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Based on work by Orlov, we give a precise recipe for mapping between B-type D-branes in a Landau-Ginzburg orbifold model (or Gepner model) and the corresponding large-radius Calabi-Yau manifold. The D-branes in Landau-Ginzburg theories…

High Energy Physics - Theory · Physics 2008-11-26 Paul S. Aspinwall

In Calabi--Yau compactifications of the heterotic string there exist quantities which are universal in the sense that they are present in every Calabi--Yau string vacuum. It is shown that such universal characteristics provide numerical…

High Energy Physics - Theory · Physics 2010-11-01 Rolf Schimmrigk

We study the possibility of realizing an effective sequestering between visible and hidden sectors in generic heterotic string models, generalizing previous work on orbifold constructions to smooth Calabi-Yau compactifications. In these…

High Energy Physics - Theory · Physics 2011-07-13 Christopher Andrey , Claudio A. Scrucca

In this review we describe the general geometrical framework of brane world constructions in orientifolds of type IIA string theory with D6-branes wrapping 3-cycles in a Calabi-Yau 3-fold. These branes generically intersect in points on the…

High Energy Physics - Theory · Physics 2009-11-10 Dieter Lust

We develop a general theory of flows in the space of Riemannian metrics induced by neural network gradient descent. This is motivated in part by recent advances in approximating Calabi-Yau metrics with neural networks and is enabled by…

High Energy Physics - Theory · Physics 2024-10-22 James Halverson , Fabian Ruehle

Understanding the operation of biological and artificial networks remains a difficult and important challenge. To identify general principles, researchers are increasingly interested in surveying large collections of networks that are…

Machine Learning · Statistics 2022-01-14 Alex H. Williams , Erin Kunz , Simon Kornblith , Scott W. Linderman

Calabi-Yau links are specific $S^1$-fibrations over Calabi-Yau manifolds, when the link is 7-dimensional they exhibit both Sasakian and G2 structures. In this invited contribution to the DANGER proceedings, previous work exhaustively…

High Energy Physics - Theory · Physics 2024-01-23 Edward Hirst

We consider a generalization of Einstein-Sasaki manifolds, which we characterize in terms both of spinors and differential forms, that in the real analytic case corresponds to contact manifolds whose symplectic cone is Calabi-Yau. We…

Differential Geometry · Mathematics 2011-04-01 Diego Conti , Anna Fino

We provide a construction of minimal injective resolutions of simple comodules of path coalgebras of quivers with relations. Dual to Calabi-Yau condition of algebras, we introduce the Calabi-Yau condition to coalgebras. Then we give some…

Rings and Algebras · Mathematics 2010-10-08 J. -W. He , B. Torrecillas , F. Van Oystaeyen , Y. Zhang

We study open B-model representing D-branes on 2-cycles of local Calabi--Yau geometries. To this end we work out a reduction technique linking D-branes partition functions and multi-matrix models in the case of conifold geometries so that…

High Energy Physics - Theory · Physics 2009-11-11 G. Bonelli , L. Bonora , A. Ricco

Results obtained by us are overviewed from a general set up. The universal $R$-matrix is exploited to obtain various important relations and structures involved in quantum group algebra, which are used subsequently for generating different…

High Energy Physics - Theory · Physics 2008-02-03 Anjan Kundu

We consider the problem of identifying universal low-dimensional features from high-dimensional data for inference tasks in settings involving learning. For such problems, we introduce natural notions of universality and we show a local…

Machine Learning · Computer Science 2019-11-22 Shao-Lun Huang , Anuran Makur , Gregory W. Wornell , Lizhong Zheng

Evidence for the same universal behavior of 2d Yukawa and Gross-Neveu models in a certain range of couplings, particularly for $\kappa<0$, is presented.

High Energy Physics - Lattice · Physics 2009-10-22 E. Focht

We use the differential geometrical framework of generalized (almost) Calabi-Yau structures to reconsider the concept of mirror symmetry. It is shown that not only the metric and B-field but also the algebraic structures are uniquely…

High Energy Physics - Theory · Physics 2007-05-23 Claus Jeschek

In this paper, we make progress on understanding the collapsing behavior of Calabi-Yau metrics on a degenerating family of polarized Calabi-Yau manifolds. In the case of a family of smooth Calabi-Yau hypersurfaces in projective space…

Differential Geometry · Mathematics 2024-09-13 Song Sun , Ruobing Zhang

As a sequel to \cite{Licollapsing}, we study Calabi-Yau metrics collapsing along a holomorphic fibration over a Riemann surface. Assuming at worst canonical singular fibres, we prove a uniform diameter bound for all fibres in the suitable…

Differential Geometry · Mathematics 2023-05-10 Yang Li

We propose that simple neural networks (NNs) trained on crossing symmetry can reconstruct conformal correlators restricted to a line to remarkable accuracy. The input is minimal: an external scaling dimension, a spectral gap, and the value…

High Energy Physics - Theory · Physics 2026-04-22 Kausik Ghosh , Sidhaarth Kumar , Vasilis Niarchos , Andreas Stergiou

In this paper we study shallow neural network functions which are linear combinations of compositions of activation and quadratic functions, replacing standard affine linear functions, often called neurons. We show the universality of this…

Numerical Analysis · Mathematics 2022-05-12 Leon Frischauf , Otmar Scherzer , Cong Shi

We investigate further on the correspondence between branes on a Calabi-Yau in the large volume limit and in the orbifold limit. We conjecture a new procedure which improves computationally the McKay correspondence and prove it in a non…

High Energy Physics - Theory · Physics 2010-02-03 Alessandro Tomasiello

We investigate the phenomenon of neuron universality in independently trained GPT-2 Small models, examining these universal neurons-neurons with consistently correlated activations across models-emerge and evolve throughout training. By…

Machine Learning · Computer Science 2025-11-11 Advey Nandan , Cheng-Ting Chou , Amrit Kurakula , Cole Blondin , Kevin Zhu , Vasu Sharma , Sean O'Brien