Results 41 to 50 of about 55,778 (240)

A tight colored Tverberg theorem for maps to manifolds (extended abstract) [PDF]

open access: yesDiscrete Mathematics & Theoretical Computer Science, 2011
Any continuous map of an $N$-dimensional simplex $Δ _N$ with colored vertices to a $d$-dimensional manifold $M$ must map $r$ points from disjoint rainbow faces of $Δ _N$ to the same point in $M$, assuming that $N≥(r-1)(d+1)$, no $r$ vertices of $Δ _N ...
Pavle V. M. Blagojević   +2 more
doaj   +1 more source

On equivariant deformation of maps

open access: yesPublicacions Matemàtiques, 2021
We work in the smooth category: manifolds and maps are meant to be smooth. Let G be a finite group acting on a connected closed manifold X and f an equivariant self-map on X with flA fixpointfree, where A is a closed invariant submanifold of X with codim A >- 3. The purpose of this paper is to give a proof using obstruction theory of the following fact:
openaire   +8 more sources

Geometric versus homotopy theoretic equivariant bordism

open access: yes, 2004
By results of Loeffler and Comezana, the Pontrjagin-Thom map from geometric G-equivariant bordism to homotopy theoretic equivariant bordism is injective for compact abelian G. If G = S^1 x ...
Hanke, Bernhard
core   +3 more sources

Conjugates of strongly equivariant maps [PDF]

open access: yesPacific Journal of Mathematics, 1994
Let \(G_1\) and \(G_2\) be hermitian algebraic groups with associated symmetric domains \(X_1\) and \(X_2\), respectively. A holomorphic embedding \(\tau : X_1 \to X_2\) is called weakly equivariant if there exists a morphism of algebraic groups \(\rho : G_1 \to G_2\) compatible with \(\tau\).
openaire   +3 more sources

Gromov’s Oka Principle for Equivariant Maps [PDF]

open access: yesThe Journal of Geometric Analysis, 2020
We take the first step in the development of an equivariant version of modern, Gromov-style Oka theory. We define equivariant versions of the standard Oka property, ellipticity, and homotopy Runge property of complex manifolds, show that they satisfy all the expected basic properties, and present examples.
Frank Kutzschebauch   +2 more
openaire   +4 more sources

Machine Learning for Accelerating Energy Materials Discovery: Bridging Quantum Accuracy with Computational Efficiency

open access: yesAdvanced Energy Materials, EarlyView.
This perspective highlights how machine learning accelerates sustainable energy materials discovery by integrating quantum‐accurate interatomic potentials with property prediction frameworks. The evolution from statistical methods to physics‐informed neural networks is examined, showcasing applications across batteries, catalysts, and photovoltaics ...
Kwang S. Kim
wiley   +1 more source

Coassembly is a homotopy limit map

open access: yes, 2020
We prove a claim by Williams that the coassembly map is a homotopy limit map. As an application, we show that the homotopy limit map for the coarse version of equivariant $A$-theory agrees with the coassembly map for bivariant $A$-theory that appears in ...
Malkiewich, Cary, Merling, Mona
core   +1 more source

Tandem Takeoff: Powering Tomorrow with Industrial‐Grade Perovskite/Silicon Solar Cells

open access: yesAdvanced Energy Materials, EarlyView.
Perovskite/silicon tandem solar cells have recently achieved certified power conversion efficiencies of 34.85%, far exceeding the Shockley‐Queisser limit for single‐junction silicon and standalone perovskite cells. This review highlights the latest advances in the design, integration, and optimization of perovskite top cells for monolithic tandem ...
Maria Vasilopoulou   +19 more
wiley   +1 more source

Critical $O(d)$-equivariant biharmonic maps

open access: yes, 2015
We study $O(d)$-equivariant biharmonic maps in the critical dimension. A major consequence of our study concerns the corresponding heat flow. More precisely, we prove that blowup occurs in the biharmonic map heat flow from $B^4(0, 1)$ into $S^4$.
Cooper, Matthew K.
core   +1 more source

Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials

open access: yesAdvanced 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

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