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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,291 papers · 148 categories

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12233546 · May 202619922001200920182026
48 results for c-projective symmetries

The paper studies symmetries in quaternionic geometry and submanifolds.

problem Understanding symmetries in quaternionic geometry and their implications for submanifolds.
method Generalized Feix--Kaledin construction, infinitesimal symmetries analysis, quaternionic and c-projective symmetries study.
result Conditions for extending c-projective symmetries to quaternionic symmetries and studying specific hyperkähler structures.

C-projective structures are analogues of projective structures in the complex setting. The maximal dimension of the Lie algebra of c-projective symmetries of a complex connection on an almost complex manifold of C-dimension n>1n>1 is classically known to be 2n2+4n2n^2+4n. We prove that the submaximal dimension is equal to $…

2015-04-27abs ↗pdf ↗

Characterizes C-projective vector fields on Randers spaces.

problem Characterizing C-projective vector fields on Randers spaces.
method Using a non-Riemannian quantity ${fΞ}$, it is shown that ${fΞ}$ is invariant for C-projective vector fields and the dimension of the algebra of C-projective vector fields is at most n(n+2)n(n+2).
result An nn-dimensional Randers space has a C-projective algebra of maximum dimension n(n+2)n(n+2) if and only if it is locally Minkowskian or (up to re-scaling) locally isometric to the generalized Funk metric.

A vector field on a Kähler manifold is called c-projective if its flow preserves the J-planar curves. We give a complete local classification of Kähler real 4-dimensional manifolds that admit an essential c-projective vector field. An important technical step is a local description of 4-dimensional c-projectively equiv…

2013-11-03abs ↗pdf ↗

We develop in detail the theory of c-projective geometry, a natural analogue of projective differential geometry adapted to complex manifolds. We realise it as a type of parabolic geometry and describe the associated Cartan or tractor connection. A Kaehler manifold gives rise to a c-projective structure and this is one…

2015-12-14abs ↗pdf ↗

Characterizes projective special complex manifolds using c-projective structures.

problem Characterizing projective special complex manifolds.
method Defining S1S^1-bundles and constructing conical special complex manifolds.
result Intrinsic characterization of projective special complex manifolds.

Geodesic flows on Kähler manifolds are quantum integrable when metrics are c-projectively equivalent.

problem Quantum integrability of geodesic flows on Kähler manifolds under c-projective equivalence.
method Construction of Poisson-commuting integrals of motion and their quantum counterparts.
result The geodesic flow's integrals of motion commute as quantum operators, leading to separation of variables in Schrödinger's equation.

Study of quasi-Kähler metrics on complex manifolds linked to c-projective metrizability.

problem Characterizing quasi-Kähler metrics on almost complex manifolds.
method Analyzing the c-projectively invariant metrizability equation and its solutions.
result New geometries induced by non-degenerate solutions with non-vanishing scalar curvature.

Two Kähler metrics on a complex manifold are called c-projectively equivalent if their JJ-planar curves coincide. These curves are defined by the property that the acceleration is complex proportional to the velocity. We give an explicit local description of all pairs of c-projectively equivalent Kähler metrics of arb…

2015-10-01abs ↗pdf ↗

Study projective symmetries in Finsler spaces, showing reductions and constant flag curvature.

problem Exploring projective symmetries in Finsler spaces and their properties.
method Analyzing algebraic sub-algebras and curvature invariants of projective vector fields.
result Closed Finsler spaces with negative Ricci curvature reduce to Killing vector fields.

The paper studies projectively equivalent para-Kaehler metrics in 4D.

problem Characterizing para-Kaehler metrics with specific properties.
method Developed c-projective geometry for para-Kaehler metrics, focusing on 4D case.
result Local description and characterization of 4D pc-projectively equivalent metrics, including Einstein type.

We study the local geometry of irreducible parabolic geometries admitting strongly essential flows; these are flows by local automorphisms with higher-order fixed points. We prove several new rigidity results, and recover some old ones for projective and conformal structures, which show that in many cases the existence…

2014-10-17abs ↗pdf ↗

New metrics defined in Finsler geometry with specific properties.

problem Understanding the properties of Finsler metrics and their subclasses.
method Introducing the generalized Berwald projective Weyl metric and proving properties of the class of generalized Douglas metrics.
result All GDWGDW metrics with vanishing Landsberg curvature are of R-quadratic type.

