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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.

168,695 papers · 148 categories

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16324864 · Oct 202419922001200920172026
48 results for Arnold conjecture

In this article, we give proofs on the Arnold Lagrangian intersection conjecture on the cotangent bundles, Arnold-Givental Lagrangian intersection conjecture and the Arnold fixed point conjecture.

2008-08-05abs ↗pdf ↗

Proves Arnold conjecture for singular symplectic manifolds using novel techniques.

problem Hamiltonian dynamics on singular symplectic manifolds.
method Introducing smooth symplectic forms to singular symplectic structures under mild conditions, using Floer homology.
result Proves a lower bound on the number of 1-periodic Hamiltonian orbits for b2mb^{2m}-symplectic manifolds.

The paper confirms Arnold's conjecture about hyperbolic polynomials.

problem The number of connected components of hyperbolic polynomials increases linearly with degree.
method Constructive proof using homotopy invariance of the index of a curve and properties of homogeneous polynomials.
result Exact number of connected components of Hyp(D)Hyp(D) is determined and representatives for each component are provided.

Proves Weinstein's and Arnold's conjectures using contact instantons.

problem Proving Weinstein's and Arnold's conjectures in contact geometry.
method Existence of fundamental class in Legendrian contact instanton cohomology, evaluation transversality, and geometric construction of contactomorphisms.
result Proves Weinstein's and Arnold's conjectures in full generality.

The paper proves that most metrics satisfy a strong version of Arnold's conjecture for Laplace eigenvalues.

problem Understanding metrics that satisfy a strong version of Arnold's conjecture for Laplace eigenvalues.
method Using geometric characterizations and perturbation theory, the paper proves the conjecture for most metrics.
result The Strong Arnold Hypothesis is satisfied for all metrics except for a set of infinite codimension.

We prove conjectures of Rene Thom and Vladimir Arnold for C^2 solutions to the degenerate elliptic equation that is the level set equation for motion by mean curvature. We believe these results are the first instances of a general principle: Solutions of many degenerate equations behave as if they are analytic, even wh…

2017-12-14abs ↗pdf ↗

The Hessian Topology is a subject with interesting relations with some classical problems of analysis and geometry. In this article we prove a conjecture on this subject stated by V.I. Arnold concerning the number of connected components of hyperbolic homogeneous polynomials of degree nn. The proof is constructive and…

2013-01-11abs ↗pdf ↗

The Poincare function is a compact form of counting moduli in local geometric problems. We discuss its property in relation to V.Arnold's conjecture, and derive this conjecture in the case when the pseudogroup acts algebraically and transitively on the base. Then we survey the known counting results for differential in…

2018-02-05abs ↗pdf ↗

We use virtual neighborhood technique to establish GW-invariants, Quantum cohomology, equivariant GW-invariants, equivariant quantum cohomology and Floer cohomology for general symplectic manifold. We also establish GW-invariants for a family of symplectic manifolds. As a consequence, we prove Arnold conjecture for non…

1996-11-19abs ↗pdf ↗

We present some results supporting the Iwase-Sakai conjecture about coincidence of the topological complexity TC(X)TC(X) and monoidal topological complexity TCM(X)TC^M(X). Using these results we provide lower and upper bounds for the topological complexity of the wedge XYX\vee Y. We use these bounds to give a counterexample t…

2012-07-31abs ↗pdf ↗

Kolmogorov-Arnold Networks promise scalable performance in high dimensions.

problem Curse of dimensionality in multilayer perceptrons.
method Kolmogorov-Arnold representation theorem and interpolation methods.
result Kolmogorov-Arnold Networks achieve true freedom from the curse of dimensionality.

Revisits the connection between neural networks and the Kolmogorov-Arnold theorem.

problem Explains the limitations of using the Kolmogorov-Arnold theorem to explain neural networks with multiple hidden layers.
method Derives modifications of the Kolmogorov-Arnold representation that transfer smoothness properties to the outer function and can be well approximated by ReLU networks.
result Shows that a deep neural network with most layers approximating the interior function is a more natural interpretation of the Kolmogorov-Arnold representation.

