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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.

168,742 papers · 148 categories

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72143215286 · May 202619922001200920172026
48 results for continuum differential geometry

We discuss some differential geometry pertaining to continuum mechanics and the route recently taken by D.N. Arnold, R.S. Falk, and R. Winther in deriving new improved finite element schemes in linear elasticity from constructions in projective geometry.

2010-05-12abs ↗pdf ↗

Within a framework of noncommutative geometry, we develop an analogue of (pseudo) Riemannian geometry on finite and discrete sets. On a finite set, there is a counterpart of the continuum metric tensor with a simple geometric interpretation. The latter is based on a correspondence between first order differential calcu…

1998-08-08abs ↗pdf ↗

In the framework of nonassociative geometry (hep-th/0003238) a unified description of continuum and discrete spacetime is proposed. In our approach at the Planck scales the spacetime is described as a so-called "diodular discrete structure" which at large spacetime scales `looks like' a differentiable manifold. After a…

2000-10-19abs ↗pdf ↗

Continuum Dropout improves neural differential equations by preventing overfitting.

problem Overfitting in Neural Differential Equations (NDEs).
method Introduces Continuum Dropout, a regularization technique based on alternating renewal processes.
result Continuum Dropout outperforms existing methods in various tasks, improving generalization and uncertainty quantification.

We are concerned with underlying connections between fluids, elasticity, isometric embedding of Riemannian manifolds, and the existence of wrinkled solutions of the associated nonlinear partial differential equations. In this paper, we develop such connections for the case of two spatial dimensions, and demonstrate tha…

2016-05-10abs ↗pdf ↗

Study of rigid body displacements in a projective space over dual numbers with geometric interpretations.

problem Understanding rigid body displacements in a novel geometric space.
method Projective differential geometry over the ring of dual numbers.
result Existence of non-straight curves with multiple osculating tangents.

Graph neural networks are extended to continuous-depth models using differential equations.

problem Improving graph neural networks for static and dynamic graph data.
method Formalizing GNNs as GDEs, blending discrete structures with differential equations.
result GDEs offer computational advantages in static settings and improved performance in dynamic settings.

In this paper we develop several algebraic structures on the simplicial cochains of a triangulated manifold that are analogues of objects in differential geometry. We study a cochain product and prove several statements about its convergence to the wedge product on differential forms. Also, for cochains with an inner p…

2005-05-11abs ↗pdf ↗

Lie groupoids and their associated algebroids arise naturally in the study of the constitutive properties of continuous media. Thus, Continuum Mechanics and Differential Geometry illuminate each other in a mutual entanglement of theory and applications. Given any material property, such as the elastic energy or an inde…

2017-12-23abs ↗pdf ↗

Neural GDEs improve graph prediction by blending discrete structures and differential equations.

problem Dynamic graph prediction challenges in irregularly sampled data.
method Continuous-depth graph neural networks (GNNs) with Neural GDEs.
result Neural GDEs enhance performance across various applications.

This paper presents a variational and multisymplectic formulation of both compressible and incompressible models of continuum mechanics on general Riemannian manifolds. A general formalism is developed for non-relativistic first-order multisymplectic field theories with constraints, such as the incompressibility constr…

2000-05-03abs ↗pdf ↗

Proves continuum limits of Lipschitz learning using Γ-convergence.

problem Semi-supervised learning with graph-based methods and continuum limits of pp-Laplacian learning.
method Proves continuum limits of Lipschitz learning using Γ-convergence.
result Proves ΓΓ-convergence in the LL^\infty-topology to the supremum norm of the gradient.

Framework learns physics-informed continuum models from molecular data.

problem Discovering accurate and robust data-driven continuum models from molecular simulation data.
method Operator regression framework using neural networks in modal space with physical inductive biases.
result Learned operators generalize to unseen system characteristics.

Study of convergence of point-object configurations to a charged dust continuum.

problem Understanding the convergence of discretized point-object configurations to a charged dust continuum.
method Establishing existence and uniqueness of horizons/minimal surfaces, studying geometries of regions exterior to minimal surfaces, and discussing limits.
result Examples of scalar curvature jumps upon taking Gromov-Hausdorff and intrinsic flat limits.

