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arXiv research

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.

168,695 papers · 148 categories

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61123184245 · May 202619922001200920172026
48 results for local phenomena

We connect topological changes that can occur in 33-space via surgery, with black hole formation, the formation of wormholes and new generalizations of these phenomena, including relationships between quantum entanglement and wormhole formation. By considering the initial manifold as the 33-dimensional spatial sectio…

2018-12-03abs ↗pdf ↗

In this paper we observe that 2-dimensional 0-surgery occurs in natural processes, such as tornado formation and other phenomena reminiscent of hole drilling. Inspired by such phenomena, we introduce new theoretical concepts which enhance the formal definition of 2-dimensional 0-surgery with the observed dynamics. To d…

2016-04-14abs ↗pdf ↗

New algorithm learns nonlinear phenomena from noisy local measurements without data exchange.

problem Learning nonlinear phenomena from noisy local measurements in a decentralized network.
method Non-parametric learning algorithm that spreads information only between neighboring nodes.
result Non-asymptotic estimation error bounds for the proposed method.

Paper studies rigidity phenomena for elliptic systems on Riemannian manifolds.

problem Local radial rigidity of elliptic systems on Riemannian manifolds.
method Reduction to singular ordinary differential equations of Euler type.
result Local uniqueness and existence results for solutions with prescribed initial jets.

We demonstrate the breakdown of several fundamentals of Lorentzian causality theory in low regularity. Most notably, chronological futures (defined naturally using locally Lipschitz curves) may be non-open, and may differ from the corresponding sets defined via piecewise C1C^1-curves. By refining the notion of a causal…

2019-01-23abs ↗pdf ↗

The paper extends curve deformation methods in Minkowski plane.

problem Studying deformations of curves in the Minkowski plane considering their geometry and singularities.
method Extends methods from [17, 18] to analyze 2-parameter families of curves in Minkowski plane.
result Obtains geometry of deformed curves, including inflections, vertices, and lightlike points.

Study invariants of elliptic curves in LCS manifolds, leading to new phenomena in Riemann-Finsler geometry.

problem Defining and studying invariants of elliptic curves in locally conformally symplectic manifolds.
method Using JJ-holomorphic curves and Gromov-Witten theory to define and study invariants.
result Found new phenomena in Riemann-Finsler geometry and an analogue of the Weinstein conjecture.

We critically review recent claims that financial crashes can be predicted using the idea of log-periodic oscillations or by other methods inspired by the physics of critical phenomena. In particular, the October 1997 `correction' does not appear to be the accumulation point of a geometric series of local minima.

1998-04-09abs ↗pdf ↗

New examples of knotting phenomena in 4-manifolds with specific fundamental groups.

problem Finding 2-spheres in simply connected 4-manifolds with prescribed fundamental groups.
method Construction of infinite sets of pairwise smoothly inequivalent 2-spheres that are topologically isotopic.
result First known examples of knotting phenomena in 4-manifolds with specific properties.

In this paper we show how the existence of a certain stable cylinder determines (locally) the ambient manifold where it is immersed. This cylinder has to verify a {\it bifurcation phenomena}, we make this explicit in the introduction. In particular, the existence of such a stable cylinder implies that the ambient manif…

2011-04-16abs ↗pdf ↗

Deep neural networks have achieved impressive performance and become the de-facto standard in many tasks. However, troubling phenomena such as adversarial and fooling examples suggest that the generalization they make is flawed. I argue that among the roots of the phenomena are two geometric properties of common deep l…

2019-11-20abs ↗pdf ↗

On the one hand, we prove that the Clifford torus in C2\mathbb{C}^2 is unstable for Lagrangian mean curvature flow under arbitrarily small Hamiltonian perturbations, even though it is Hamiltonian FF-stable and locally area minimising under Hamiltonian variations. On the other hand, we show that the Clifford torus is r…

2018-02-05abs ↗pdf ↗

Differentiable NAS frameworks grow networks wider and deeper, revealing biases in wiring evolution.

problem Understanding the evolution of neural architecture wiring in differentiable NAS methods.
method Unified view on searching algorithms, local cost minimization, empirical and theoretical analyses.
result Implicit inductive biases cause observed searching patterns in differentiable NAS methods.

Framework calculates positional influence in causal residual Transformers.

problem Understanding positional influence in causal residual Transformers.
method Adjoint-sensitivity framework for positional influence in causal residual Transformers.
result Exact evolution of adjoint-energy influence density and decomposition into residual transmission, nonlocal Volterra, and local channels.

Much recent work has concerned sparse approximations to speed up the Gaussian process regression from the unfavorable O(n3) scaling in computational time to O(nm2). Thus far, work has concentrated on models with one covariance function. However, in many practical situations additive models with multiple covariance func…

2012-06-13abs ↗pdf ↗

The paper shows how solutions of perturbed Dirac operators concentrate near singular sets.

problem Understanding concentration of solutions for perturbed Dirac operators.
method Analyzing the algebraic criterion on $(c, \A)$ and spectral properties of deformed Laplacians.
result Proves an index localization theorem based on spectral separation properties.

