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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.

168,742 papers · 148 categories

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265177102 · Jun 202019922001200920172026
48 results for hidden symmetries

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 ↗

The paper proves limitations on hyperbolic knot complements with hidden symmetries.

problem Identifying hyperbolic knot complements with hidden symmetries.
method Obstructions to infinitely many fillings producing knot complements with hidden symmetries.
result The figure-eight knot complement is the only hyperbolic knot complement with hidden symmetries.

We briefly review the hierarchy for the hyper-Kähler equations and define a notion of symmetry for solutions of this hierarchy. A four-dimensional hyper-Kähler metric admits a hidden symmetry if it embeds into a hierarchy with a symmetry. It is shown that a hyper-Kähler metric admits a hidden symmetry if it admits a ce…

2003-01-16abs ↗pdf ↗

A "hidden symmetry" of a Riemannian manifold M is an isometry of a d-sheeted, 1<d<\infty, Riemannian cover of M which is not the lift of any isometry. In this paper we characterize the locally symmetric metric(s) on a closed, arithmetic manifold as the unique metric with infinitely many hidden symmetries.

2004-05-10abs ↗pdf ↗

This paper provides two obstructions to small knot complements in S3S^3 admitting hidden symmetries. The first obstruction is being cyclically commensurable with another knot complement. This result provides a partial answer to a conjecture of Boileau, Boyer, Cebanu, and Walsh. We also provide a second obstruction to a…

2011-10-18abs ↗pdf ↗

Some natural hidden symmetries in the Verma modules over the Virasoro algebra are constructed in terms of geometric quantization. Their differential geometric meaning is established and their expression via qRq_R-conformal symmetries in the Verma modules over the Lie algebra sl(2,C)sl(2,C) is found. The analysis and the unr…

1998-07-25abs ↗pdf ↗

We establish a pair of criteria for proving that most knot complements obtained as Dehn fillings of a given two-component hyperbolic link complement lack hidden symmetries. To do this, we use certain rational functions on varieties associated to the link. We apply our criteria to show that among certain infinite famili…

2019-10-10abs ↗pdf ↗

Permutation of any two hidden units yields invariant properties in typical deep generative neural networks. This permutation symmetry plays an important role in understanding the computation performance of a broad class of neural networks with two or more hidden units. However, a theoretical study of the permutation sy…

2019-04-30abs ↗pdf ↗

Study symmetric linear bandits with hidden symmetry, achieving improved regret bounds.

problem High-dimensional linear bandits with hidden symmetry.
method Model selection within low-dimensional subspaces to learn hidden symmetry.
result Achieved improved regret bounds of O(d02/3T2/3log(d)) O(d_0^{2/3} T^{2/3} \log(d)) and O(d0Tlog(d)) O(d_0\sqrt{T\log(d)} ).

Study spectral settings of generalized Laplacians on homogeneous spaces.

problem Understanding the spectral properties of generalized Laplacians on compact homogeneous spaces.
method Investigates the generic spectral configuration of operators on GG-invariant metrics on M=G/KM=G/K.
result The spectral setting depends on GG-isometries and hidden symmetries.

We generalize the symmetry superalgebras of isometries and geometric Killing spinors on a manifold to include all the hidden symmetries of the manifold generated by Killing spinors in all dimensions. We show that bilinears of geometric Killing spinors produce special Killing-Yano and special conformal Killing-Yano form…

2018-06-04abs ↗pdf ↗

Study generalizes Yang-Mills equations for special complex surfaces.

problem Deriving equations for self-dual Yang-Mills fields on complex surfaces.
method Generalization of flat space Yang's and Newman's equations to conformally Kahler Riemannian 4-manifolds.
result Continuous group of hidden symmetries found only for conformally half-flat geometry.

In this article we examine the conjecture of Neumann and Reid that the only hyperbolic knots in the 33-sphere which admit hidden symmetries are the figure-eight knot and the two dodecahedral knots. Knots whose complements cover hyperbolic reflection orbifolds admit hidden symmetries, and we verify the Neumann-Reid con…

2015-01-09abs ↗pdf ↗

The paper explores hidden torus symmetries in integrable systems and their stability.

problem Structural stability of singularities in integrable systems.
method Use of hidden torus actions near singular orbits and integrable perturbations.
result Persistence of toric symmetries and structural stability of Kalashnikov's parabolic orbits.

