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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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186373559745 · Jun 202019922001200920172026
48 results for time dimension

New geometric flow equations describe how space-time dimensions change.

problem Understanding how the number of space-time dimensions affects geometry.
method Developed D-flow equations to model the variation of space-time geometries.
result Solutions for D-flow equations on D-dimensional spheres and Freund-Rubin Compactification.

We derive precise transformation formulas for synthetic lower Ricci bounds under time change. More precisely, for local Dirichlet forms we study how the curvature-dimension condition in the sense of Bakry-Emery will transform under time change. Similarly, for metric measure spaces we study how the curvature-dimension c…

2019-07-12abs ↗pdf ↗

A large class of vacuum space-times is constructed in dimension 4+1 from hyperboloidal initial data sets which are not small perturbations of empty space data. These space-times are future geodesically complete, smooth up to their future null infinity, and extend as vacuum space-times through their Cauchy horizon. Dime…

2001-06-20abs ↗pdf ↗

We propose studies of special Riemannian geometries with structure groups H1=SO(3)SO(5)H_1=SO(3)\subset SO(5), H2=SU(3)SO(8)H_2=SU(3)\subset SO(8), H3=Sp(3)SO(14)H_3=Sp(3)\subset SO(14) and H4=F4SO(26)H_4=F_4\subset SO(26) in respective dimensions 5, 8, 14 and 26. These geometries, have torsionless models with symmetry groups G1=SU(3)G_1=SU(3), $G_2=SU(3)\times SU(3)…

2006-03-28abs ↗pdf ↗

The paper extends the spacetime positive mass theorem to multiple time dimensions.

problem Proving the nonnegativity of mass in spacetimes with multiple time dimensions.
method Generalizing the spacetime positive mass theorem to include multiple time dimensions and showing mass nonnegativity through energy inequalities.
result Equality in the energy inequality implies a foliation by flat submanifolds.

We prove that for geometrically finite groups cohomological dimension of the direct product of a group with itself equals 2 times the cohomological dimension dimension of the group.

2019-02-08abs ↗pdf ↗

For an ancient solution of the mean curvature flow, we show that each time slice M_t is contained in an affine subspace with dimension bounded in terms of the density and the dimension of the evolving submanifold. Recall that an ancient solution is a family M_t that evolves under mean curvature flow for all negative ti…

2005-03-01abs ↗pdf ↗

Generative model handles varying data dimensions using jump diffusion processes.

problem Handling data of varying dimensionality in generative models.
method Formulated as a jump diffusion process, learning to approximate the process with a novel evidence lower bound.
result Effective sampling of data of varying dimensionality, better compatibility with test-time diffusion guidance imputation tasks.

The paper extends the avoidance principle for mean curvature flows, proving new intersection dimension monotonicity results.

problem Understanding the behavior of intersections in mean curvature flows.
method Proving new intersection dimension monotonicity results for mean curvature flows, Brakke flows, and level set flows.
result The dimension of the intersection of mean curvature flows is non-increasing over time.

The authors characterize flexibility in power and energy markets considering time, spatiality, resource, and risk.

problem Evaluating and maximizing flexibility in power systems and markets.
method Characterization of flexibility dimensions (time, spatiality, resource, risk) and their interrelations with flexibility assets, products, and services.
result Flexibility should be evaluated based on multiple dimensions for efficient power systems and markets.

We prove that if G=G1××GnG = G_1\times\dots\times G_n acts essentially, properly and cocompactly on a CAT(0) cube complex X, then the cube complex splits as a product. We use this theorem to give various examples of groups for which the minimal dimension of a cube complex the group acts on is strictly larger than that of the…

2019-12-11abs ↗pdf ↗

The article examines entropy-information inequalities for continuous-time Markov chains under curvature-dimension conditions.

problem Proving Li-Yau inequalities and modified logarithmic Sobolev inequalities for reversible Markov chains.
method Introducing the CDΥ(κ,F)CD_Υ(κ,F) condition and deriving entropy-information inequalities.
result Derives functional inequalities relating entropy to Fisher information.

Researchers find solutions to Einstein equations in higher dimensions.

problem Finding spatially homogeneous solutions to vacuum Einstein equations in general dimensions.
method Assumed spatially homogeneous spacetime, solved Einstein equations for globally hyperbolic spacetimes with specific symmetry groups.
result Spatially homogeneous solutions found, corresponding to Bianchi type II in 4D, and constraints on spacetime expansion.

We show some results for the L2L^2 curvature flow linked by the theme of addressing collapsing phenomena. First we show long time existence and convergence of the flow for SO(3)SO(3)-invariant initial data on S3S^3, as well as a long time existence and convergence statement for three-manifolds with initial L2L^2 norm of c…

2012-01-05abs ↗pdf ↗

Proposes a neural network for handling multi-sensor time series with varying input dimensions.

problem Handling multi-sensor time series with varying input dimensions.
method Graph neural network conditioning vectors for zero-shot transfer learning.
result Better generalization in activity recognition and equipment prognostics datasets.

