Results 51 to 60 of about 55,778 (240)

T-equivariant disc potential and SYZ mirror construction [PDF]

open access: yes, 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

Projectively Equivariant Quantization Map

open access: yesLetters in Mathematical Physics, 2000
Let M be a manifold endowed with a symmetric affine connection $ .$ The aim of this paper is to describe a quantization map between the space of second-order polynomials on the cotangent bundle T^{*} M and the space of second-order linear differential operators, both viewed as modules over the group of diffeomorphisms and the Lie algebra of vector ...
openaire   +2 more sources

A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons

open access: yesAdvanced 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

Relaxation of wave maps exterior to a ball to harmonic maps for all data [PDF]

open access: yes, 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  

Mining Chemical Space with Generative Models for Battery Materials

open access: yesBatteries &Supercaps, EarlyView.
Revolutionizing Li‐ion battery material discovery with MatterGen, a foundational generative AI model for crystal structure inverse design. Explored stable, unique, and novel compositions and their analysis with respect to the state‐of‐the‐art databases, followed by DFT validation, provides a new direction for accelerating materials discovery ...
Chiku Parida   +3 more
wiley   +1 more source

Second-Order Conformally Equivariant Quantization in Dimension 1|2

open access: yesSymmetry, 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

open access: yesForum 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

The geometric Hopf invariant and double points

open access: yes, 2010
The geometric Hopf invariant of a stable map F is a stable Z_2-equivariant map h(F) such that the stable Z_2-equivariant homotopy class of h(F) is the primary obstruction to F being homotopic to an unstable map.
Crabb, Michael, Ranicki, Andrew
core   +3 more sources

Equivariant Phantom Maps

open access: green, 2001
A successful generalization of phantom map theory to the equivariant case for all compact Lie groups is obtained in this paper. One of the key observations is the discovery of the fact that homotopy fiber of equivariant completion splits as product of equivariant Eilenberg-Maclane spaces which seems impossible at first sight by the example of ...
Jianzhong Pan
openalex   +4 more sources

Generative Deep Learning for Advanced Battery Materials

open access: yesBatteries &Supercaps, EarlyView.
This review explores the role of generative deep learning (DL) in battery materials analysis and highlights the fundamental principles of generative DL and its applications in designing battery materials. The importance of using multimodal data is underscored to effectively address the challenges faced during the development of battery materials across
Deepalaxmi Rajagopal   +3 more
wiley   +1 more source

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