The moduli space of the Calabi-Yau three-folds, which play a role as superstring ground states, exhibits the same {\em special geometry} that is known from nonlinear sigma models in N=2N=2 supergravity theories. We discuss the symmetry structure of special real, complex and quaternionic spaces. Maps between these spaces…

1993-10-13abs ↗pdf ↗

Hidden symmetry of a G'-space X is defined by an extension of the G'-action on X to that of a group G containing G' as a subgroup. In this setting, we study the relationship between the three objects: (A) global analysis on X by using representations of G (hidden symmetry); (B) global analysis on X by using representat…

2016-08-30abs ↗pdf ↗

The relations between the infinite dimensional geometry of qRq_R-conformal symmetries at qRq_R\to\infty, Berezin quantization of the Lobachevskii plane and Karasev-Maslov asymptotic quantization are explicated. Some aspects of the ``approximate'' representation theory are discussed.

1997-02-02abs ↗pdf ↗

Study finds necessary conditions for black hole geometries to asymptotically approach Kerr-de Sitter spacetime.

problem Understanding the asymptotic behavior of black hole geometries.
method Used hidden symmetry and conformal geometry technology to find necessary conditions.
result Necessary conditions for black hole geometries to asymptotically approach Kerr-de Sitter spacetime.

Hyperbolic knots decompose into prism orbifolds.

problem Understanding hyperbolic knot complements and their geometric properties.
method Analyzing knot complements as quotients of H3\mathbb{H}^3 by discrete groups of reflections in polyhedra with triangular prism combinatorial type.
result Knot complements decompose into hidden symmetries and contain closed, embedded, totally geodesic surfaces.

In this semi-expository paper we disclose hidden symmetries of a classical nonholonomic kinematic model and try to explain geometric meaning of basic invariants of vector distributions.

2006-11-27abs ↗pdf ↗

Quantum Fourier Transform aids machine learning inference.

problem Generalizing from finite data samples to ground truth.
method Inspired by quantum algorithms, uses Quantum Fourier Transform to expose invariant subspace for data comparison.
result Proposes a concrete implementation for machine learning applications leveraging symmetries.

In this paper, we show that any non-arithmetic hyperbolic 22-bridge link complement admits no hidden symmetries. As a corollary, we conclude that a hyperbolic 22-bridge link complement cannot irregularly cover a hyperbolic 33-manifold. By combining this corollary with the work of Boileau and Weidmann, we obtain a ch…

2016-01-05abs ↗pdf ↗

Paper analyzes coexisting hidden and self-excited attractors in an economic system.

problem Existence of coexisting hidden and self-excited attractors in economic systems.
method Integer and fractional order analysis of an economic system.
result Integer-order system exhibits multiple combinations of coexisting hidden and self-excited attractors.

We propose to impose symmetry in neural network parameters to improve parameter usage and make use of dedicated convolution and matrix multiplication routines. Due to significant reduction in the number of parameters as a result of the symmetry constraints, one would expect a dramatic drop in accuracy. Surprisingly, we…

2018-12-28abs ↗pdf ↗

We present and analyse three online algorithms for learning in discrete Hidden Markov Models (HMMs) and compare them with the Baldi-Chauvin Algorithm. Using the Kullback-Leibler divergence as a measure of generalisation error we draw learning curves in simplified situations. The performance for learning drifting concep…

2007-08-17abs ↗pdf ↗

This work provides an additional step in the theoretical understanding of neural networks. We consider neural networks with one hidden layer and show that when learning symmetric functions, one can choose initial conditions so that standard SGD training efficiently produces generalization guarantees. We empirically ver…

2019-07-01abs ↗pdf ↗

Akbulut has recently shown that an infinite family of Cappell-Shaneson homotopy 4-spheres is diffeomorphic to the standard 4-sphere. In the present paper, a strictly larger family is shown to be standard by a simpler method. This new approach uses no Kirby calculus except through the relatively simple 1979 paper of Akb…

2009-08-13abs ↗pdf ↗

Study shows arithmetic properties of specific hyperbolic Dehn fillings.

problem Arithmeticity of one-cusped Dehn fillings of specific link complements.
method Investigation of cusp fields, trace fields, and invariant trace fields.
result No one-cusped hyperbolic Dehn filling of the Berge manifold is arithmetic.

We consider a binary sequence generated by thresholding a hidden continuous sequence. The hidden variables are assumed to have a compound symmetry covariance structure with a single parameter characterizing the common correlation. We study the parameter estimation problem under such one-parameter models. We demonstrate…

2017-12-27abs ↗pdf ↗

Study shows directional convergence for neural networks under spherical symmetry.

problem Learning linear predictors with neural networks under spherically symmetric data.
method Analysis of gradient flow and gradient descent for two-layer and deep linear networks.
result Directional convergence guarantees with exact convergence rate for specific network architectures.