Automatically identifies geometric flat outputs for robotic systems.

problem Lack of systematic and practical means to identify flat outputs for arbitrary robotic systems.
method Casts the search for a globally valid, equivariant flat output as an optimization problem using Riemannian geometry, Lie group theory, and differential forms.
result Approximate transcription of continuum formulation to a quadratic program achieves precise agreement with known closed-form flat outputs.

This paper is an attempt at understanding the quantum-like dynamics of financial markets in terms of non-differentiable price-time continuum having fractal properties. The main steps of this development are the statistical scaling, the non-differentiability hypothesis, and the equations of motion entailed by this hypot…

2013-12-11abs ↗pdf ↗

We examine a Type-1 neck pinch singularity in simplicial Ricci flow (SRF) for an axisymmetric piecewise flat 3-dimensional geometry with 3-sphere topology. SRF was recently introduced as an unstructured mesh formulation of Hamilton's Ricci flow (RF). It describes the RF of a piecewise-flat simplicial geometry. In this …

2013-08-19abs ↗pdf ↗

Introduces neural point-forms for learning geometric features from noisy point clouds.

problem Learning geometric features from noisy point clouds with missing tangency information.
method Uses Laplacian-based techniques to build comparison matrices for point clouds, proving consistency under various assumptions.
result Neural point-forms provide a competitive and interpretable representation, especially beneficial for dense or manifold-like structures.

We investigated the feature map inside deep neural networks (DNNs) by tracking the transport map. We are interested in the role of depth (why do DNNs perform better than shallow models?) and the interpretation of DNNs (what do intermediate layers do?) Despite the rapid development in their application, DNNs remain anal…

2016-05-10abs ↗pdf ↗

In this paper we present a new theory of calculus over kk-dimensional domains in a smooth nn-manifold, unifying the discrete, exterior, and continuum theories. The calculus begins at a single point and is extended to chains of finitely many points by linearity, or superposition. It converges to the smooth continuum w…

2006-01-09abs ↗pdf ↗

Survey explores cohomology's roles in applied math and sciences.

problem Understanding cohomology's role in solving differential equations.
method Examining differential complexes and structure-preserving discretizations.
result Various fundamental concepts in mechanics are formulated using differential complexes.

Differential chains are a proper subspace of de Rham currents given as an inductive limit of Banach spaces endowed with a geometrically defined strong topology. Boundary is a continuous operator, as are operators that dualize to Hodge star, Lie derivative, pullback and interior product. Partitions of unity exist in thi…

2012-10-16abs ↗pdf ↗

Smooth knots can be embedded into a specific Menger continuum.

problem Embedding smooth knots into a specific type of continuum.
method Explicit construction using cubical models and self-similarity of the Menger continuum.
result Every smooth knot can be isotoped into the Menger continuum.

We prove the following result announced in Todorov and Valov: Any homogeneous, metric ANRANR-continuum is a VGnV^n_G-continuum provided dimGX=n1\dim_GX=n\geq 1 and Hˇn(X;G)0\check{H}^n(X;G)\neq 0, where GG is a principal ideal domain. This implies that any homogeneous nn-dimensional metric ANRANR-continuum with $\check{H}^n(X;G)\neq…

2012-08-31abs ↗pdf ↗

We present several principal bundles of embeddings of compact manifolds (with or without boundary) whose base manifolds are nonlinear Grassmannians. We study their infinite dimensional differential manifold structure in the Fréchet category. This study is motivated by the occurrence of such objects in the geometric Lag…

2014-02-06abs ↗pdf ↗

The paper deals with the Weyl equation which is the massless Dirac equation. We study the Weyl equation in the stationary setting, i.e. when the spinor field oscillates harmonically in time. We suggest a new geometric interpretation of the stationary Weyl equation, one which does not require the use of spinors, Pauli m…

2010-01-26abs ↗pdf ↗

We introduce the continuum self-similar tree (CSST) and characterize it topologically. We apply this to answer a question of Curien about the topology of the continuum random tree (CRT). We also give a topological characterization of other trees with branch points of finite or infinite valences.