In this paper, based on an intrinsic definition of asymptotically AdS space-times, we show that the standard anti-de Sitter space-time is the unique strictly stationary asymptotically AdS solution to the vacuum Einstein equations with negative cosmological constant in dimension less than 7. Instead of using the positiv…

2003-10-18abs ↗pdf ↗

Leave-one-out cross-validation (LOOCV) can be particularly accurate among cross-validation (CV) variants for machine learning assessment tasks -- e.g., assessing methods' error or variability. But it is expensive to re-fit a model NN times for a dataset of size NN. Previous work has shown that approximations to LOOCV…

2019-05-31abs ↗pdf ↗

We introduce the notion of asymptotic cohomology based on the bounded cohomology and define cohomological asymptotic dimension $\as_{\Z} X$ of metric spaces. We show that it agrees with the asymptotic dimension $\as X$ when the later is finite. Then we use this fact to construct an example of a metric space XX of boun…

2006-08-09abs ↗pdf ↗

Study finite time singularities in Ricci flow with bounded scalar curvature.

problem Understanding finite time singularities in Ricci flow with bounded scalar curvature.
method Analyzing blow-up sequences of locally Type I singularities.
result Every blow-up sequence of a locally Type I singularity has a specific property.

Langevin Dynamics speeds up mixing time with manifold hypothesis and multi-scale approach.

problem Langevin Dynamics struggles in high dimensions and nonconvex landscapes.
method Utilizes manifold hypothesis to reduce mixing time and employs multi-scale approach to improve image generation quality.
result Mixing time depends on intrinsic dimension rather than ambient dimension, significantly reducing computational complexity.

We define the Kodaira dimension for 33-dimensional manifolds through Thurston's eight geometries, along with a classification in terms of this Kodaira dimension. We show this is compatible with other existing Kodaira dimensions and the partial order defined by non-zero degree maps. For higher dimensions, we explore th…

2014-04-16abs ↗pdf ↗

This work analyzes Gibbs samplers for Bayesian hierarchical models without dimensionality constraints.

problem Analyzing convergence properties of Gibbs samplers for Bayesian hierarchical models.
method Using Bayesian asymptotics and total variation mixing times, the study provides dimension-free convergence results.
result Dimension-free convergence results for Gibbs samplers targeting hierarchical models under random data-generating assumptions.

We investigate Ising model description of dynamics of stock price. The model is defined in near 2 dimensions, one dimension is time and another represents ensemble of stocks, and strength of response of investors to price change corresponds to inverse temperature of the system. At critical temperature, infinitely long …

2004-02-20abs ↗pdf ↗

We study the relation between critical exponents and Hausdorff dimensions of limit sets for projective Anosov representations. We prove that the Hausdorff dimension of the symmetric limit set in P(Rn)×P(Rn)\mathbf{P}(\mathbb{R}^{n}) \times \mathbf{P}({\mathbb{R}^{n}}^*) is bounded between two critical exponents associated respe…

2019-02-05abs ↗pdf ↗

We define a family of functionals generalizing the Yang-Mills functional. We study the corresponding gradient flows and prove long-time existence and convergence results for subcritical dimensions as well as a bubbling criterion for the critical dimensions. Consequently, we have an alternate proof of the convergence of…

2015-05-26abs ↗pdf ↗

The correspondence of stationary, axisymmetric, asymptotically flat space-times and bundles over a reduced twistor space has been established in four dimensions. The main impediment for an application of this correspondence to examples in higher dimensions is the lack of a higher-dimensional equivalent of the Ernst pot…

2012-06-30abs ↗pdf ↗

Sparse OSEs achieve optimal embedding dimension of O(d).

problem Achieving optimal embedding dimension for sparse OSEs.
method Random sparsified matrix with m(1+θ)dm \geq (1+θ)d non-zeros per column.
result Sparse OSEs can achieve embedding dimension m=O(d)m=O(d), improving on previous m=O(dlog(d))m=O(d\log(d)).

A new method uses deep learning to efficiently solve complex physics equations in high dimensions.

problem Efficiently solving high-dimensional time-dependent PDEs with dynamic solutions.
method Deep adaptive sampling framework for PINNs extended to spacetime domains using normalizing flows.
result The method effectively identifies and tracks high-residual regions in both space and time.

Dynamic risk factor model improves portfolio performance in high dimensions.

problem Dynamic portfolio allocation in high-dimensional financial markets.
method Time-varying sparsity on factor loadings, sequential learning of parameters and volatilities.
result Significant portfolio performance improvements and higher utility gains.

The study constructs metrics with positive 2nd Ricci curvature on various manifolds.

problem Constructing metrics with positive 2nd Ricci curvature on closed manifolds.
method Generalization of the concept of fatness to ensure the existence of metrics with positive 2nd Ricci curvature on certain homogeneous bundles.
result Infinitely many examples of manifolds with positive 2nd Ricci curvature, including non-simply connected spaces.

A new stable similarity measure for time series using persistent homology.

problem Constructing a robust measure of time series similarity.
method Persistent homology for stability, bi-conditional periodicity score for similarity.
result Stability of the bi-conditional periodicity score under perturbations and dimension reduction.