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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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96192287383 · May 202619922001200920172026
48 results for Covariant Derivatives

Invariant covariant derivatives on homogeneous spaces are characterized.

problem Understanding invariant covariant derivatives on homogeneous spaces.
method Expressing covariant derivatives in terms of horizontally lifted vector fields and bilinear maps.
result Existence and characterization of invariant covariant derivatives.

The paper shows objective derivatives are covariant derivatives on Riemannian metrics.

problem The definition and interpretation of objective derivatives in continuum mechanics.
method Demonstrates that objective derivatives correspond to covariant derivatives on the manifold of Riemannian metrics.
result Objective derivatives are unified as covariant derivatives on the manifold of Riemannian metrics.

Constructs covariant derivatives for Ehresmann connections.

problem Developing a method for covariant derivatives in fibre bundles.
method Introducing a vertical endomorphism to construct covariant derivatives on vertical and horizontal distributions.
result Covariant derivatives can be constructed separately on vertical and horizontal distributions and then glued together.

Homotopy equivalence between formalities with different covariant derivatives.

problem Formality of Dolgushev depends on covariant derivative choice.
method Proved homotopy equivalence of LL_\infty-morphisms twisted by gauge equivalent elements.
result Globalized formalities with different covariant derivatives are homotopic.

We present a unified derivation of covariant time derivatives, which transform as tensors under a time-dependent coordinate change. Such derivatives are essential for formulating physical laws in a frame-independent manner. Three specific derivatives are described: convective, corotational, and directional. The covaria…

2001-02-28abs ↗pdf ↗

Formulae for non-symmetric connections derived from covariant derivatives.

problem Deriving commutation formulae for non-symmetric affine connections.
method Covariant derivatives of tensors with respect to symmetric and non-symmetric affine connections.
result Formulae for non-symmetric connections derived from covariant derivatives.

Study covariant derivatives of eigenfunctions on curved spaces, proving they are scalar multiples of the functions.

problem Understanding covariant derivatives of eigenfunctions on curved spaces.
method Analyzing the Laplace-Beltrami operator on Riemannian manifolds with constant curvature.
result Covariant derivatives of eigenfunctions are scalar multiples of the functions, and these scalars are polynomials in the eigenvalue.

Study on stochastic covariant derivatives in curved space-time.

problem Analyzing covariant derivatives in curved space-time under stochastic processes.
method Using Itô-Wiener processes and stochastic calculus, including Besov spaces, Schrödinger operators, and white noise.
result Developed a framework for stochastic geodesics and white noise in fractoid spaces.

Estimates for covariant derivatives and Riesz transforms on differential forms.

problem Bounding covariant derivatives and Riesz transforms on differential forms.
method Use Bismut derivative formula to prove heat kernel bounds and Riesz transform boundedness.
result Formulate and prove conjecture on boundedness of covariant local Riesz-transforms in L^p.

New non-separable covariance kernels for spatiotemporal data derived from harmonic oscillator physics.

problem Capturing complex spatiotemporal dependencies in Gaussian processes.
method Hybrid spectral method based on the harmonic oscillator, deriving explicit covariance kernels.
result Explicit non-separable covariance kernels with space-time interactions.

The paper optimizes regret using covariance between costs and decisions.

problem Optimizing expected regret in decision-making problems.
method Developed derivative theory of covariance regret functional, derived Gâteaux derivative, and extended to constrained optimization.
result Gradient of covariance regret is the cost covariance matrix, with implications for portfolio optimization.

Algorithm solves covariant exterior derivative equations in small regions.

problem Solving covariant exterior derivative equations in geometric and algorithmic ways.
method Linear homotopy operator of the Poincare lemma, constraints for parallel transport equations.
result Solves covariant constant and related equations in a geometric and algorithmic way.

Study of generalized vector bundles and their geometric tools.

problem Extension of differential geometric tools to infinite dimensional vector bundles.
method Analysis of automorphisms, frame bundle, connection 1-forms, and covariant derivatives in diffeological vector pseudo-bundles.
result Non-isomorphism between connection 1-forms and covariant derivatives in infinite dimensional cases.

Defines natural tensors for submanifolds of pseudo-Riemannian manifolds.

problem Characterizing tensors for submanifolds of pseudo-Riemannian manifolds.
method Constructs geodesic normal coordinates and expresses metric coefficients as polynomials in curvature and second fundamental form derivatives.
result Natural tensors are linear combinations of contractions of curvature and second fundamental form derivatives.

Recently Berman and Perry constructed a four-dimensional M-theory effective action which manifests SL(5) U-duality. Here we propose an underlying differential geometry of it, under the name `SL(5) U-geometry' which generalizes the ordinary Riemannian geometry in an SL(5) compatible manner. We introduce a `semi-covarian…

2013-02-07abs ↗pdf ↗

Develops a hedging method for multi-asset derivatives with correlation risk.

problem Hedging multi-asset derivatives exposed to correlation and covariance risk.
method Combines dynamic trading with static hedging instruments using Galtchouk--Kunita--Watanabe decomposition.
result Explicit semi-static replication formulas for covariance swaps and geometric dispersion trades.

Proves stability of Minkowski space-time for Einstein-Yang-Mills equations.

problem Stability of Minkowski space-time for perturbations governed by Einstein-Yang-Mills equations.
method Proves exterior energy estimates for tensorial non-linear wave equations in Minkowski space-time.
result Proves exterior stability of Minkowski space-time for Einstein-Yang-Mills equations.