2018-03-26abs ↗pdf ↗

The paper deals with the Weyl equation which is the massless Dirac equation. We study the Weyl equation in the stationary setting, i.e. when the the spinor field oscillates harmonically in time. We suggest a new geometric interpretation of the stationary Weyl equation, one which does not require the use of spinors, Pau…

2010-03-02abs ↗pdf ↗

New scheme optimizes BMI through probabilistic and geometric shaping.

problem Optimizing bit-wise mutual information (BMI) for coded modulation.
method Joint optimization of BMI through probabilistic and geometric shaping.
result Joint optimization enables a continuum of constellation geometries and probability distributions.

Study Bernstein-Gelfand-Gelfand complexes on Lipschitz domains, computing cohomology and applying to elasticity models.

problem Cohomology of BGG complexes on bounded Lipschitz domains.
method Computes cohomology of conformal deformation and Hessian complexes in Sobolev spaces, allowing multiple input complexes.
result Establishes conformal Korn inequality and proposes generalizations of continuum models with microstructures.

Geometrically reformulates Cosserat solid mechanics using differential geometry.

problem Formalizing Cosserat solid mechanics in modern differential geometry.
method Formulation as a principal fibre bundle, using Cartan's magic formula, and integrating infinitesimal strains.
result Reveals strain as a Lie algebra-valued one-form and finite strain through integration.

Dimension reduction of multivariate data supervised by auxiliary information is considered. A series of basis for dimension reduction is obtained as minimizers of a novel criterion. The proposed method is akin to continuum regression, and the resulting basis is called continuum directions. With a presence of binary sup…

2016-06-20abs ↗pdf ↗

Derives continuum model from discrete ε\varepsilon-graphs with connectivity functional.

problem Modeling diffusion in networks with varying connectivity.
method Energy-based continuum limit derivation, neural-network reconstruction of connectivity.
result Error between discrete and continuum energies is O(ε)O(\varepsilon), valid even with fluctuations.

An important question that discrete approaches to quantum gravity must address is how continuum features of spacetime can be recovered from the discrete substructure. Here, we examine this question within the causal set approach to quantum gravity, where the substructure replacing the spacetime continuum is a locally f…

2006-04-28abs ↗pdf ↗

New method converts video of dye plumes into PDEs for better understanding.

problem Inferring continuum models from uncalibrated video data.
method Develops a pipeline to convert grayscale recordings into scalar fields, isolates drift, and identifies transport laws.
result Selected reduced model outperforms advection-diffusion baselines and retains structural interpretability.

Theory models nonlinear soft tissue elasticity and remodeling using extended Finsler geometry.

problem Understanding and predicting the behavior of nonlinear soft tissues, especially in biologic contexts.
method Formulated a continuum mechanical theory incorporating extended Finsler geometry to describe the complex behaviors of fibrous soft solids.
result The model quantifies residual strains from growth, remodeling, and degradation, and predicts equilibrium configurations.

Generalizes Alexandroff's VnV^n-continua to cohomological dimensions.

problem Extending Alexandroff's concept of VnV^n-continua to cohomological dimensions.
method Proves that strongly locally homogeneous generalized continua with cohomological dimension nn are generalized VnV^n-spaces.
result Every strongly locally homogeneous continuum of covering dimension nn is a VnV^n-continuum in the sense of Alexandroff.

This paper studies continuum-armed bandits under Besov smoothness conditions and derives minimax rates.

problem Optimizing an unknown function with limited evaluations.
method Studies continuum-armed bandits under Besov smoothness conditions and derives minimax rates.
result Minimax rates over Besov spaces are identical to those over the smallest Hölder space into which Besov spaces embed.

A mesh-free method solves continuum-marginal optimal transport problems.

problem Recovering minimum-energy velocity fields from time-continuous probability marginals.
method Embeds weak continuity equation in a reproducing kernel Hilbert space, optimizing with mini-batch stochastic methods.
result Accurately recovers drift and maintains marginal consistency in synthetic experiments.