A constrained informationally efficient market is defined to be one whose price process arises as the outcome of some equilibrium where agents face restrictions on trade. This paper investigates the case of short sale constraints, a setting which despite its simplicity, generates new insights. In particular, it is show…

2014-01-08abs ↗pdf ↗

We examine the moduli space of oriented locally homogeneous manifolds of Type A which have non-degenerate symmetric Ricci tensor both in the setting of manifolds with torsion and also in the torsion free setting where the dimension is at least 3. These exhibit phenomena that is very different than in the case of surfac…

2016-07-06abs ↗pdf ↗

Sharp changes in time series representing market dynamics are studied by means of the self--similar analysis suggested earlier by the authors. These sharp changes are market booms and crashes. Such crises phenomena in markets are analogous to critical phenomena in physics. A simple classification of the market crisis p…

1998-10-08abs ↗pdf ↗

New surfaces with special geodesic and horocycle behaviors discovered.

problem Understanding geodesic and horocycle dynamics on hyperbolic surfaces.
method Constructing geometrically infinite hyperbolic surfaces with tailored recurrence properties.
result First examples of non-trivial minimal horocyclic orbit closures and infinite locally-finite conservative horocyclic invariant measures.

Study on Lane-Emden equation on curved spaces, revealing new existence and non-existence phenomena.

problem Existence and non-existence of positive solutions for the Lane-Emden equation on Riemannian models.
method Analysis of the subcritical Lane-Emden equation on various Riemannian manifolds with polynomial volume growth.
result Subcritical regime divides into three ranges with distinct existence and non-existence phenomena.

The paper explores higher property T in lattices and its connections to geometric phenomena.

problem Understanding higher property T in lattices and related geometric phenomena.
method Operator-algebraic characterizations of higher property T and connections to lattice geometry.
result Unified framework for understanding higher property T and related geometric phenomena.

Paper connects Stokes phenomena to quantum groups and Poisson-Lie groups.

problem Analyse Stokes phenomena in Poisson-Lie groups and quantum groups.
method Use Ug-valued Stokes phenomena to construct quantum group U_hg and relate it to Poisson-Lie group G*.
result Show that Ug-valued Stokes phenomena can be obtained as a semiclassical limit of the KZ associator.

In this paper, we study Clifford-Wolf translations of homogeneous Randers metrics on spheres. It turns out that we can present a complete description of all the Clifford-Wolf translations of all the homogeneous Randers metrics on spheres. The most important point of this paper is that a new phenomena surfaces. Namely, …

2012-04-23abs ↗pdf ↗

Paper investigates rigidity phenomena for weighted Ricci curvature bounds with Laplacian comparison theorem.

problem Investigating rigidity phenomena for weighted Ricci curvature bounds.
method Derived comparison geometric estimates and generalized for non-symmetric Laplacian.
result Obtained rigidity results for Laplacian comparison theorem, diameter comparisons, and volume comparisons.

Let M be a smooth locally embeddable CR manifold, having some CR dimension m and some CR codimension d. We find an improved local geometric condition on M which guarantees, at a point p on M, that germs of CR distributions are smooth functions, and have extensions to germs of holomorphic functions on a full ambient nei…

2009-03-30abs ↗pdf ↗

The goal of this paper is to measure the non-convexity of compact and smooth connected components of real algebraic plane curves. We study these curves first in a general setting and then in an asymptotic one. In particular, we consider sufficiently small levels of a real bivariate polynomial in a small enough neighbou…

2019-07-19abs ↗pdf ↗

GNNs may be limited by graph topology, affecting their learning outcomes.

problem Understanding how graph topology influences GNN behavior and performance.
method Investigating the interaction between local topological features and GNN message-passing schemes.
result Locally similar neighborhoods can lead to consistent node representations, affecting GNN performance.

Analyzes magnetic Laplacian on hyperbolic surfaces, highlighting key quantum phenomena.

problem Understanding quantum phenomena on hyperbolic surfaces with magnetic fields.
method Semiclassical analysis and mathematical modeling of the magnetic Laplacian.
result Discovers new insights into quantum behavior on hyperbolic surfaces with magnetic fields.

Knowing and modelling the migration phenomena and especially the social and economic consequences have a theoretical and practical importance, being related to their consequences for development, economic progress (or as appropriate, regression), environmental influences etc. One of the causes of migration, especially …

2012-02-05abs ↗pdf ↗

We study the first uniformly finite homology group of Block and Weinberger for uniformly locally finite graphs, with coefficients in Z\mathbb{Z} and Z2\mathbb{Z}_2. When the graph is a tree, or coefficients are in Z2\mathbb{Z}_2, a characterisation of the group is obtained. In the general case, we describe three pheno…

2020-01-14abs ↗pdf ↗

We study in this paper the fractional Yamabe problem first considered by Gonzalez-Qing on the conformal infinity (Mn,[h])(M^n , [h]) of a Poincaré-Einstein manifold (Xn+1,g+)(X^{n+1} , g^+ ) with either n=2n = 2 or n3n \geq 3 and (Mn,[h])(M^n , [h]) is locally flat - namely (M,h)(M, h) is locally conformally flat. However, as for the classic…

2017-01-20abs ↗pdf ↗

The paper explains emergent phenomena in deep learning using entropic forces.

problem Understanding the cause of emergent phenomena in deep learning and large language models.
method Proposes a rigorous entropic-force theory for neural networks trained with SGD and variants.
result Shows that representation learning is governed by emergent entropic forces that break continuous symmetries and preserve discrete ones.

Random matrix theory predicts neural representations generalize well.

problem Understanding why neural representations generalize well in practice.
method Applied random matrix theory to kernel regression and neural networks.
result GCV estimator accurately predicts generalization risk in overparameterized settings.