Quotients Y=X/conjY=X/conj of complex surfaces by anti-holomorphic involutions conjXXconj\: X\to X tend to be completely decomposable when they are simply connected, i.e., split into connected sums, $n CP^2\#m\barCP2$, if w2(Y)0w_2(Y)\ne0, or into n(S2×S2)n(S^2\times S^2) if w2(Y)=0w_2(Y)=0. If XX is a double branched covering over CP2CP^2, th…

1995-06-14abs ↗pdf ↗

Arnold-Liouville systems cannot be bi-Hamiltonian generically.

problem The bi-Hamiltonian structure of Arnold-Liouville systems.
method Proving that a specific class of smooth functions is a meagre subset for the Fréchet topology, which implies Arnold-Liouville systems cannot be bi-Hamiltonian.
result Generically, Arnold-Liouville systems cannot be bi-Hamiltonian.

A new Kolmogorov-Arnold network improves function approximation and optimization.

problem Approximating potentially irregular functions in high dimensions.
method Proposes a new Kolmogorov-Arnold network (KAN) and provides error bounds and universal approximation theorems.
result Outperforms multilayer perceptrons in accuracy and convergence speed for irregular functions.

SVGP KAN integrates uncertainty quantification into Kolmogorov-Arnold networks.

problem Uncertainty quantification in scientific machine learning models.
method Sparse variational Gaussian process inference with Kolmogorov-Arnold topology.
result Demonstrated ability to distinguish aleatoric and epistemic uncertainty in various scientific applications.

Recently V. Arnold introduced Strangeness and J±J^{\pm} invariants of generic immersions of an oriented circle to R2\R^2. Here these invariants are generalized to the case of generic immersions of an oriented circle to an arbitrary surface FF. We explicitly describe all the invariants satisfying axioms, which naturall…

1999-06-18abs ↗pdf ↗

In this paper we will prove that for a compact, symplectic manifold (M,ω)(M, ω) and for ωω-compatible almost-complex structure J any properly perturbed J-holomorphic curve has a non-negative symplectic area. This non-negative property provides us with a new obstruction to the bubbling off phenomenon and thus allows us to…

2002-02-07abs ↗pdf ↗

Combines geometric hydrodynamics with magnetic systems to derive new equations and prove well-posedness.

problem Deriving new equations for magnetic systems and proving their well-posedness.
method Introducing the magnetic Euler-Arnold equation and proving well-posedness for specific equations.
result Local and global well-posedness results for the magnetic Euler-Arnold equation associated with the global quasi-geostrophic equations.

Unified framework for Arnold-type invariants via dual complexes and finite-difference structures.

problem Study of Arnold-type invariants of immersed curves and surfaces.
method Framework on dual complexes, locally normalized maps, finite-difference structures, and Shumakovitch-type identities.
result Unified evaluation of Arnold-type invariants St(1)St_{(1)} and St(2)St_{(2)} on dual skeleta.

We present another view dealing with the Arnold-Givental conjecture on a real symplectic manifold (M,ω,τ)(M, ω, τ) with nonempty and compact real part L=Fix(τ)L={\rm Fix}(τ). For given Λ(0,+]Λ\in (0, +\infty] and mN{0}m\in\N\cup\{0\} we show the equivalence of the following two claims: (i) (Lφ1H(L))m\sharp(L\capφ^H_1(L))\ge m for any Hamiltonia…

2008-06-01abs ↗pdf ↗

Hamiltonian minimality (H-minimality) for Lagrangian submanifolds is a symplectic analogue of Riemannian minimality. A Lagrangian submanifold is called H-minimal if the variations of its volume along all Hamiltonian vector fields are zero. This notion was introduced in the work of Y.-G. Oh in connection with the celebr…

2013-01-12abs ↗pdf ↗

Kolmogorov-Arnold Networks achieve optimal convergence rates in nonparametric regression.

problem Nonparametric function approximation in multivariate settings.
method Structured additive and multiplicative KANs using B-splines.
result Achieve minimax-optimal convergence rate O(n2r/(2r+1))O(n^{-2r/(2r+1)}) for Sobolev space functions.

Kolmogorov-Arnold Networks improve deep learning adaptivity and can approximate Besov functions optimally.

problem Improving deep learning adaptivity and understanding approximation rates.
method Analyzing Besov norms and using Res-KANs for approximation.
result KANs can optimally approximate Besov functions at the optimal rate.

Proposes a new neural network architecture combining MLP and basis functions.

problem Function approximation and operator learning in scientific machine learning.
method Combines robust MLP inner functions with flexible basis functions outer functions.
result KKAN outperforms MLPs and KANs in function approximation and operator learning tasks.