasaki S, Endo K, Muramatsu M.
europepmc   +1 more source

Linear Hamiltonian Systems [PDF]

, 2003
openaire   +1 more source

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

Advanced Intelligent Discovery, EarlyView.
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley   +1 more source

Effective Mode Approximation for Probabilistic Verification of Collective Hamiltonians in Large Continuous-Variable Quantum Systems. [PDF]

Entropy (Basel)
Rosas-Bustos JR, Van Griensven Thé J, Fraser RA, Said N, Ratto Valderrama S, Pecen M, Truskovsky A, Thanos A.   +7 more
europepmc   +1 more source