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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.

168,695 papers · 148 categories

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48 results for dynamical invariants

Invariant measures found for contact Hamiltonian systems split into Reeb and Liouville dynamics.

problem Finding invariant measures for contact Hamiltonian systems.
method Splitting the system into Reeb and Liouville dynamics; using invariant measures and symplectic sandwiches.
result Invariant measure found for Reeb dynamics; characterization of Liouville dynamics invariant measure.

Dynamic risk measures follow law invariance principles over time.

problem Tackles dynamic risk measurement principles.
method Shows equivalence between adapted law invariance and recursive one-step conditional-law representation for time-consistent risk measures.
result Identifies adapted law invariance as the dynamic counterpart of ordinary law invariance.

The paper introduces invariants to describe period-doubling routes to chaos in dynamical systems.

problem Understanding the dynamics of period-doubling routes to chaos in complex systems.
method Introducing three topological invariants to describe the topology of period-doubling routes to chaos.
result Ascribed symbolic dynamics to perturbations of the Shilnikov homoclinic scenario and dynamics of the Henon map.

Explains a 2D color exchange invariant correspondence to 3D linking numbers.

problem Understanding color exchange invariants in 2D dynamics and their 3D geometric interpretation.
method Visualizes invariants as linking of lines on a special surface with Arf-Kervaire invariant one, and interprets it as an obstruction to continuous transformation.
result Interprets a 2D color exchange invariant as a 3D linking number, providing a topological explanation.

Study of spectral invariants on CR contact manifolds with circle action.

problem Analytic torsion and eta-like invariants on CR contact manifolds.
method Interpret spectral series topologically and dynamically using Reeb flow.
result Spectral series can be interpreted both topologically and dynamically.

Proposes local coordinate frames for improving model performance in complex dynamical systems.

problem Improving model performance in complex, non-linear, and time-dependent dynamical systems.
method Introduces roto-translation invariant local coordinate frames for geometric graphs.
result The approach outperforms state-of-the-art models in various complex scenarios.

Proposes a method to learn stable invariant sets in dynamical systems.

problem Learning stable invariant sets in general dynamical systems.
method Generalizes Manek and Kolter's approach by introducing projection onto latent space shapes and using invertible neural networks.
result Validates the method and shows its usefulness for long-term prediction.

Study reveals failure of uniqueness in dynamical invariants for 3D volume-preserving diffeomorphisms.

problem Uniqueness of dynamical invariants for 3D volume-preserving diffeomorphisms.
method Examined failure of uniqueness on integral homology spheres and arbitrary three-manifolds using local and global invariants.
result Failure of uniqueness is severe, with continuous and non-constant invariants appearing in C1C^1-open sets of nonvanishing exact fields of fixed helicity.

The paper develops algorithms and topological invariants for distinguishing dynamic systems.

problem Distinguishing the topological type of surfaces and functions in dynamic systems.
method Construction of algorithms and topological invariants using discrete topological structures.
result The development of discrete topological structures for topological equivalence of dynamic systems.

Efficiently simulates slow dynamics of high-dimensional stochastic systems.

problem Simulating high-dimensional stochastic systems with slow dynamics and fast modes.
method Designs an algorithm to estimate an invariant manifold and its dynamics, averaging out fast modes.
result Efficient simulator of effective dynamics on low-dimensional invariant manifold.

Biracks are algebraic structures related to knots and links. We define a new enhancement of the birack counting invariant for oriented classical and virtual knots and links via algebraic structures called birack dynamical cocycles. The new invariants can also be understood in terms of partitions of the set of birack la…

2012-05-19abs ↗pdf ↗

A universal collection of 4 invariants improves neural network accuracy for molecular dynamics.

problem Improving accuracy of neural networks in molecular dynamics.
method Developed a universal collection of 4 smooth scalar invariants on M(3) x M(3) and evaluated their effectiveness in a PONITA neural network architecture.
result Using a universal collection of invariants significantly improves neural network accuracy.

The paper studies geometric loci and their invariants in complex dynamics.

problem Analyzing geometric loci and their invariants in complex dynamics.
method Intersection theory and dynamical invariants on the flex and gothic loci.
result Determined the divisor class of the flex locus and various tautological intersection numbers on the gothic locus.

The theory of quandle (co)homology and cocycle knot invariants is rapidly being developed. We begin with a summary of these recent advances. One such advance is the notion of a dynamical cocycle. We show how dynamical cocycles can be used to color knotted surfaces that are obtained from classical knots by twist-spinnin…

2002-04-10abs ↗pdf ↗

The paper defines unimodularity for coisotropic Poisson spaces and discusses invariant volume forms.

problem Understanding unimodularity and invariant volume forms for Hamiltonian dynamics on coisotropic Poisson spaces.
method Introducing multiplicative unimodularity and discussing its properties for coisotropic Poisson homogeneous spaces.
result Existence of invariant volume forms for explicit Hamiltonian systems on coisotropic Poisson spaces.

