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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 shear-free condition

Researchers create a method to join hyperboloidal data sets without violating the shear-free condition.

problem Creating consistent initial data sets for simulations of spacetime.
method Developed a new gluing procedure that maintains the shear-free condition using special Hölder spaces and elliptic operators.
result Successfully constructed hyperboloidal initial data sets that preserve the shear-free condition.

The paper generalizes Alexandrov theorems for null hypersurfaces with integral curvature conditions.

problem Determining when a submanifold lies on a shear-free null hypersurface under integral curvature conditions.
method Using Minkowski formulas with arbitrary weight to derive rigidity results for submanifolds with weaker integral curvature conditions.
result A necessary and sufficient condition for a submanifold to lie in a shear-free null hypersurface is given by a mean curvature integral inequality.

We describe the relationship between complex-valued harmonic morphisms from Minkowski 4-space} and the shear-free ray congruences of mathematical physics. Then we show how a horizontally conformal submersion on a domain of Euclidean 3-space gives the boundary values at infinity of a complex-valued harmonic morphism on …

2003-06-27abs ↗pdf ↗

Equivalences between conformal foliations on Euclidean 33-space, Hermitian structures on Euclidean 44-space, shear-free ray congruences on Minkowski 44-space, and holomorphic foliations on complex 44-space are explained geometrically and twistorially; these are used to show that 1) any real-analytic complex-valued …

1996-03-13abs ↗pdf ↗

We show that the Euclidean Kerr-NUT-(A)dS metric in 2m2m dimensions locally admits 2m2^m hermitian complex structures. These are derived from the existence of a non-degenerate closed conformal Killing-Yano tensor with distinct eigenvalues. More generally, a conformal Killing-Yano tensor, provided its exterior derivativ…

2008-05-24abs ↗pdf ↗

Study of 3D trans-Sasakian manifolds using Newman--Penrose formalism.

problem Characterizing and understanding the geometry of 3D trans-Sasakian manifolds.
method Using Newman--Penrose formalism to encode the geometry of the structure vector field.
result Derivation of curvature and Laplacian identities for trans-Sasakian manifolds and their subclasses, including rigidity results.

In this paper we exploit the ideas and formalisms of twistor theory, to show how, on Minkowski space, given a null solution of the wave equation, there are precisely two null directions in kerdf\ker df, at least one of which is a shear-free ray congruence.

2010-03-01abs ↗pdf ↗

We obtain explicitly all solutions of the SU(infinity) Toda field equation with the property that the associated Einstein-Weyl space admits a 2-sphere of divergence-free shear-free geodesic congruences. The solutions depend on an arbitrary holomorphic function and give rise to new hyperKahler and selfdual Einstein metr…

1999-11-16abs ↗pdf ↗

The article introduces pseudo generalized Ricci-recurrent spacetimes and their applications in modified gravity.

problem Characterizing and understanding pseudo generalized Ricci-recurrent spacetimes.
method Introduced and characterized pseudo generalized Ricci-recurrent spacetimes, provided examples, and studied their implications in modified gravity.
result Pseudo generalized Ricci-recurrent spacetimes represent perfect fluid spacetimes and can model dark energy epochs or static spacetimes.

E. Cartan's method of moving frames is applied to 3-dimensional manifolds MM which are CR-embedded in 5-dimensional real hyperquadrics QQ in order to classify MM up to CR symmetries of QQ given by the action of one of the Lie groups SU(3,1)SU(3,1) or SU(2,2)SU(2,2). In the latter case, the CR structure of MM derives from a …

2018-08-26abs ↗pdf ↗

The null Penrose inequality, i.e. the Penrose inequality in terms of the Bondi energy, is studied by introducing a funtional on surfaces and studying its properties along a null hypersurface ΩΩ extending to past null infinity. We prove a general Penrose-type inequality which involves the limit at infinity of the Hawki…

2015-11-19abs ↗pdf ↗

Making use of the Kerr theorem for shear-free null congruences and of Newman's representation for a virtual charge ``moving'' in complex space-time, we obtain an axisymmetric time-dependent generalization of the Kerr congruence, with a singular ring uniformly contracting to a point and expanding then to infinity. Elect…

2009-08-07abs ↗pdf ↗

The classical Minkowski formula is extended to spacelike codimension-two submanifolds in spacetimes which admit "hidden symmetry" from conformal Killing-Yano two-forms. As an application, we obtain an Alexandrov type theorem for spacelike codimension-two submanifolds in a static spherically symmetric spacetime: a codim…

2014-09-08abs ↗pdf ↗

In this paper we consider pseudo-Riemannian spaces of arbitrary signature for which all of the polynomial curvature invariants vanish (VSI spaces). Using an algebraic classification of pseudo-Riemannian spaces in terms of the boost-weight decomposition we first show more generally that a space which is not characterise…

2015-04-07abs ↗pdf ↗

The paper develops a new approach to conditional risk measures using modular convex analysis.

problem Developing a new method for conditional risk measures.
method Random modular approach to conditional certainty equivalents and niveloids in the conditional LL^{\infty}-space.
result Retrieves a conditional variational formula for optimized certainty equivalents and applies it to the conditional entropic risk measure.