For a smooth manifold MM, it was shown in \cite{BPH} that every affine connection on the tangent bundle TMTM naturally gives rise to covariant differentiation of multivector fields (MVFs) and differential forms along MVFs. In this paper, we generalize the covariant derivative of \cite{BPH} and construct covariant deri…

2014-08-18abs ↗pdf ↗

Study semi-supervised learning with noisy proxy covariates, deriving bounds and showing gains.

problem Learning from noisy proxy covariates with scarce labels.
method Two-stage estimator learning kernel eigenfeatures from all proxy covariates and fitting a ridge predictor on labeled data.
result Finite sample bounds show fast labeled sample rates and consistent gains over supervised and semi-supervised baselines.

Abstract reviews recent Lagrangian analysis on immersions into higher dimensions.

problem Analyzing Lagrangians on immersions into higher dimensions.
method Reviews recent progress on Lagrangians on immersions with first and second fundamental forms and their derivatives.
result Recent progress in the analysis of Lagrangians on immersions into higher dimensions.

Batch Active Learning uses derivative information for Gaussian Process regression.

problem Efficiently selecting data batches in Gaussian Process regression models.
method Proposes using the predictive covariance matrix to select data batches, exploiting full correlation.
result Demonstrates the effectiveness of incorporating derivative information across diverse applications.

A regular normal parabolic geometry of type G/PG/P on a manifold MM gives rise to sequences DiD_i of invariant differential operators, known as the curved version of the BGG resolution. These sequences are constructed from the normal covariant derivative $\na^\om$ on the corresponding tractor bundle V,V, where $\om$ is…

2010-03-31abs ↗pdf ↗

Abstract: Review and definitions of generalised spin structures, their connections, and symmetry algebra.

problem Understanding and characterizing generalised spin structures and their properties.
method Definitions, basic notions, connections, covariant Lie derivative, covariant Cartan calculus, symmetry algebra.
result Characterization of homogeneous generalised spin structures.

ULA estimates covariance of log-concave distributions efficiently.

problem Estimating covariance matrices of log-concave distributions efficiently.
method Unadjusted Langevin algorithm (ULA) for sampling and covariance estimation.
result Sample complexity of single-chain ULA is smaller than that of parallel ULA by a logarithmic factor.

This paper studies covariant derivatives for Lie groupoids with representation-valued forms.

problem Understanding covariant derivatives for Lie groupoids with representation-valued forms.
method The paper explores two approaches: linear connections and multiplicative Ehresmann connections, both yielding geometrically richer curved double complexes.
result The horizontal exterior covariant derivative DD is a key finding, generalizing the well-known operator from principal bundles.

The paper calculates sensitivities for financial derivatives using path weighting methods.

problem Computing sensitivities for path-dependent financial derivatives with high variance and degeneracy issues.
method Proposes explicit path weighting formula, variance reduction adjustment, and covariance inflation technique.
result Effective methods to address high variance and degeneracy in sensitivities computation.

Study variance-optimal hedging of forward curve derivatives under stochastic volatility.

problem Variance-optimal hedging of forward curve derivatives with stochastic volatility.
method Assumes HJM-Musiela dynamics modulated by stochastic covariance, uses Galtchouk-Kunita-Watanabe projection.
result Density of finite-maturity strategies, convergence of finite-rank projections, decomposition of hedging error.

The n-th order covariant derivative on a smooth manifold with an affine connection is a differential operator which turns a function into a tensor field of type (0,n). In this paper the properties of this operatior related to the permutation of indices are investigated by means of non-associative algebra. The general f…

2006-05-02abs ↗pdf ↗

We obtain a complete time expansion of the pull-back operator generated by a real analytic flow of real analytic automorphisms acting on analytic tensor sections of a manifold. Our expansion is given in terms of multiple Lie derivatives. Motivated by this expansion, we provide a rather simple and explicit estimate for …

2018-06-21abs ↗pdf ↗

This work further develops the properties of fractional differential forms. In particular, finite dimensional subspaces of fractional form spaces are considered. An inner product, Hodge dual, and covariant derivative are defined. Coordinate transformation rules for integral order forms are also computed. Matrix order f…

2003-01-13abs ↗pdf ↗

This paper, sixth in a series of eight, uses the geometric calculus on manifolds developed in previous papers of the series to introduce through the concept of a metric extensor field g a metric structure for a smooth manifold M. The associated Christoffel operators, a notable decomposition of that object and the assoc…

2005-01-31abs ↗pdf ↗

Introduces a new phase space for 2D supersymmetric sigma models.

problem Developing a new Hamiltonian formulation for 2D supersymmetric sigma models.
method Introduces a phase space with spinorial momenta and derives a covariant Hamiltonian formulation.
result Shows the existence of additional supersymmetries in the new formulation.

Extends covariance estimation with multiple targets for better performance.

problem Improving covariance estimation for multiple targets.
method Combines multiple constant matrices with sample covariance matrix, derives estimators and proves convergence.
result The multi-target linear shrinkage estimator outperforms other estimators in various situations.

Biological and social systems consist of myriad interacting units. The interactions can be represented in the form of a graph or network. Measurements of these graphs can reveal the underlying structure of these interactions, which provides insight into the systems that generated the graphs. Moreover, in applications s…

2014-11-08abs ↗pdf ↗

The paper studies sections of time-like twistor spaces with specific covariant derivatives.

problem Sections of time-like twistor spaces with light-like or zero covariant derivatives.
method Analyzes conformal Gauss maps of time-like minimal surfaces and properties of almost paracomplex structures.
result Sections of time-like twistor spaces have light-like or zero covariant derivatives.

Study on friction forces for nonholonomic systems using affine connections.

problem Realizing nonholonomic constraints with strong friction forces.
method Affine connection approach, covariant derivatives, recursive procedure.
result Approximations of slip velocities and dynamics up to second order.