Results 171 to 180 of about 7,283,719 (303)

Evolution of Physical Intelligence Across Scales

Advanced 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, Tianyun Huang, Aming Li, Pengyu Lv, Tingting Qin, Wenhui Chen, Hui Wei, Huiling Duan   +7 more
wiley   +1 more source

Symplectic Structure-Aware Hamiltonian (Graph) Embeddings [PDF]

In traditional Graph Neural Networks (GNNs), the assumption of a fixed embedding manifold often limits their adaptability to diverse graph geometries.
Huang, Xiaowei, Yi, Xinping, Zhang, Tianle, Liu, Jiaxu   +3 more
core  

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

Advanced 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, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Lie Groups of Partial Differential Equations and Their Application to the Multidimensional Screening Problems [PDF]

In this paper I describe group theoretic methods that can be used for analyzing the boundary problems, which arise when the Hamiltonian method is applied to solve the relaxed problem for the multidimensional screening problem.
Suren Basov
core  

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

Advanced 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

Tunable Raman Scattering of Fe(II) Coordination Networks With Magnetic Fields

Angewandte Chemie, EarlyView.
Four heavy Hg(II) coordination networks with paramagnetic Fe(II) sites reveal strong and halogen‐tunable low‐frequency (LF) sub‐terahertz phonons and field‐dependent magnetic transitions. LF phonon spectroscopy and Raman magnetospectroscopy are powerful probes of structure, low‐energy vibration, zero‐field splitting, and spin–phonon coupling supported ...
Guanping Li, Olaf Stefanczyk, Joseph M. Flitcroft, Jonathan M. Skelton, William T. Morrillo, Meagan Oakley, Lulu Xiong, Koji Nakabayashi, Dmitry Smirnov, Komalavalli Thirunavukkuarasu, Mykhaylo Ozerov, Shin‐ichi Ohkoshi, Nicholas F. Chilton   +12 more
wiley   +2 more sources

A Breadth‐First Pruned‐Enriched Rosenbluth Method for Force–Extension Simulations of Confined Semiflexible Chains

Advanced Intelligent Discovery, EarlyView.
The behaviors of semiflexible polymers such as DNA and protein are often reshaped by coupled interactions. Monte Carlo simulations assist in studying these systems. This work recasts the traditional chain‐growth strategy into a new framework: a fixed number of chains grow synchronously, while less relevant chains to the target system are removed and ...
Yihan Zhao, Jizeng Wang
wiley   +1 more source

Template‐Encoded Assembly and Adaptive Function in Selenium‐Based Molybdenum Chalcoxide Rings

Angewandte Chemie, EarlyView.
External templates write structural information into Se‐containing molybdenum rings, while selenium's softness confers adaptive host–guest behaviour and catalytic responsiveness, an integrated framework for programmable inorganic function. ABSTRACT Controlling both structure and function in inorganic self‐assembly remains a major challenge.
Giulia Pellegrino, Alexander Elliott, Yu‐Fei Song, Nuno A. G. Bandeira, Haralampos N. Miras   +4 more
wiley   +2 more sources

Efficient Hamiltonian, structure and trace distance learning of Gaussian states. [PDF]

Nat Commun
Fanizza M, Rouzé C, Stilck França D.
europepmc   +1 more source

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

Advanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison, Kevin Nadaud, Josquin Harrison, Guillaume F. Nataf, Laura Bégon‐Lours   +4 more
wiley   +1 more source