Research
On-device research index

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.

169,181 papers · 148 categories

Trend · papers per month

326395126 · May 202619922001200920182026
48 results for shear flows

Physics-informed neural networks simulate solute dispersion in shear flows, validating complex transport mechanisms.

problem Simulating complex solute dispersion in asymmetric reactive environments.
method Physics-informed neural networks (PINNs) embedded with governing equations and boundary conditions.
result PINNs accurately predict solute dispersion, validating transport diagnostics.

Study uses neural networks to predict wall quantities in turbulent flows.

problem Predicting wall quantities in turbulent open channel flows.
method Training convolutional neural networks (FCN) and a proposed R-Net architecture to predict wall-shear-stress and wall pressure.
result R-Net architecture performs better and predicts wall quantities with around 10% error.

Study predicts shear stress in compound channels using data mining and machine learning.

problem Predicting shear stress distribution in symmetric compound channels.
method Conducted experiments to measure shear stress. Used data mining and machine learning models (RF, M5P, RC, KStar, AR) to predict.
result Random Forest (RF) model showed highest accuracy with R2=0.9.

Bayesian Monte-Carlo method assesses uncertainty in shear stress entropy models.

problem Uncertainty in evaluating shear stress entropy models remains an open question.
method Bayesian Monte-Carlo (BMC) uncertainty method to evaluate four entropy models.
result FOCB statistic index determines certainty of entropy models in shear stress estimation.

Sparse regression models CMs from oscillatory shear data efficiently.

problem Discovering parsimonious constitutive models from oscillatory shear experiments.
method Sparse regression with tensor basis functions, l1 regularization, and greedy two-stage algorithm.
result Inferred CMs extrapolate well beyond training data and flow conditions.

Study of circle homeomorphisms with square summable diamond shears.

problem Characterizing circle homeomorphisms with specific summability properties.
method Analysis of homeomorphisms in modular coordinates and comparison to Weil-Petersson class.
result Sharp results comparing new class to Weil-Petersson class and Hölder classes.

Study fluid spacetimes, proving shear-free implies vanishing expansion or vorticity.

problem Understanding shear and vorticity in perfect-fluid spacetimes.
method Analyzing perfect-fluid spacetimes using Weyl tensor and divergence.
result Proves shear-free implies vanishing expansion or vorticity for perfect fluids.

First we review the definition of a negative point mass singularity. Then we examine the gravitational lensing effects of these singularities in isolation and with shear and convergence from continuous matter. We review the Inverse Mean Curvature Flow and use this flow to prove some new results about the mass of a sing…

2010-08-10abs ↗pdf ↗

Thurston introduced shear deformations (cataclysms) on geodesic laminations - deformations including left and right displacements along geodesics. For hyperbolic surfaces with cusps, we consider shear deformations on disjoint unions of ideal geodesics. The length of a balanced weighted sum of ideal geodesics is defined…

2013-03-01abs ↗pdf ↗

The twist construction is a method to build new interesting examples of geometric structures with torus symmetry from well-known ones. In fact it can be used to construct arbitrary nilmanifolds from tori. In our previous paper, we presented a generalization of the twist, a shear construction of rank one, which allowed …

2017-02-17abs ↗pdf ↗

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.

Twisted SL2C\operatorname{SL}_2 \mathbb{C} local systems on surfaces of finite type appear often in geometry and physics. Most of them arise geometrically as local systems of charts for pleated hyperbolic structures. Bonahon and Thurston's "shear-bend coordinates" parameterize these local systems of charts. On a surface …

2015-10-20abs ↗pdf ↗

Link between Teichmüller and anti de Sitter geometry via length functions.

problem Understanding the geometry of Teichmüller space and anti de Sitter manifolds.
method Establishing a connection between Teichmüller space and anti de Sitter geometry through length functions.
result New purely anti de Sitter proofs of Teichmüller theory results.

The twist construction is a geometric model of T-duality that includes constructions of nilmanifolds from tori. This paper shows how one-dimensional foliations on manifolds may be used in a shear construction, which in algebraic form builds certain solvable Lie groups from Abelian ones. We discuss other examples of geo…

2015-05-31abs ↗pdf ↗

Shearing deformations in Hitchin representations are computed for a symplectic form.

problem Computing symplectic form pairings for Hitchin representations.
method Shearing deformations of Hitchin representations.
result Pairings of shearing deformations computed for the Atiyah-Bott-Goldman symplectic form.

