Results 131 to 140 of about 24,687,007 (292)

Quadrature Based Neural Network Learning of Stochastic Hamiltonian Systems

open access: yesMathematics
Hamiltonian Neural Networks (HNNs) provide structure-preserving learning of Hamiltonian systems. In this paper, we extend HNNs to structure-preserving inversion of stochastic Hamiltonian systems (SHSs) from observational data.
Xupeng Cheng, Lijin Wang, Yanzhao Cao
doaj   +1 more source

Evolution of Physical Intelligence Across Scales

open access: yesAdvanced Intelligent Discovery, EarlyView.
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu   +7 more
wiley   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

open access: yesAdvanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy   +8 more
wiley   +1 more source

Factorization Machine with Iterative Quantum Reverse Annealing: A Python Package for Batch Black‐Box Optimization With Reverse Quantum Annealing

open access: yesAdvanced Intelligent Discovery, EarlyView.
Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley   +1 more source

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

open access: yesAdvanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy   +2 more
wiley   +1 more source

Universal Entanglement and an Information‐Complete Quantum Theory

open access: yesAdvanced Physics Research, EarlyView.
This Perspective summarize an informationcomplete quantum theory which describes a fully quantum world without any classical systems and concepts. Here spacetime/gravity, having to be a physical quantum system, universally entangles matter (matter fermions and their gauge fields) as an indivisible trinity, and encodes information‐complete physical ...
Zeng‐Bing Chen
wiley   +1 more source

PID Passivity-Based Control of Port-Hamiltonian Systems

open access: yesIEEE Transactions on Automatic Control, 2018
Meng Zhang   +4 more
semanticscholar   +1 more source

Amplified Quantum Correlation via Dynamical Modulation in Qubit‐Qutrit System under Markovian and Non‐Markovian Noise

open access: yesAdvanced Physics Research, EarlyView.
This study proposes an innovative approach to strengthen and amplify entanglement in a hybrid qubit–qutrit system driven by a dynamic field. By analyzing the system's dynamics under both Markovian and non‐Markovian environments, we show that specific field values optimize entanglement.
Polislin Fabrice Wonang   +5 more
wiley   +1 more source

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