Starting from a complex manifold S with a real-analytic c-projective structure whose curvature has type (1,1), and a complex line bundle L with a connection whose curvature has type (1,1), we construct the twistor space Z of a quaternionic manifold M with a quaternionic circle action which contains S as a totally compl…

2015-12-23abs ↗pdf ↗

New method finds open subsets with trivial holonomy for certain geometries.

problem Finding open subsets with trivial holonomy for Cartan geometries.
method Analyzing the behavior of isotropies in model geometries to generalize properties of isolated higher-order fixed points.
result Existence of open subsets with trivial holonomy for Cartan geometries with certain isotropies.

Sym-NET detects human symmetries in photos, outperforming existing models.

problem Capturing human symmetry perception in real-world images.
method Deep-learning neural network (Sym-NET) trained on MS-COCO dataset with human labels.
result Sym-NET significantly outperforms existing algorithms on unseen MS-COCO photos.

The paper analyzes symmetries of Vaidya-Bonner geodesics.

problem Investigating invariance properties of Vaidya-Bonner geodesics.
method Classification of Lie point symmetries and Noether symmetries, determination of optimal system of subalgebras.
result Determination of optimal system of subalgebras for Vaidya-Bonner geodesics.

Extends symmetry superalgebras to include all hidden symmetries of manifolds.

problem Tackles hidden symmetries of manifolds generated by Killing spinors.
method Defines generalized symmetry superalgebras, constructs Lie algebra structure, and defines symmetry operators.
result Constructs special Killing-Yano and conformal Killing-Yano forms from bilinears of Killing spinors.

Method improves deep learning models for datasets with mixed approximate symmetries.

problem Improving deep learning models for datasets with mixed approximate symmetries.
method Regularizer-based approach to build models for datasets with mixed approximate symmetries.
result Our method achieves better accuracy than prior approaches while discovering the approximate symmetry levels correctly.

Symmetry in loss functions constrains model parameters, leading to specific learning outcomes.

problem Understanding and leveraging symmetries in neural networks to improve learning outcomes.
method Analyzing the impact of loss function symmetries on model parameters and learning behavior.
result Mirror-reflection symmetries in loss functions lead to constraints on model parameters, influencing learning outcomes.

Approximate symmetries of geodesic equations on 2-spheres are studied. These are the symmetries of the perturbed geodesic equations which represent approximate path of a particle rather than exact path. After giving the exact symmetries of the geodesic equations, two different approaches to study the approximate symmet…

2010-05-09abs ↗pdf ↗

Devign uses graph neural networks to identify vulnerabilities efficiently.

problem Challenging and tedious process of identifying vulnerabilities in software systems.
method Devign employs a graph neural network to classify graph-level vulnerabilities using comprehensive code semantic representations.
result Devign significantly outperforms state-of-the-art models in vulnerability identification.

New framework discovers non-affine continuous symmetries in neural networks.

problem Lack of efficient methods for detecting non-affine continuous symmetries in neural networks.
method Computational framework for discovering infinitesimal generators of multi-parameter group actions.
result Framework can discover non-affine continuous symmetries in neural networks.

Symmetry in neural networks reduces parameter count without sacrificing accuracy.

problem Improving parameter usage and efficiency in deep neural networks.
method Imposing symmetry constraints on neural network parameters, especially in convolutional and recurrent networks.
result Symmetry can have little or no negative effect on network accuracy, even in deep overparameterized networks.

The paper explores symmetries and conservation laws in Hamiltonian systems.

problem Understanding symmetries and conservation laws in Hamiltonian systems.
method Using dynamical covariant derivative and Jacobi endomorphism, the paper finds invariant equations of symmetries and proves the canonical nonlinear connection can be determined by these symmetries.
result The canonical nonlinear connection can be determined by infinitesimal symmetries and Newtonoid vector fields.

This paper introduces a new approach to finding knots and links with hidden symmetries using "hidden extensions", a class of hidden symmetries defined here. We exhibit a family of tangle complements in the ball whose boundaries have symmetries with hidden extensions, then we further extend these to hidden symmetries of…

2015-01-04abs ↗pdf ↗