Deep learning detects bifurcations in dynamical systems.

problem Predicting catastrophic changes in dynamical systems across sciences.
method Data-driven, physically-informed deep-learning framework for classifying dynamical regimes and characterizing bifurcation boundaries.
result Extracts topologically invariant features to detect bifurcation boundaries in unseen systems.

We study the variation of a smooth volume form along extremals of a variational problem with nonholonomic constraints and an action-like Lagrangian. We introduce a new invariant describing the interaction of the volume with the dynamics and we study its basic properties. We then show how this invariant, together with c…

2016-02-28abs ↗pdf ↗

We consider cocycles of isometries on spaces of nonpositive curvature HH. We show that the supremum of the drift over all invariant ergodic probability measures equals the infimum of the displacements of continuous sections under the cocycle dynamics. In particular, if a cocycle has uniform sublinear drift, then there…

2011-12-02abs ↗pdf ↗

An Entropic Dynamics of exchange rates is laid down to model the dynamics of foreign exchange rates, FX, and European Options on FX. The main objective is to represent an alternative framework to model dynamics. Entropic inference is an inductive inference framework equipped with proper tools to handle situations where…

2019-08-18abs ↗pdf ↗

The paper explores the connection between Poisson-Lie structures and invariant volume forms in Hamiltonian dynamics.

problem Understanding the relationship between Poisson-Lie structures and invariant volume forms in Hamiltonian systems.
method Analyzing the existence and preservation of invariant volume forms under Hamiltonian vector fields on Poisson-Lie groups.
result A unimodular Poisson-Lie structure ensures the preservation of a multiple of any left-invariant volume, and the existence of a preserving volume form implies unimodularity.

Study shows invariant curves in tubular origami dynamics, revealing geometric barriers to folding transitions.

problem Understanding the dynamics and geometric barriers in tubular origami structures.
method Kolmogorov--Arnold--Moser (KAM) theory and numerical simulations.
result Invariant curves persist in large module limits, providing phase-space interpretation of folding modes.

New algorithms extract Koopman invariant subspaces from large-scale data.

problem Difficulty in discerning the Koopman invariant subspace from many Koopman eigenmodes.
method Multi-task feature learning and pruning procedure to remove spurious modes.
result Effective in approximating Koopman operator for complex flows.

The paper studies minimal resistance dynamics in radial fields, finding unique solutions for incompressible flows.

problem Nonlinear dynamics of minimal resistance in radial fields.
method Analysis of two non-equilibrium scenarios: scale-invariant free expansion and incompressible source flow.
result Incompressible flow acts as a structural regularizer, admitting unique, smooth, and strictly concave solutions.

New learning dynamics achieve fast convergence in games without needing to know utility scales.

problem Fast convergence guarantees in learning games require prior knowledge of utility scales.
method Developed scale-free and scale-invariant learning dynamics using optimistic follow-the-regularized-leader with adaptive learning rates and clipping techniques.
result Achieved fast convergence rates to Nash and correlated equilibria without prior utility scale knowledge.

The paper shows measures equidistribute on affine submanifolds with a rate.

problem Understanding equidistribution of measures on affine invariant submanifolds.
method Analyzing unstable foliations and using results from homogeneous dynamics.
result Measures of large dimension equidistribute on affine invariant submanifolds with an effective rate.

The paper studies invariant weighted Bergman metrics on domains.

problem Investigating invariant weighted Bergman metrics under biholomorphisms.
method Introducing invariant weight assignments, using Bergman's minimum integral method and domain version of Tian-Yau-Zelditch expansion.
result Uniform convergence of weighted Bergman kernels and metrics on uniform squeezing domains.

We develop an entropic framework to model the dynamics of stocks and European Options. Entropic inference is an inductive inference framework equipped with proper tools to handle situations where incomplete information is available. The objective of the paper is to lay down an alternative framework for modeling dynamic…

2019-08-18abs ↗pdf ↗

The paper generalizes relations between dynamical series and resolvents of vector fields.

problem Analyzing dynamical series using resolvents of vector fields.
method Derives the general form of relations involving intersection of kernel with integration currents for any smooth flow.
result Computes values of dynamical series and their relation with topological invariants.

Constructs algorithms to recognize and classify 2D surfaces.

problem Recognizing and classifying 2D surfaces in dynamic systems.
method Discrete topological structures and algorithms for simplicial and CW-complexes.
result Determines the topological type of 2-manifolds.

The study connects contact forms and Ruelle invariant in convex domains.

problem Understanding the relationship between contact forms and Ruelle invariant in convex domains.
method Using the extrinsic curvature and Ruelle invariant, the authors prove bounds and construct counterexamples.
result First examples of dynamically convex contact 3-spheres not strictly contactomorphic to convex boundaries.

The paper develops a new algorithm for RBMs using dynamical mean-field theory.

problem Learning in Restricted Boltzmann Machines (RBMs) with complex dependencies.
method Dynamical mean-field theory applied to RBMs with rectangular coupling matrices drawn from a bi-rotation invariant ensemble.
result The algorithm converges globally under a stability criterion, with rates matching numerical simulations.