Study circular foliations and shear-radius coordinates on hyperbolic cone surfaces.

problem Characterize Teichmüller spaces of hyperbolic cone surfaces.
method Construct circular foliations and shear-radius coordinates on Teichmüller spaces of hyperbolic cone surfaces.
result Shear-radius coordinates provide global coordinates on Teichmüller spaces and converge to specific metrics.

The paper extends optimal transport for linear separability of sheared distributions in supervised learning.

problem Learning on the space of probability measures using shifts and scalings.
method Embedding probability measures into L2L^2 spaces using optimal transport, then applying regular machine learning techniques.
result Sheared distributions can be linearly separated under certain conditions, with bounds on transformations.

The paper studies properties of triangle and shearing invariants in PSL(n,R) and connects them to a slice of Hitchin components.

problem Understanding invariants of PSL(n,R)-Fuchsian representations and their relationship to Hitchin components.
method Examined triangle and shearing invariants, used Bonahon-Dreyer parameterization.
result The Fuchsian locus of Hitchin components corresponds to a slice.

Machine learning improves cosmic shear measurements by compensating for feature noise.

problem Accurately measuring cosmic shear from galaxy images in the presence of various nuisance effects.
method Supervised machine learning with artificial neural networks trained on simulated data.
result Demonstrated competitive low shear biases in Euclid-like images.

Study quasisymmetric maps on hyperbolic plane boundaries.

problem Identify quasisymmetric maps corresponding to specific lambda lengths and flip distances.
method Analyze maps on Farey triangulation, relate to shearing coordinates and flip distance.
result Identify quasisymmetric maps corresponding to pinched lambda lengths and flip distances.

Given a semi-Riemannian manifold, we give necessary and sufficient conditions for a Riemannian submanifold of arbitrary co-dimension to be umbilical along normal directions. We do that by using the so-called \emph{total shear tensor}, i.e., the trace-free part of the second fundamental form. We define the \emph{shear s…

2017-01-21abs ↗pdf ↗

Enhanced Teichmüller space for surfaces with decorations and enhancements.

problem Parameterizing and understanding Teichmüller spaces with enhancements and decorations.
method Introduced a new variation of Teichmüller space, constructed parameterization, and introduced lamination space.
result Compatibility of shear coordinates and λ-length coordinates in the new deformation space.

Abstract: Poisson bracket on shear coordinates relates to Fenchel-Nielsen bracket on gluing parameters.

problem Relationship between Fenchel-Nielsen coordinates and shear coordinates on Riemann surfaces.
method Explicitly showed the Poisson bracket on shear coordinates induces the Fenchel-Nielsen bracket on gluing parameters.
result Poisson bracket on shear coordinates relates to Fenchel-Nielsen bracket on gluing parameters.

We show that the length function of a measured geodesic lamination is convex in Thurston's shear coordinates over Teichmüller space and strictly convex for generic laminations. We give some consequences of this result in the context of Thurston's asymmetric metric on Teichmüller space.

2014-08-25abs ↗pdf ↗

A simple property of Weyl tensor in shear-free, vorticity-free, acceleration-free velocity fields.

problem Proving a property of the Weyl tensor in specific velocity fields.
method Analyzing the Weyl tensor's divergence and contraction properties in shear-free, vorticity-free, acceleration-free velocity fields.
result The covariant divergence of the Weyl tensor is zero if the contraction of the Weyl tensor with the velocity is zero, and vice versa.

The paper models financial order books using geometric shears and directional liquidity.

problem Understanding the geometry and dynamics of financial order books.
method Structural framework modeling liquidity as emergent observables, geometric shears, and directional imbalances.
result The geometry of financial order books can be described by a rigid drift and geometric shear, leading to a gamma-like profile of projected liquidity.

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 ↗

Convolutional networks predict turbulence from wall quantities.

problem Predicting turbulence fields from wall-shear-stress components and wall pressure.
method Two CNN models: FCN and FCN-POD, trained on DNS data.
result FCN and FCN-POD models outperform EPOD in predicting turbulence fields.