Results 51 to 60 of about 56,136 (229)
Advanced Intelligent Discovery, EarlyView.We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob +2 more
wiley +1 more source
Relaxation of wave maps exterior to a ball to harmonic maps for all data [PDF]
, 2013 In this paper we study 1-equivariant wave maps of finite energy from 1+3-dimensional Minkowski space exterior to the unit ball at the origin into the 3-sphere.
Kenig, Carlos +2 more
core
A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons
Advanced Intelligent Discovery, EarlyView.We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam +5 more
wiley +1 more source
Character varieties and harmonic maps to R-trees [PDF]
, 1998 We show that the Korevaar-Schoen limit of the sequence of equivariant harmonic maps corresponding to a sequence of irreducible $SL_2({\mathbb C})$ representations of the fundamental group of a compact Riemannian manifold is an equivariant harmonic map to
Daskalopoulos, Georgios +2 more
core +2 more sources
Equivariant Surgery Theory: Construction of Equivariant Normal Maps
Publications of the Research Institute for Mathematical Sciences, 1995 Following an idea and a description of T. Petrie, many authors have constructed exotic smooth group actions using equivariant surgery. This involves the construction of suitable \(G\)-normal maps via \(G\)- transversality, and an arrangement that makes \(G\)-surgery obstructions vanish.
openaire +3 more sources
Advanced Intelligent Discovery, EarlyView.This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu +5 more
wiley +1 more source
Second-Order Conformally Equivariant Quantization in Dimension 1|2
Symmetry, Integrability and Geometry: Methods and Applications, 2009 This paper is the next step of an ambitious program to develop conformally equivariant quantization on supermanifolds. This problem was considered so far in (super)dimensions 1 and 1|1.
Najla Mellouli
doaj +1 more source
HILBERT STRATIFOLDS AND A QUILLEN TYPE GEOMETRIC DESCRIPTION OF COHOMOLOGY FOR HILBERT MANIFOLDS
Forum of Mathematics, Sigma, 2018 In this paper we use tools from differential topology to give a geometric description of cohomology for Hilbert manifolds. Our model is Quillen’s geometric description of cobordism groups for finite-dimensional smooth manifolds [Quillen, ‘Elementary ...
MATTHIAS KRECK, HAGGAI TENE
doaj +1 more source
T-equivariant disc potential and SYZ mirror construction [PDF]
, 2019 We develop a G-equivariant Lagrangian Floer theory by counting pearly trees in the Borel construction LG. We apply the construction to smooth moment-map fibers of toric semi-Fano manifolds and obtain the T-equivariant Landau-Ginzburg mirrors.
Kim, Yoosik, Lau, Siu, Zheng, Xiao
core +1 more source
General position of equivariant maps [PDF]
Transactions of the American Mathematical Society, 1977 A natural generic notion of general position for smooth maps which are equivariant with respect to the action of a compact Lie group is introduced. If G is a compact Lie group, and M, N are smooth G-manifolds, then the set of smooth equivariant maps F : M → N F:M \to N which are in general position ...
openaire +2 more sources