Paper constructs solutions to Bogomolny equations with specific boundary and asymptotic conditions.

problem Constructing solutions to Bogomolny equations with given boundary and asymptotic conditions.
method Using generalized Nahm pole boundary condition and real symmetry breaking condition.
result Solutions analogous to instanton solutions, satisfying different asymptotic conditions.

We extend probabilistic programming to handle conditioning on marginal distributions.

problem Conditioning probabilistic programs on marginal distributions of observable variables.
method We define and implement stochastic conditioning, allowing inference in probabilistic programs conditioned on marginal distributions.
result We demonstrate the effectiveness of stochastic conditioning in various real-life scenarios.

Paper finds necessary condition for logarithmic Minkowski problem in higher dimensions.

problem Logarithmic Minkowski problem in higher dimensions.
method Established a necessary condition through generalization and refinement of previous work.
result Generalizes and refines necessary condition for logarithmic Minkowski problem.

This paper introduces a neural operator for probabilistic conditioning.

problem Probabilistic conditioning of random variables XX given YY.
method Develops a single operator that maps any joint density to its conditional, approximated by neural operators.
result Neural operators can approximate the conditioning operator to arbitrary accuracy.

CSI method learns conditional distributions by estimating flow equations.

problem Learning conditional distributions in generative models.
method Estimates probability flow equations to transport reference to target distribution.
result Derives explicit expressions for conditional drift and score functions.

New conditional risk measures called conditional generalized quantiles defined and characterized.

problem Developing new risk measures for dynamic risk assessment.
method Propose and characterize conditional generalized quantiles using expected utility model and equivalent conditions.
result Characterized conditional generalized quantiles as well-defined and equivalent to a conditional first order condition.

A new method for learning conditional distributions using ODEs and neural networks.

problem Learning conditional distributions efficiently and accurately.
method Conditional Föllmer Flow, discretized with Euler's method, using nonparametric velocity estimation.
result Effective approximation of target conditional distributions, with convergence results for Wasserstein-2 distance.

Sharp statistical theory for conditional diffusion models.

problem Lack of theoretical foundation for conditional diffusion models.
method Sharp statistical theory with approximation of conditional score function.
result Sample complexity bound that adapts to data distribution smoothness.

An analysis is made of reality conditions within the context of noncommutative geometry. We show that if a covariant derivative satisfies a given left Leibniz rule then a right Leibniz rule is equivalent to the reality condition. We show also that the matrix which determines the reality condition must satisfy the Yang-…

1998-06-12abs ↗pdf ↗

We consider families of strongly consistent multivariate conditional risk measures. We show that under strong consistency these families admit a decomposition into a conditional aggregation function and a univariate conditional risk measure as introduced Hoffmann et al. (2016). Further, in analogy to the univariate cas…

2016-09-26abs ↗pdf ↗

Proposes a new method for interpreting feature importance and effects in dependent feature models.

problem Challenges in interpreting feature importance when features are dependent and interactions are present.
method Conditional Subgroup Approach
result Conditional PFI and PDP estimates based on this approach often outperform existing methods.

New boundary conditions solve Cauchy problem for Dirac operators on spacetimes.

problem Understanding non-local boundary conditions for Dirac operators on spacetimes.
method Define and analyze a class of Lorentzian boundary conditions that are local in time and non-local in spatial directions.
result Well-posed Cauchy problem for the Dirac operator is established under these conditions.

We extend CS divergence to conditional distributions and show its advantages in time series data and sequential decision making.

problem Quantifying the closeness between conditional distributions.
method Developed and estimated a conditional Cauchy-Schwarz divergence using kernel density estimation.
result Conditional CS divergence outperforms previous methods in time series clustering and sequential decision making.

We describe a Groebner basis of relations among conditional probabilities in a discrete probability space, with any set of conditioned-upon events. They may be specialized to the partially-observed random variable case, the purely conditional case, and other special cases. We also investigate the connection to generali…

2008-08-08abs ↗pdf ↗

A new method tests conditional independence by transforming it into an unconditional problem using transport maps.

problem Testing conditional independence between two random vectors given a third.
method Constructing transport maps to transform conditional independence into unconditional independence, estimating these maps from data using conditional continuous normalizing flow models.
result The proposed method is validated through simulations and real-data analysis, demonstrating practical effectiveness.

Generalizes moment-matching for exponential families with conditioning or hidden data.

problem Generalizing moment-matching conditions for exponential families with conditioning or hidden data.
method First-principles explanation and self-contained derivation of generalized moment-matching conditions.
result Derives generalized moment-matching conditions for conditional exponential families and hidden data.

DG algorithms often fail to generalize well in limited domains, highlighting necessary vs. sufficient conditions.

problem DG algorithms fail to consistently outperform ERM in limited domains.
method Examined necessary and sufficient conditions for DG, proposing a subspace alignment method.
result DG methods focus on sufficient conditions, often neglecting necessary conditions, leading to generalization failures.